diff --git a/.gitattributes b/.gitattributes
index f4e74a7ad7d225998f59d498d6bd89daafb582a7..8543a5cd85f0bdedead25248f63796ca746d7e03 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -63,3 +63,29 @@ experiments/robotwin-native/standalone-3/combined.mp4 filter=lfs diff=lfs merge=
experiments/robotwin-native/kinex_policy-2/combined.mp4 filter=lfs diff=lfs merge=lfs -text
experiments/robotwin-native/kinex-3/combined.mp4 filter=lfs diff=lfs merge=lfs -text
experiments/robotwin-native/kinex_policy-3/combined.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-1/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-1/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-1/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-2/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-2/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-2/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-2/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-2/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-2/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-1/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-1/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-1/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-1/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-1/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-1/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-3/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-3/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex_policy-3/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-3/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-3/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-2/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-2/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/kinex-2/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-3/presentation/poster.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-3/presentation/terminal.jpg filter=lfs diff=lfs merge=lfs -text
+experiments/robotwin-native/standalone-3/presentation/video.mp4 filter=lfs diff=lfs merge=lfs -text
diff --git a/app.js b/app.js
index 64d4655cf283bb9531b7cfdba7c454db579fedea..fa26724abf7e95753e4421987513df22b198cf82 100644
--- a/app.js
+++ b/app.js
@@ -1,22 +1,546 @@
'use strict';
-const $=s=>document.querySelector(s),esc=x=>String(x??'').replace(/[&<>"']/g,c=>({'&':'&','<':'<','>':'>','"':'"',"'":'''}[c]));
-const num=x=>x==null?'—':Number(x).toLocaleString('en-US'),money=x=>x==null?'—':'$'+Number(x).toFixed(4);
-let data;const cache=new Map();
-async function load(path){if(!cache.has(path)){const r=await fetch(path);if(!r.ok)throw new Error(`${path}: ${r.status}`);cache.set(path,await r.json());}return cache.get(path)}
-const condition=id=>data.conditions.find(x=>x.id===id),episode=(t,c)=>data.episodes.find(e=>e.task===t&&e.condition===c);
-const state=e=>!e?'pending':e.valid===false?'invalid':e.success===true?'success':e.success===false?'failure':e.status||'pending';
-const badge=(e,url)=>`${{success:'Success',failure:'Failure',invalid:'Interrupted',pending:'Pending',running:'Running'}[state(e)]||esc(state(e))} `;
-const route=(t,c,tab='overview')=>`#episode/${t}/${c}/${tab}`;
-function matrix(){return `Task · seed 0 ${data.conditions.map(c=>`${esc(c.label)} `).join('')}Action limit ${data.tasks.map(t=>`${esc(t.label)} ${badge(episode(t.id,c.id),route(t.id,c.id))} `).join('')}${num(t.max_steps)}
${esc(c.label)} ${esc(c.model)}
${es.length?(100*wins/es.length).toFixed(0)+'%':'—'}
${wins} / ${es.length} successful · ${all.filter(e=>e.status==='complete').length} / ${data.tasks.length} completed
${es.length?num(es.reduce((n,e)=>n+(e.input_tokens||0)+(e.output_tokens||0),0)):'—'} tokens ${(!es.length||es.some(e=>e.api_cost_usd==null))?'—':money(es.reduce((n,e)=>n+(e.api_cost_usd||0),0))} API equivalent
RoboTwin 2.0 · task03 · single seed
${tasksOnly?'Explore tasks':'Agent decisions. Policy actions.'} Standalone VLA, Kinex, and Kinex with a native policy tool.
${tasksOnly?'':`${cards}
`}
Matched task comparison ${matrix()}Same instructions, seeds and native control budgets. Three-task behavior pilot; incomplete episodes are excluded from success-rate denominators.
← All experiments ${data.tasks.map(x=>`${esc(x.label)} `).join('')} ${data.conditions.map(x=>`${esc(x.label)} `).join('')} ${badge(e,route(tid,cid))}
${esc(t.label)} ${esc(c.model)} · ${num(t.max_steps)} action steps · seed 0
`;$('#task-select').onchange=x=>location.hash=route(x.target.value,cid,tab);$('#condition-select').onchange=x=>location.hash=route(tid,x.target.value,tab);const target=$('#detail-content');if(!e||!e.path){target.innerHTML='Episode pending
';return}const d=await load(e.path+'/detail.json');if(!document.contains(target))return;
-const metrics=`${[['Native steps',num(e.control_steps)],['Tool calls',num(e.tool_calls)],['VLA inferences',num(e.vla_calls)],['Input / output',`${num(e.input_tokens)} / ${num(e.output_tokens)}`],['Cached input',num(e.cached_input_tokens)],['API equivalent',money(e.api_cost_usd)]].map(([k,v])=>`
${v} ${k}
`).join('')}
${e.video?`
`:'
Recording is not available yet
'}${metrics}
${esc(d.cost_note||'API-equivalent cost is an estimate, not a subscription charge.')} ${esc(d.media_note||'')}
Task instruction ${esc(d.instruction)}
${num(v.length)} messages · Download full session
${v.map(m=>`${esc(m.role)} ${esc(m.name||'')} ${esc(m.text)}
${(m.images||[]).map(x=>`
`).join('')}
Recorded payload ${esc(JSON.stringify(m.data,null,2))} Standalone evaluation has no planning-agent session.
'}`;}
-else if(tab==='tools'){const v=await load(e.path+'/tool-calls.json');target.innerHTML=`${num(v.length)} calls · Download tool calls
${v.map((m,i)=>`${i+1}. ${esc(m.name)} ${esc(m.summary||'')} Input ${esc(JSON.stringify(m.input,null,2))} Output ${esc(typeof m.output==='string'?m.output:JSON.stringify(m.output,null,2))} No agent tool calls
'}`;}
-else if(tab==='policy'){const v=await load(e.path+'/policy-calls.json');target.innerHTML=`${num(v.length)} inferences · Download all input / output records
${v.map((m,i)=>`${i+1}. ${esc(m.task)} ${m.inference_s?.toFixed(2)||'—'} s ${(m.images||[]).map(x=>`
`).join('')}
Predicted actions and interface conversion ${esc(JSON.stringify(m.output,null,2))} No VLA inference recorded
'}`;}}
-function protocol(){$('#main').innerHTML=`Experiment protocol
One task. Three control choices. Execution ${[['Suite','RLE-Bench task03 · RoboTwin 2.0 · ALOHA AgileX'],['VLA','StarVLA/Qwen3-VL-OFT-Robotwin2 · steps 40,000'],['Agent','Kinex · GPT-6 Astra · high'],['Policy interface','Native run_policy · one inference per call · agent owns the outer loop'],['Inputs','VLA: three RGB views and language. Kinex: public RGB-D, joint state, calibration and native tools.'],['Control','25 Hz native joint / gripper frames; original task-specific limits'],['Selection','First three task03 tasks, seed 0; frozen before outcome inspection'],['Scope','Frozen-policy behavior only; no encoder or progress monitor']].map(([k,v])=>`${k} ${v}
This fixed-rate device protocol differs from upstream VLA trajectory execution. Published StarVLA benchmark scores are not a direct comparison. RoboTwin 2.0-Plus is a separate suite and is not included here.
Source and model identities ↗ `}
-async function render(){try{const parts=location.hash.slice(1).split('/');if(parts[0]==='episode')await detail(parts[1],parts[2],parts[3]||'overview');else if(parts[0]==='protocol')protocol();else overview(parts[0]==='tasks')}catch(e){$('#main').innerHTML=``}}
-fetch('data.json').then(r=>r.json()).then(x=>{data=x;window.addEventListener('hashchange',render);render()}).catch(e=>{$('#main').textContent=e.message});
+const plannedProtocol = (task, variant) => task.planned_protocol_by_variant?.[variant] || task.planned_protocol;
+// RoboEnv LIBERO raw counters include five initialization frames; RoboBridge counters do not.
+const actionSteps = (value, task, variant=task?.variant || current.variant || filters.variant) => Number.isFinite(value) ? Math.max(0, value - (task?.initialization_control_steps ?? task?.planned_protocol_by_variant?.[variant]?.initialization_control_steps ?? 0)) : null;
+const currentBudget = task => data.budget_defaults?.tasks?.[task.native_id]?.action_step_limit ?? null;
+const budgetNote = task => `${currentBudget(task)==null?'':`Current benchmark default: ${number(currentBudget(task))} action steps. `}${task.family==='task02'?'RoboEnv and rosbridge displays exclude five initialization steps; RoboBridge directly counts agent actions. ':''}Recorded episodes and campaign plans retain their original budgets.
`;
+const $ = s => document.querySelector(s);
+const $$ = s => [...document.querySelectorAll(s)];
+const esc = value => String(value ?? '').replace(/[&<>"']/g, c => ({'&':'&','<':'<','>':'>','"':'"',"'":'''}[c]));
+const number = v => v == null ? '—' : Number(v).toLocaleString('en-US');
+const compact = v => v == null ? '—' : Math.abs(v) >= 1e9 ? (v/1e9).toFixed(2)+'B' : Math.abs(v) >= 1e6 ? (v/1e6).toFixed(2)+'M' : Math.abs(v) >= 1e3 ? (v/1e3).toFixed(1)+'K' : Math.round(v).toString();
+const pct = v => v == null ? '—' : (v*100).toFixed(1)+'%';
+const elapsed = v => v == null ? '—' : v >= 3600 ? (v/3600).toFixed(1)+' h' : v >= 60 ? (v/60).toFixed(1)+' min' : v.toFixed(1)+' s';
+const arrow = '↗ ';
+const colors = {'standalone':'#39819c','kinex_policy':'#756ee4','kinex':'#27847a','codex-astra-spectator':'#a76a34','codex-astra':'#39819c','kinex-astra':'#756ee4','cc-opus':'#b48566','kinex-opus':'#958bc8','cc-opus-vertex-high':'#c9875a','cc-opus-vertex-xhigh':'#8c5a3a','kinex-opus-vertex-high':'#5b8bd8','kinex-opus-vertex-xhigh':'#3a5ba6','cc-opus-vertex-high-run2':'#e0a37a','cc-opus-vertex-xhigh-run2':'#a8704a','kinex-opus-vertex-high-run2':'#86aae6','kinex-opus-vertex-xhigh-run2':'#5876c0'};
+let data, epoch = 0, current = {}, matrixMetric = 'success';
+let filters = {query:'',family:'',status:'',variant:'kinex',sort:'catalog'};
+let sessionState = {filter:'all',query:'',count:40,view:'timeline'};
+let imageItems = [], imageIndex = 0;
+const sessionCache = new Map(), fileCache = new Map();
+const episodes = (variant, family) => data.episodes.filter(e => (!variant || e.variant===variant) && (!family || e.family===family));
+const reviewFor = (key, variant) => (data.runtime_reviews||[]).find(r => r.task_key===key && r.variant===variant);
+const epFor = (key, variant) => data.episodes.find(e => e.task_key===key && e.variant===variant);
+const plannedTasks = variant => data.tasks.filter(t => !variant || t.planned_variants.includes(variant));
+const variantFor = id => data.variants.find(v => v.id===id);
+const familyName = id => data.families.find(f => f.id===id)?.name || id;
+const variantName = id => {const v=variantFor(id);return v ? `${v.label||v.agent} + ${v.model}` : id;};
+const taskRoute = (key, variant='kinex', section='overview') => `#task/${key}/${variant}${section==='overview' ? '' : '/'+section}`;
+const outcome = e => !e ? 'pending' : e.valid===false ? 'invalid' : typeof e.success!=='boolean' ? 'unreported' : e.success ? 'pass' : 'fail';
+const badge = (e, link) => {if(!e&&link){const p=link.split('/'),t=data.tasks.find(t=>t.key===p.slice(1,3).join('/'));if(t&&!t.planned_variants.includes(p[3]))return 'Not scheduled ';}if(!e&&link){const p=link.split('/');if(reviewFor(p.slice(1,3).join('/'),p[3]))return `Under review `;}const s=outcome(e),tag=link?'a':'span';return `<${tag} class="badge ${s}" ${link ? `href="${esc(link)}"` : ''}>${esc(label)} ${arrow} ` : '';
+const modelLabel = v => `${v.model} / ${v.effort} / ${esc(v.provider)}`;
+const icon = v => `${label} ${value} ${detail?`${detail} `:''}
`;}
+function usageDefinition(){return 'Inclusive input = fresh input + cache read + cache write. Fresh input excludes both cache categories. Cache hit rate = cache read / inclusive input. Output includes reasoning. Counts cover selected evaluated episodes; unavailable values are shown as —, not zero.';}
+function variantTabs(selected,taskKey,section) {
+ return ``;
+}
+
+const rangeNumber = (lo,hi,formatter=compact) => UsageMetrics.bounds(lo,hi,formatter);
+const costValue = s => UsageMetrics.bounds(s.costLow,s.costHigh,UsageMetrics.money);
+const exactMoney = v => v == null ? '—' : '$'+v.toLocaleString('en-US',{minimumFractionDigits:6,maximumFractionDigits:6});
+const costNote = s => !s.n ? 'Not evaluated' : s.costCount!==s.n ? `Pricing available for ${s.costCount} / ${s.n} episodes` : s.conditional ? 'Estimated · 5m cache-write basis' : 'Estimated · recorded session rates';
+function taskResult(ep, link) {
+ const s=stats(ep?[ep]:[]), cost=costValue(s);
+ return `${badge(ep,link)}${cost} `;
+}
+function usageTiles(s,includeCost=true) {
+ const freshNote=s.freshCount===s.n?'Excludes cache read and write':`${s.freshCount} / ${s.n} episodes have a complete split`;
+ const writeNote=s.writeCount!==s.n?`${s.writeCount} / ${s.n} episodes reported`:s.cacheWrite===0?'Reported zero; see counter source':'Recorded cache creation tokens';
+ return `${metric(compact(s.fresh),'Fresh input',freshNote,`title="${number(s.fresh)}"`)}${metric(rangeNumber(s.cacheLow,s.cacheHigh),'Cache read','Reused input tokens',`title="${rangeNumber(s.cacheLow,s.cacheHigh,number)}"`)}${metric(compact(s.cacheWrite),'Cache write',writeNote,`title="${number(s.cacheWrite)}"`)}${metric(compact(s.output),'Output',s.reasoning==null?'Includes reasoning when reported':compact(s.reasoning)+' reasoning')}${metric(rangeNumber(s.cacheRateLow,s.cacheRateHigh,pct),'Cache hit rate','Cache read / inclusive input')}${includeCost?metric(costValue(s),'Total cost',costNote(s)):''}
`;
+}
+function usageEvidence(ep) {
+ const u=ep?.usage;
+ const parser=u?.parser?`Recomputed with ${u.parser} from recorded sessions. `:'';
+ const coverage=u?.parser&&u.audit_complete===false?'Provider request identity is incomplete; recorded token totals are retained. ':'';
+ return parser+coverage+counterEvidence(ep);
+}
+function counterEvidence(ep) {
+ const u=UsageMetrics.usage(ep);
+ if(u.cacheWrite==null)return 'Cache-write coverage is missing; fresh input cannot be separated reliably.';
+ if(u.writeBasis==='provider-reported')return `Cache write: ${number(u.cacheWrite)} reported in raw provider responses. A reported zero does not establish unreported physical cache creation or an API bill.`;
+ if(u.writeBasis==='codex-native-counter')return `Cache write: ${number(u.cacheWrite)} in Codex native counters. Raw provider usage was not retained for this run; a CLI zero cannot distinguish an upstream zero from a missing field.`;
+ return `Cache write: ${number(u.cacheWrite)} in ${u.writeBasis==='claude-native-counter'?'Claude Code native':'Pi session'} counters. Fresh input is inclusive input minus cache read and cache write.`;
+}
+function costBreakdown(s,open=false) {
+ if (!s.n) return '';
+ const names={fresh_input:'Fresh input',cache_read:'Cache reads',cache_write:'Cache writes',output:'Output',unclassified_input:'Unclassified input'};
+ const order=['fresh_input','cache_read','cache_write','output','unclassified_input'];
+ const rows=[...s.buckets].sort((a,b)=>order.indexOf(a.category)-order.indexOf(b.category)||a.tier.localeCompare(b.tier));
+ return `Cost breakdown USD${s.perTask?' / task':''} · estimated + ${s.costCount!==s.n?`
A complete cost is unavailable. The breakdown covers ${s.costCount} of ${s.n} episodes only.
`:''}
${s.perTask?'Each row = average tokens per task × its rate / 1,000,000.':'Each row = tokens × its rate / 1,000,000.'} Fresh input, cache read, cache write and output are disjoint categories; reasoning is already included in output.
Costs are summed from the recorded Pi session estimates. Standalone VLA uses no language-agent API calls.
API-equivalent estimates, not verified account charges. Subscription allocation, discounts, credits, taxes, simulator costs and archived attempts are excluded. Estimates recorded ${esc(UsageMetrics.pricingDate||'—')}.
Not scheduled ${pct(s.rate)} ${s.n?s.passes+' / '+s.n+' passed':'Not evaluated'}
`;
+ else if(matrixMetric==='tokens')value=`
Fresh input / task ${compact(mean.fresh)}
Cache write / task ${compact(mean.cacheWrite)}
Cache read / task ${rangeNumber(mean.cacheLow,mean.cacheHigh)}
Cache hit ${rangeNumber(s.cacheRateLow,s.cacheRateHigh,pct)}
Output / task ${compact(mean.output)} ${costValue(mean)} USD / task · ${costNote(s)}
${costBreakdown(mean)}`;
+ return `${value}${s.n} evaluated · ${plannedTasks(v.id).filter(t=>t.family===f.id).length-s.n} pending ${arrow} `;
+}
+
+function comparisonTable() {
+ const scope='Per-task averages divide totals by the number of valid evaluated tasks in each environment and variant, including passes and failures. Pending and invalid tasks are excluded; missing values remain —.';
+ return `Compare environments Compare the three baselines on the same tasks. Coverage is shown for each environment.
${[['success','Success rate'],['tokens','Tokens / task'],['cost','Cost / task']].map(([k,l])=>`${l} `).join('')}
${matrixMetric==='tokens'?scope+' '+usageDefinition():matrixMetric==='cost'?scope+' Estimated API-equivalent USD per task; expand a breakdown for average token categories and costs.':'Native passes / evaluated tasks. Pending tasks are excluded; compare coverage alongside success rates.'}
${modelGroups().map((g,i)=>`
${esc(g.model)} ${g.key==='baselines'?'Seed 0':esc(g.effort)+' effort'} · ${g.variants.map(v=>esc(v.label||v.agent)).join(' vs ')} ${g.variants.length} variants ⌄ `).join('')}
Codex + RoboBridge · GPT-6 Astra / high · GPU recording pilot ${number(p.completed)} / ${number(p.planned)} independent attempts published: LIBERO, RoboTwin, and two RoboDojo recording conditions. This pilot does not cover the full benchmark.
LIBERO and RoboTwin use independent 720-high spectator cameras. RoboDojo compares native camera recording with online HD recording. Both keep native agent camera resolution, but the RTX control test found that extra HD cameras change subsequent native image pixels. The HD control is shown separately.
Videos play at 4× simulation speed. Session galleries contain images actually submitted to the agent. One model episode per condition cannot establish a success-rate effect.
i Recording comparison · ${hd?'Online HD cameras':'Native camera frames'} ${hd?'The agent receives native-resolution images. GPU controls show that extra HD cameras affect subsequent native RGB pixels through the shared renderer. Spectator images are for the human video only.':'The video uses cached native camera frames. No extra camera or rendering pass is added for recording.'}
Same task, seed 0, model, effort, prompt, budget and owner image; one fresh model attempt per condition. Model sampling also varies, so trajectory differences alone do not establish causality.
${ep.collector_review?`
Original Harbor collection failed because of a nested Docker log-path mismatch. The unchanged session, usage, sealed evidence and native failure were recovered; the original collection exception is retained. ${external(ep.links.collector_review,'Collection recovery receipt')}
`:''}${ep.encoding_review?`
The original 300-second encoding deadline expired after four of six videos. This presentation uses all sealed source frames re-encoded offline with a 600-second deadline; there was no model or simulator retry. ${external(ep.links.encoding_recovery,'Encoding recovery receipt')}
`:''}
View the other recording condition ↗ ${external(data.recording_pilot.details_url||data.recording_pilot.report_url,'Measured image differences and behavior review')}
${esc(c.phase||'Kinex + RoboEnv · GPT-6 Astra / high')} ${c.dispatch_enabled===false?'New dispatch paused. '+esc(c.pause_reason||'Runtime review pending.')+'
':''}${number(n.finished||0)} / ${number(c.planned_episodes)} episodes completed · ${number(n.running||0)} running · ${number(n.queued||0)} queued${n.preflight?' · '+number(n.preflight)+' checking initialization':''}${paired?' · '+number(paired)+' paired replacements pending':''}${codexOnly?' · '+number(codexOnly)+' Codex replacements pending':''}${n.preflight_failed?' · '+number(n.preflight_failed)+' initialization failures awaiting replacement':''}${n.not_run?' · '+number(n.not_run)+' unavailable':''}${n.needs_review?' · '+number(n.needs_review)+' under review':''}. ${c.closed&&c.published_episodes===n.finished?'Evaluations have finished. All available results, videos and evidence are listed below.':'Results, videos and evidence are published after verification.'}
${kinex.length?''+number(kinexDone)+' / '+number(kinex.length)+' authorized Kinex reruns verified and published. Original selected results remain visible until replacement verification finishes.
':''}Updated ${esc(c.updated_at)} · Campaign status and provenance ↗
Claude Code · Opus 5.5 / high ${number(n.finished||0)} / ${number(c.planned_episodes)} episodes completed · ${number(n.running||0)} running · ${number(n.queued||0)} pending${n.needs_review?' · '+number(n.needs_review)+' under review':''}${n.interrupted?' · '+number(n.interrupted)+' interrupted':''}.
${c.quota_waiting?'Waiting for model-service quota recovery · ':''}${number(c.published_episodes)} episode records published · Results and protocol ↗
Reading the benchmark Protocol, metrics & provenance + One selected episode One fresh episode per selected task–baseline pair. Seed 0. Three tasks, three baselines, nine episodes.
Native success Success rate is passes / evaluated tasks, pooled over the selected episodes. Pending tasks do not count as failures. Results follow the original native verifier.
Native control budget RLE-Bench task03 · RoboTwin 2.0 · ALOHA AgileX. Per-task limits: 800, 600 and 1,700 action steps. rosbridge uses 25 Hz control frames; this differs from StarVLA's upstream variable-duration execution.
Policy & agent StarVLA/Qwen3-VL-OFT-Robotwin2, step 40,000. Kinex uses GPT-6 Astra / high. Kinex writes its own control loop around native run_policy; each inference receives three RGB images and language. Encoder changes and progress monitors are not used.
Token accounting ${usageDefinition()} API-equivalent cost uses the recorded Pi session estimates; account charges and GPU costs are not reported.
${variant?'Episode index':'Browse the benchmark'}
Explore tasks ${plannedTasks(variant).length} Export CSV ↓ ${esc(t.title)} ↗ ${familyName(t.family)} · ${t.key}${data.task_notes[t.key]?'◆ Native note ':''} ${badge(ep,taskRoute(t.key,selected))} ${compact(us.fresh)} ${rangeNumber(us.cacheLow,us.cacheHigh)} ${compact(us.cacheWrite)} ${rangeNumber(us.cacheRateLow,us.cacheRateHigh,pct)} ${compact(us.output)} ${costValue(cs)} ${number(actionSteps(ep?.steps,t))}${ep?'of '+number(actionSteps(ep.measured_protocol?.max_steps,ep)):number(actionSteps(plannedProtocol(t,selected).max_control_steps,t))+' campaign plan'} `:data.variants.map(v=>`${taskResult(epFor(t.key,v.id),taskRoute(t.key,v.id))} `).join('')}No tasks match these filters. Clear filters ✦ RLE-Bench · Embodied agent evaluation
Coding agents.Physical tasks. Compare native success, token usage and recorded behavior.
${data.families.length} environment
${data.tasks.length} distinct tasks
${data.variants.length} agent–model variants
Recorded effort · Cache-aware costs · Native verdicts preserved
${comparisonTable()}
Instructions audit Compare current catalog and native instructions side by side for all ${catalogInstructionAudit.tasks.length} tasks.
→ ${s.n?'Selected results':'Planned evaluation'}
${esc(v.label||v.agent)} × ${v.model} ${esc(v.effort)} effort · One seed per task · ${s.n} evaluated · ${plannedTasks(variant).length-s.n} pending
Download results ↓ ${metric(pct(s.rate),'Native success',s.n?`${s.passes} passed / ${s.n} evaluated`:'No recorded episodes')}${metric(costValue(s),'Total cost',costNote(s))}${metric(number(s.responses??s.usageMessages),s.responses==null&&s.usageMessages!=null?'Session usage messages':'Model responses',s.n?(s.responses==null&&s.usageMessages!=null?'Provider response identity unavailable':'Recorded response count'):'Not yet measured')}${metric(elapsed(s.wall==null?null:s.wall/s.n),'Mean wall time',s.n?'Per evaluated episode':'Not yet measured')}
${usageTiles(s,false)}${costBreakdown(s)}${data.families.map(f=>{const fs=stats(episodes(variant,f.id));if(!plannedTasks(variant).some(t=>t.family===f.id))return '';return `
${f.name} ${pct(fs.rate)}
${fs.n?`${fs.passes} / ${fs.n} passed`:'Pending'} · ${plannedTasks(variant).filter(t=>t.family===f.id).length-fs.n} untested `;}).join('')}
${s.n?'Native success is computed from the selected evaluated episodes. Native notes identify simulator source issues. '+usageDefinition():'This combination has no published episodes. The catalog and planned budgets are shown below.'}
${taskBrowser(variant)}${methodology()}`;
+ renderRows();
+}
+function nativeNote(task,ep) {
+ const note=data.task_notes[task.key];if(!note)return '';
+ return `! Native source · ${esc(note.kind)} ${esc(note.text)}
${external(note.source,'Pinned source')}${external(note.evidence,'Diagnostic evidence')}${external(ep?.links?.analysis,'Episode record')}${external(ep?.links?.terminal_frame,'Terminal frame')}
${m.width||'—'} × ${m.height||'—'} · ${m.duration_s==null?'':m.duration_s.toFixed(2)+' s'}
Video unavailable. Open the pinned video directly using the Video link.
${usageTiles(s)}${usageDefinition()}
${esc(usageEvidence(ep))}
${costBreakdown(s,true)}${u.response_count==null&&Number.isFinite(u.known_response_count)?number(u.known_response_count)+'+':number(u.response_count??u.usage_message_count)} ${u.response_count==null&&u.usage_message_count!=null?'session usage messages':'model responses'}${number(ep.call_activity?.model_tool_calls)} tool calls
`;
+}
+// Align words and punctuation while preserving the exact original whitespace.
+function instructionDiff(original, revised) {
+ const split = text => text.match(/\s+|[\p{L}\p{N}_]+|[^\s]/gu) || [];
+ const a=split(original), b=split(revised);
+ const lcs=Array.from({length:a.length+1},()=>new Uint16Array(b.length+1));
+ for(let i=a.length-1;i>=0;i--)for(let j=b.length-1;j>=0;j--)
+ lcs[i][j]=a[i]===b[j]?lcs[i+1][j+1]+1:Math.max(lcs[i+1][j],lcs[i][j+1]);
+ const before=[],after=[];
+ const append=(list,text,changed)=>{const last=list.at(-1);if(last&&last.changed===changed)last.text+=text;else list.push({text,changed});};
+ let i=0,j=0;
+ while(i=lcs[i+1][j]))append(after,b[j++],true);
+ else append(before,a[i++],true);
+ }
+ const html=(parts,kind)=>parts.map(p=>p.changed&&p.text.trim()?`<${kind==='removed'?'del':'mark'} class="instruction-${kind}">${esc(p.text)}`:esc(p.text)).join('');
+ return {original:html(before,'removed'),revised:html(after,'added')};
+}
+function instructionPair(task, ep) {
+ const candidate = ep ? measuredInstructions.episodes[ep.id] : null;
+ const record = candidate && candidate.initial_goal === ep.instruction && candidate.task_key === task.key ? candidate : null;
+ const recordedNative = record?.observed_native || (ep ? ep.native_instruction : task.native_instruction);
+ const measured = record?.text || (ep ? (ep.instruction || (ep.instruction_policy === 'original_native' ? recordedNative : null)) : null);
+ const reference = catalogInstructionAudit.tasks.find(item => item.key === task.key && item.native_id === task.native_id);
+ const nativeReference = !recordedNative && reference?.native ? reference : null;
+ const native = recordedNative || nativeReference?.native;
+ return {record, native, measured, nativeReference};
+}
+
+let instructionAuditFilters = {query:'', family:'', status:''};
+const instructionAuditCache = new Map();
+
+function instructionAuditEntry(task) {
+ if (instructionAuditCache.has(task.key)) return instructionAuditCache.get(task.key);
+ const {native, measured} = task;
+ const status = native === measured ? 'unchanged' : 'changed';
+ const diff = status === 'changed' ? instructionDiff(native, measured) : null;
+ const entry = {task, native, measured, status, diff};
+ instructionAuditCache.set(task.key, entry);
+ return entry;
+}
+
+function instructionAuditCard(entry) {
+ const {task, native, measured, status, diff} = entry;
+ return `
+
+
+
Current instruction ${diff?.revised || esc(measured)}
+
Native instruction ${diff?.original || esc(native)}
+
`;
+}
+
+function renderInstructionAudit() {
+ const f = instructionAuditFilters, q = f.query.trim().toLowerCase();
+ const entries = catalogInstructionAudit.tasks.map(instructionAuditEntry);
+ const changed = entries.filter(e => e.status === 'changed').length;
+ $('#audit-summary').innerHTML = `${entries.length} tasks ${changed} changed ${entries.length - changed} unchanged `;
+ const names = Object.fromEntries(catalogInstructionAudit.families.map(family => [family.id, family.name]));
+ const shown = entries.filter(e => (!f.family || e.task.family === f.family) && (!f.status || e.status === f.status) && (!q || [e.task.key, e.task.title, e.task.native_id, names[e.task.family], e.native, e.measured].some(s => s?.toLowerCase().includes(q))));
+ $('#audit-count').textContent = `${shown.length} / ${entries.length} tasks shown`;
+ $('#audit-groups').innerHTML = shown.length ? catalogInstructionAudit.families.map(family => {
+ const rows = shown.filter(e => e.task.family === family.id);
+ return rows.length ? `
${esc(family.name)} ${rows.length} tasks ${rows.map(instructionAuditCard).join('')}No matching tasks Try another search or reset the filters.
Instruction comparison · All tasks
Instructions audit Current catalog instruction on the left. Native instruction on the right.
`;
+ $('#audit-search').addEventListener('input', event => {f.query = event.target.value; renderInstructionAudit();});
+ for (const key of ['family','status']) $('#audit-' + key).addEventListener('change', event => {f[key] = event.target.value; renderInstructionAudit();});
+ $('#audit-reset').addEventListener('click', () => {instructionAuditFilters = {query:'', family:'', status:''}; instructionAuditPage();});
+ renderInstructionAudit();
+}
+
+function instructionPanel(task,ep) {
+ const {record,native,measured:recorded,nativeReference}=instructionPair(task,ep);
+ const measured=ep?recorded:task.catalog_instruction;
+ const initial=record&&record.initial_goal!==measured?record.initial_goal:null;
+ const changed=Boolean(native&&measured&&native!==measured);
+ const diff=changed?instructionDiff(native,measured):null;
+ const choices=[['measured',ep?'Measured':'Planned',measured],['native','Original native',native],['current','Current catalog',task.catalog_instruction]].filter(([key,,text])=>text&&(key!=='current'||(ep&&text!==measured&&text!==initial)));
+ const currentChanged=native&&task.catalog_instruction&&native!==task.catalog_instruction;
+ const description=!ep?'The current catalog instruction for the planned evaluation.':record?.kind==='scene_bound_goal'?"The measured goal with this episode's objects and targets filled in from the agent's session.":record?.kind==='native_received'?'The native instruction received by the agent during this episode.':'The task instruction supplied for this episode.';
+ return `Task instruction ${description}
${choices.map(([k,label],i)=>`${label} `).join('')}
Native comparison uses a pinned upstream reference${ep?'; native text was not recorded in this episode':''}. ${external(nativeReference.source_url,'Native source')}
`:''}${choices.map(([k,,text],i)=>{
+ const comparison=k==='current'?(currentChanged?instructionDiff(native,text):null):diff;
+ const html=comparison?(k==='native'?comparison.original:comparison.revised):esc(text);
+ const note=comparison?(k==='native'?'Struck-through text was removed or replaced in the '+(ep?'measured':'planned')+' instruction.':'Highlighted text was added or replaced relative to the original native instruction.'):(native?'No changes from the original native instruction.':'Original native text is unavailable for comparison.');
+ return `${comparison?`
${html}
${record.kind==='scene_bound_goal'?'Object names are resolved for display; the measured completion requirements are preserved.':'The initial input contained a generic placeholder; this native instruction was received in the recorded session.'} Original instruction record ↗ · Session evidence ↗
`:''}Under review Native success recorded; runtime finalization failed ${esc(review.reason)}
Original harness verdict: invalid. Recording manifest: incomplete. This attempt is excluded from formal success metrics; its usage is retained separately.
Native terminal steps ${number(actionSteps(review.native_terminal_steps,task,current.variant))} Fresh input ${number(review.usage.fresh_input_tokens)} Cache read ${number(review.usage.cached_input_tokens)} Output ${number(review.usage.output_tokens)} Model responses ${number(review.usage.response_count)} Estimated API-equivalent cost ${exactMoney(review.estimated_api_equivalent_usd)} Both original camera streams decode successfully. Their completion manifest was not sealed, so they are retained as review evidence.
${Object.entries(review.links).map(([key,url])=>external(url,key.replaceAll('_',' '))).join('')}
○ ${initializationBlocked?'Initialization blocked':'Awaiting evaluation'} ${seedLimit?.exhausted?'No native-valid seed at or below '+number(seedLimit.max_seed):initializationBlocked?'Native seed 0 could not initialize':'No recorded episode yet'} ${variantName(current.variant)} / ${esc(variantFor(current.variant).effort)}
${metric(number(actionSteps(plannedProtocol(task,current.variant).max_control_steps,task)),'Campaign planned action steps')}${metric(String(task.planned_seed_by_variant?.[current.variant]??plannedProtocol(task,current.variant).seed),'Seed')}${metric(task.planned_protocol.control_frequency_hz+' Hz','Control frequency')}
${seedLimit?.exhausted?'Native checks exhausted seeds 1–'+number(seedLimit.max_seed)+'. No Codex model attempt was launched. The original Kinex result is retained; this unavailable Codex task is excluded from success rates.':initializationBlocked?'No model was called. Seed 0 is retained by user decision; this is excluded from task success rates.':'This task is included in the planned catalog. Results and usage will appear after evaluation.'}
${instructionPanel(task,null)}
${videoPanel(ep)}
${ep.recording_mode==='native'?'Native camera recording · cached agent-resolution frames · '+(m.speed||1)+'× simulation speed.':ep.provider==='robobridge'&&m.playback_kind==='live_spectator'?'Independent spectator cameras · 720 px high per view · overview + wrist views · '+(m.speed||1)+'× simulation speed. Agent images retain native resolution and orientation.':m.playback_kind==='native_observation_snapshots'?'Native observation snapshots · 10 FPS playback; this is not simulation time.':`${m.source_fps?m.source_fps+' FPS source capture · ':''}${m.speed||1}× simulation speed.`} Session timestamps use wall time and are not synchronized to video frames.
Native verdict ${badge(ep)}
${number(actionSteps(ep.steps,ep))} / ${number(actionSteps(ep.measured_protocol?.max_steps,ep))} action steps
Termination ${esc(ep.verdict?.termination||'—')} Execution ${esc(ep.execution?.status||'—')} Evidence ${ep.valid?'Valid':'Invalid'} Simulation time ${elapsed(ep.simulation_time_s)} Wall time ${elapsed(ep.wall_time_s)} Estimated cost ${costValue(stats([ep]))} Seed ${ep.seed} Agent version ${ep.kinex_version?'Kinex '+esc(ep.kinex_version):ep.codex_version?'Codex '+esc(ep.codex_version):ep.claude_code_version?'Claude Code '+esc(ep.claude_code_version):esc(variantFor(ep.variant).agent)} ${external(ep.links.verdict,'Native verdict')}${external(ep.links.provenance,'Source identity')}
! Native episode completed; later provider error ${esc(ep.post_terminal_review.reason)}
${external(ep.links.completion_review,"Terminal completion review")}
i Native physics clock differs from control-frame time ${esc(ep.native_clock_review.reason)}
${external(ep.links.native_clock_review,"Native clock review")}
i Host collector recovered; original model continued ${esc(ep.collector_review.reason)}
Wall time uses the original session timestamps. Lost host setup timing is left unknown.
Host waiting protection was extended prospectively from 8 to 16 hours for this original execution; the native control budget is unchanged.
${external(ep.links.collector_review,"Collector recovery evidence")}
i Different evaluation seeds Codex uses seed ${number(ep.seed)} after native expert and initialization checks with no model calls during selection. ${ep.provenance.protocol_exception.max_seed!=null?'Seed selection was capped at '+number(ep.provenance.protocol_exception.max_seed)+'. ':''} Kinex retains its original seed ${number(ep.provenance.protocol_exception.preserved_kinex_seed)} result. Codex ran once; this is not a same-seed comparison.
${external(ep.links.seed_selection,'Native seed selection evidence')}
${instructionPanel(task,ep)}
Episode notes Recorded observations and task-specific interpretation.
${reason?`
${esc(reason)}
`:`
${esc(a.outcome||'The native result and original evidence are retained for this episode.')}
`}
Read recorded analysis ${Object.entries(a).filter(([k])=>k!=='preflight').map(([k,v])=>`${esc(k.replaceAll('_',' '))} ${esc(typeof v==='string'?v:JSON.stringify(v))}
${external(ep.links.analysis,'Analysis JSON')}${external(ep.links.terminal_frame,'Terminal evidence')}
${familyName(task.family)} · ${key}
${esc(task.title)} ${esc(task.native_id)}
${index?`
← `:''}${index
→`:''} ${[['overview','Overview',null],['session','Session',ep?.session_counts?.visible_events],['tools','Tool calls',ep?.call_activity?.model_tool_calls],['policy','VLA input/output',ep?.vla_calls],['artifacts','Artifacts',ep?.resources?.length],['evidence','Evidence',null],['attempts','Previous attempts',history.length]].filter(([k])=>k!=='attempts'||history.length).map(([k,l,n])=>!ep&&!['overview','attempts'].includes(k)?`${l} `:`${l}${n!=null?`${number(n)} `:''} `).join('')}${variantFor(variant).model} / ${variantFor(variant).effort} ${section==='overview'?overviewDetail(task,ep):section==='session'?sessionShell(ep):section==='tools'?toolsShell(ep):section==='policy'?policyShell(ep):section==='artifacts'?artifactsPanel(ep):section==='evidence'?evidencePanel(task,ep):historyPanel(history,task)}
`;
+ setupVideo();
+ if(section==='session')loadSession(ep,epoch);
+ if(section==='tools')loadTools(ep,epoch);
+ if(section==='policy')loadPolicy(ep,epoch);
+ if(section==='artifacts'&&ep.resources?.length)loadResource(0,epoch);
+}
+function setupVideo() {
+ const v=$('#episode-video');if(!v)return;
+ v.onerror=()=>{if($('#video-error'))$('#video-error').hidden=false;};
+}
+function sessionShell(ep) {
+ return `Session & observations Loading the original transcript…
${external(ep.links.transcript,'Transcript JSON')}${external(ep.links.native_session,'Native session')}
Load more events
Transcript preview could not load (${esc(error.message)}).Retry ${external(ep.links.transcript,'Open original transcript')}
`;}
+}
+function sessionText(entry) {return [entry.id,entry.role,entry.tool,...(entry.parts||[]).map(p=>p.text||JSON.stringify(p.input||p))].join('\n');}
+function renderSession() {
+ const entries=sessionCache.get(current.ep.id);if(!entries)return;
+ const {filter,query,count,view}=sessionState, q=query.trim().toLowerCase();
+ let matches=entries.map((entry,i)=>({entry,index:i})).filter(({entry:e})=>(filter==='all'||filter==='assistant'&&e.role==='assistant'||filter==='tools'&&e.role==='toolResult'||filter==='errors'&&e.error||filter==='images'&&(e.parts||[]).some(p=>p.type==='image')||filter==='context'&&['user','system','developer'].includes(e.role))&&(!q||sessionText(e).toLowerCase().includes(q)));
+ imageItems=[];
+ const imagePart=(p,index,entry,cls='observation')=>{
+ const url=new URL(p.src,new URL(current.ep.links.transcript,location.href)).href;if(!/^https?:/.test(url))return '';
+ const n=imageItems.length;imageItems.push({url,label:`Event ${index+1} · ${entry.id||entry.role||'Observation'}`});
+ return `Event ${index+1} ${arrow} ${images.slice(0,count).map(({entry,index,part})=>imagePart(part,index,entry,'gallery-image')).join('')}
`:'No observation images match these filters.
';
+ $('#event-count').textContent=`${Math.min(count,images.length)} / ${images.length} images`;$('#more-events').hidden=count>=images.length;
+ } else {
+ $('#session-events').innerHTML=matches.length?`${matches.slice(0,count).map(({entry:e,index})=>{
+ const role=e.role==='toolResult'?'Tool result':e.role==='assistant'?'Assistant':({user:'User',system:'System',developer:'Developer'}[e.role]||e.role||e.type||'Event');
+ const tool=e.tool||(e.parts||[]).find(p=>p.type==='tool')?.name;
+ return `
${index+1}
${(e.parts||[{type:'text',text:typeof e==='string'?e:JSON.stringify(e,null,2)}]).map(p=>{
+ if(p.type==='image'&&p.src)return imagePart(p,index,e);
+ if(p.type==='tool')return `
Tool call · ${esc(p.name)} ${esc((typeof p.input==='string'?p.input:JSON.stringify(p.input)).slice(0,130))}${esc(typeof p.input==='string'?p.input:JSON.stringify(p.input,null,2))} `;
+ const txt=p.text??p.thinking??JSON.stringify(p,null,2);
+ if(txt==='')return '
No text recorded. ';
+ if(p.type==='thinking'||p.type==='reasoning')return `
Recorded reasoning ${esc(txt)} `;
+ if(e.role==='toolResult'||txt.length>1800)return `
${e.role==='toolResult'?'Tool output':'Message'} ${esc(txt.slice(0,160))} ${esc(txt)} `;
+ return `
${esc(txt)}
`;
+ }).join('')}
${esc(e.id||'')}
`;
+ }).join('')}
No events match these filters.
';
+ $('#event-count').textContent=`${Math.min(count,matches.length)} / ${matches.length} events`;$('#more-events').hidden=count>=matches.length;
+ }
+ $('#more-events').textContent=view==='gallery'?'Load more observations':'Load next 40 events';
+}
+function artifactsPanel(ep) {
+ const resources=ep.resources||[];
+ return `Agent artifacts Final files created during this episode. Their edit history remains in the session.
${external(ep.links.workspace,'Workspace archive')}${external(ep.links.workspace_changes,'Workspace manifest')}
No standalone tool or memo files were saved in this episode. The original session and workspace evidence remain available.
'}${evidenceCard('Execution evidence','Original verdict, protocol and runtime identity.',[['verdict','Native verdict'],['protocol','Protocol'],['provenance','Source identity']],ep)}${evidenceCard('Session & interactions','Original tool calls, observations and edited workspace.',[['native_session','Native session'],['trace','Trace'],['workspace_changes','Workspace changes']],ep)}
`;
+}
+async function fetchText(url) {
+ if(fileCache.has(url))return fileCache.get(url);
+ const r=await fetch(url);if(!r.ok)throw Error('HTTP '+r.status);
+ if(Number(r.headers.get('content-length'))>3e6)throw Error('File exceeds the 3 MB preview limit; use Open file');
+ const text=await r.text();if(text.length>3e6)throw Error('File exceeds the preview limit; use Open file');
+ fileCache.set(url,text);if(fileCache.size>20)fileCache.delete(fileCache.keys().next().value);return text;
+}
+async function loadResource(index,token) {
+ const r=current.ep?.resources?.[index];if(!r)return;
+ current.resource=index;$('#resource-name').textContent=r.name;$('#resource-open').href=r.file;$('#resource-kind').textContent=r.kind||'Final workspace snapshot';$('#resource-preview').textContent='Loading file…';
+ $$('[data-resource]').forEach(b=>{b.classList.toggle('active',+b.dataset.resource===index);b.setAttribute('aria-pressed',+b.dataset.resource===index);});
+ try{const text=await fetchText(r.file);if(token===epoch&¤t.resource===index){$('#resource-preview').textContent=text;current.resourceText=text;}}
+ catch(e){if(token===epoch&¤t.resource===index){$('#resource-preview').textContent='Preview unavailable: '+e.message;current.resourceText=null;}}
+}
+const evidenceGroups=[
+ ['Native evaluation','Owner verdicts, measured task and control protocol.',[['verdict','Native verdict'],['protocol','Measured protocol'],['native_goal','Task instructions'],['owner_journal','Owner action journal']]],
+ ['Session & workspace','The original agent trajectory and final files.',[['native_session','Native session'],['transcript','Readable transcript'],['trace','Agent trace'],['workspace','Workspace archive'],['workspace_changes','Workspace manifest']]],
+ ['Recording & review','Published media and checks against the recorded evidence.',[['video','Video'],['poster','Poster'],['terminal_frame','Terminal frame'],['recording_manifest','Recording manifest'],['media_check','Media validation'],['analysis','Episode analysis']]],
+ ['Usage & provenance','Provider counters and the actual code used by the episode.',[['usage','Token usage'],['provider_usage','Provider usage ledger'],['provenance','Source identities'],['tool_errors','Tool errors']]]
+];
+function evidenceCard(title,description,items,ep) {
+ return `${title} ${description}
${items.filter(([k])=>ep.links[k]).flatMap(([k,l])=>(Array.isArray(ep.links[k])?ep.links[k]:[ep.links[k]]).map((url,i)=>external(url,l+(Array.isArray(ep.links[k])?' '+(i+1):'')))).join('')}
Evidence & provenance Original files retained with their published checksums. Native verdicts and measured source identities remain unchanged.
${evidenceGroups.map(([title,desc,items])=>evidenceCard(title,desc,items,ep)).join('')}${extras.length?evidenceCard('Additional records','Episode-specific checks and retained references.',extras.map(k=>[k,k.replaceAll('_',' ')]),ep):''}
Recorded identity Source and protocol belonging to this episode.
Episode ${esc(ep.source_episode_id)}Model ${esc(ep.model)} / ${ep.effort} Space ${external('https://huggingface.co/spaces/'+source.space,source.space)} Original evidence revision ${source.evidence_revision}Kinex revision ${esc(ep.kinex_revision)}${esc(k)} ${esc(v.revision||'Unrecorded revision')}${v.dirty?' Local changes recorded ':''}Recorded action-step budget ${number(actionSteps(ep.measured_protocol?.max_steps,ep))} steps Campaign planned action-step budget ${number(actionSteps(plannedProtocol(task,current.variant).max_control_steps,task))} steps Current benchmark default ${number(currentBudget(task))} action steps Inspect the measured protocol JSON ${esc(JSON.stringify(ep.measured_protocol,null,2))} Preview an evidence file Inspect the recorded JSON without leaving this page.
Choose a file… ${[['verdict','Native verdict'],['protocol','Measured protocol'],['provenance','Source identities'],['usage','Token usage'],['analysis','Episode analysis'],['media_check','Media validation'],['recording_manifest','Recording manifest']].filter(([k])=>ep.links[k]).map(([k,l])=>`${l} `).join('')}Previous attempts Archived attempts are preserved separately and excluded from the current success rate, usage and costs.
Full archive ↗ ${badge(h)}${h.valid===false?'Interrupted / invalid':typeof h.success==='boolean'?'Archived result':'Verdict not recorded'}
${esc((h.status||'Archived attempt').replaceAll('_',' '))} ${esc(h.id||h.job||h.dataset_revision||'Historical record')}
${h.steps!=null?number(actionSteps(h.steps,task))+' action steps · ':''}${h.usage?'Fresh input '+compact(UsageMetrics.usage(h).fresh)+' · cache read '+compact(h.usage.cached_input_tokens)+' · cache write '+compact(UsageMetrics.usage(h).cacheWrite)+' · output '+compact(UsageMetrics.usage(h).output)+' · ':''}${h.dataset_revision?'Revision '+h.dataset_revision.slice(0,8):''} ${h.analysis?.execution?`
${esc(h.analysis.execution)}
`:''}${h.instruction?`
Measured instruction ${esc(h.instruction)}
`:''}
${Object.entries(h.links||{}).filter(([k])=>['video','verdict','provenance','transcript','terminal_frame','native_session'].includes(k)).map(([k,u])=>external(u,k.replaceAll('_',' '))).join('')}
No earlier attempts are listed for this task and agent combination.
'}VLA input/output ${number(ep.vla_calls)} recorded inferences · model inputs, action outputs and agent tool results.
${external(ep.links.vla_io,'All calls JSON')}${external(ep.links.policy_trace,'Original trace')}
Loading recorded calls…
${esc(title)} ${esc(JSON.stringify(value,null,2))} No VLA inference was made in this episode.
';return;}
+ const images=c.images.map(im=>`${esc(im.camera)} · 224 × 224Recorded RGB · ${im.recorded_size.join(' × ')} ↗ Inference ${record.calls.map((x,i)=>`${i+1} / ${record.calls.length} · ${x.call_id.slice(0,12)} `).join('')} ${esc(c.call_id)}${c.service_response.inference_s.toFixed(3)} s · 16 × 14 actions
Task instruction ${esc(c.request.task)}
${images}
Model images use the recorded RGB inputs with the executed resize to 224 × 224. No joint state or agent conversation is passed to the VLA.
${jsonBlock('Model-service request · retained image paths',c.request)}${jsonBlock('Backbone message · reconstructed from executed code',c.backbone_messages)}Model-service output The complete response consumed by Kinex run_policy. Joint values are absolute radians; grippers use −1 open, +1 closed.
Action ${cols.map(x=>`${esc(x.replace('left_','L ').replace('right_','R '))} `).join('')}${c.service_response.actions.map((row,i)=>`${i+1} ${row.map(x=>`${x.toFixed(5)} `).join('')}
Kinex tool call & result This inference falls within the recorded exec call below. One exec can contain several inferences. The language agent receives the tool result, not the model's raw action array.
${jsonBlock('Agent tool call',caller.tool_call,true)}${jsonBlock('Tool result received by the language agent',{...caller.tool_result,parts:textParts(caller.tool_result.parts)},true)}${c.executed_tool_source?jsonBlock('Agent-authored code at this call',c.executed_tool_source):''}`:'Standalone execution; no language-agent tool call.
'}Recording coverage & model contract Temporary image filenames, normalized action tensors and processor tensors were not retained. Recorded images, task text and both complete action arrays are available for every inference.
${esc(JSON.stringify(record.contract,null,2))} ${external(record.contract.model_metadata,'Model configuration')}${external(record.contract.executed_sources,'Executed source checksums')}${external('policy-contract/model_node.py','Model service')}${external('policy-contract/starvla.py','Policy adapter')}${external('policy-contract/kinex_policy.py','Kinex run_policy')}
Tool calls Original tool inputs and outputs from the agent trace.
${external(ep.links.tool_calls,'Tool calls JSON')}
Loading tool calls…
${i+1} · ${esc(c.name)}${c.is_error?' · Error':''} ${esc(c.call_id)}
Input ${esc(JSON.stringify(c.input,null,2))} Output ${esc(typeof c.output==='string'?c.output:JSON.stringify(c.output,null,2))} No language-agent tool calls in this episode.
';}catch(e){if(token===epoch)$('#tools-body').textContent='Preview unavailable: '+e.message;}
+}
+
+async function boot(){try{
+const source=await fetch('data-source.json');if(!source.ok)throw Error('Result source unavailable');
+resultFiles=(await source.json()).files;
+document.querySelectorAll('[data-result-file]').forEach(link=>{link.href=resultURL(link.dataset.resultFile);});
+const r=await fetch(resultURL('data.json'));if(!r.ok)throw Error('HTTP '+r.status);data=await r.json();
+const ir=await fetch('measured-instructions.json');if(!ir.ok)throw Error('Instruction evidence unavailable');measuredInstructions=await ir.json();
+const nr=await fetch(resultURL('instruction-audit.json'));if(!nr.ok)throw Error('Instruction audit unavailable');catalogInstructionAudit=await nr.json();
+try{const c=await fetch(resultURL('cost-data.json'));if(c.ok)UsageMetrics.init(await c.json());}catch{UsageMetrics.init({episodes:{},sources:[]});}
+for(const task of data.tasks){
+ if(task.family==='task02'){
+ const {suite_name,task_id}=task.native_identity;
+ task.title=`LIBERO-${suite_name.replace(/^libero_/, '')}-${String(task_id+1).padStart(2,'0')}`;
+ }
+}
+window.benchmarkData=data;$('#updated').textContent='Results updated '+data.updated_at.slice(0,10);window.addEventListener('hashchange',route);route();}catch(e){$('#main').innerHTML=``;}}
+boot();
diff --git a/assets/anthropic-logo.svg b/assets/anthropic-logo.svg
new file mode 100644
index 0000000000000000000000000000000000000000..df672869bf991bff410bfc463dc5d71d10b96bc8
--- /dev/null
+++ b/assets/anthropic-logo.svg
@@ -0,0 +1 @@
+
+
diff --git a/assets/kinex-logo.svg b/assets/kinex-logo.svg
new file mode 100644
index 0000000000000000000000000000000000000000..35baa8bbccf1d959948b4e01b019124f14185a3d
--- /dev/null
+++ b/assets/kinex-logo.svg
@@ -0,0 +1,4 @@
+
+
diff --git a/assets/openai-logo.svg b/assets/openai-logo.svg
new file mode 100644
index 0000000000000000000000000000000000000000..6982cfcbcb646ef113471b2c0a325ff4aa70d0b3
--- /dev/null
+++ b/assets/openai-logo.svg
@@ -0,0 +1,4 @@
+
+
diff --git a/assets/vla-logo.svg b/assets/vla-logo.svg
new file mode 100644
index 0000000000000000000000000000000000000000..a8150682de5f4540183bbae74757d8b3b85f61e6
--- /dev/null
+++ b/assets/vla-logo.svg
@@ -0,0 +1 @@
+/base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 11, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 10, in main\\nTypeError: tuple indices must be integers or slices, not str\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "888980b4",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:26:25.414Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
+ "offset": 1,
+ "limit": 180
+ },
+ "call_id": "call_764ced789f0d4188899433ec60bc7b1a|fc_0df8288370165955016ae26880fc78819d82a1b2e75454d578"
+ }
+ ]
+ },
+ {
+ "id": "85aa9ef6",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:26:25.418Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "e1574d32",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:26:29.317Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import asyncio\nfrom kinex import runtime, communication, helpers, finish\nasync def main():\n async with communication() as io:\n image,depth=await helpers.camera_frame(io,'head_camera')\n out={}\n for d in ['left_arm','right_arm','left_gripper','right_gripper']:\n async with io.subscribe(d+'.joint_state') as s: out[d]=await s.next()\n out['schemas']={x:runtime.describe(x) for x in ['left_arm.joint_target','left_gripper.target','world.wait']}\n p=helpers.save_image(image)\n finish(out,file=p)\nasyncio.run(main())",
+ "description": "observe scene and schemas"
+ },
+ "call_id": "call_1f72f2a5fef14e6c9770552b06e256ef|fc_0df8288370165955016ae2688345b4819daff7e571c13a4374"
+ }
+ ]
+ },
+ {
+ "id": "01d7a694",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:26:31.346Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793222790.779743893] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"left_arm\": {\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"fl_joint1\",\"fl_joint2\",\"fl_joint3\",\"fl_joint4\",\"fl_joint5\",\"fl_joint6\"],\"position\":[-3.016615224282759e-8,-5.666987590302597e-7,-0.000004835828804061748,7.701128623693876e-8,4.63164752773082e-7,-8.158995683515968e-7],\"velocity\":[0.00000265039443547721,-0.000010050378477899358,0.000024748725991230458,-0.000004255349267623387,-0.00001595680987520609,0.00007239235128508881],\"effort\":[]},\n \"right_arm\": {\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"fr_joint1\",\"fr_joint2\",\"fr_joint3\",\"fr_joint4\",\"fr_joint5\",\"fr_joint6\"],\"position\":[-3.258066882949606e-8,-5.65274206110189e-7,-0.000004838918357563671,7.693390813301448e-8,4.6469963876916154e-7,-8.163781899384048e-7],\"velocity\":[0.0000026605034690874163,-0.00001006854472507257,0.000024771599782980047,-0.000004258563421899453,-0.00001595234061824158,0.00007239227852551267],\"effort\":[]},\n \"left_gripper\": {\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"left_gripper\"],\"position\":[0.986124409870668],\"velocity\":[0.018415418030186134],\"effort\":[]},\n \"right_gripper\": {\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"right_gripper\"],\"position\":[0.9861242744055662],\"velocity\":[0.0184164128520272],\"effort\":[]},\n \"schemas\": {\"left_arm.joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"joint_names\":\"sequence\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"left_gripper.target\":{\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\"world.wait\":{\"description\":\"Advance or await duration_s of world time (finite and nonnegative). Zero is an observation barrier. Waits are sequential; one requested while another is pending is rejected. A terminal episode rejects further progression without exposing benchmark results.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/world/wait\",\"type\":\"kinex_interfaces/srv/Wait\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"duration_s\":\"double\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"time_s\":\"double\",\"waited_s\":\"double\"},\"definitions\":{}}},\n \"file\": \"/tmp/kinex-observation-ftia7zbo.png\"\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/01d7a694-1.png"
+ }
+ ]
+ },
+ {
+ "id": "9082ebc5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:26:42.398Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Segmenting the red prism**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae26889f68c819d9b664c99a6227d39\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Segmenting the red prism**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4miNns4hStLldJl_kwfZZmUiENploYfPdk3X8QcfUyapIG4gMYuxzDGP-2-HqyuMco7BI5AyaE_Nn9XrjuhsYtlE0NQboClQnrsT0MpRUy5l8K2xLQE6OSH1xd_r4Ng7JHbB-whHrnijHIGJdlk7oudZFW0UVDJ74pVGBUcTISAWFKyUT32f2FjsDRf3BAdu1tREZfg4ndX1uVvGpYX3O5xfyPhx59kGU7fMGYvwhu6_GRKDzrPu92fEKYC1GcpvxbzcNH27OKt_xOu0upw7M6UlQMyARZoJWoVya4mPNSk1LCq3LDfxt43tVJyYqqrS4xoUfBxKgnxv6uPaP9pTGvYPr9st4O-YKlZxYc2d-tMFoGCuBGfx7kQF1ePWaGILz7l_QvhECANoTgJB7Jgm_u7AVsuidMiK0ttqYuPoRal4kluAoTPtlSqFVj8K5qTFbBepzeFZ6_wHh-JjoKbA7_KFOTGSnbfDJF1JgphUPMAvbVsZue7AASQnqHm0QYcmCQeAlQgtip3M-lG35Gsq_knggIO_GUX9fSgogNSWU23MpPdfWBKgI-TGY88oAFFX2m4E1WTrxZQRb6OcQWqbVQiAa4RSmyPwalF_HGIMiMYuu7dWbMTQVZcM8l0sPdNJc_3i9rTMQIUFtUkz6otNBVGkiAdGZU7IAI9OwnN25MR-yOSMHuCWeGD2a97W9Gm4HeXjZUiSFlE_mIbNcS6ls7SqloCkXn_Zkl31fyl_j9X8KrNvHes5JbHgsVI0Dt7lz_QYvKn0b0bfmjCzErsoxMPZy8PRVAfuQMoX1LDaTd4EobXxRrzql-cXYBG43LuDFnbVDaEbg3idxS9VLUMyR95G1K4zAbAhmMeWoRuc7YTMxGpK5LgINWiknzrGEinWEpvQhK2AYcwHskKeIXZsuMQ6yBcEddNuTACfOdER-ZtY3QN0n9tw4y3vnaZ8QYZzBtwKJfZGqrtB-OuQUaAMbyuW1V8PPmnSJC3xeLLU9f40jpoa6dRTW0soGGHoIZFWAmRZ_EiqFLl7y-WwScND89-qiIiJo6kCJDucA5duDVljJFzwArQK0kWf6Z24_OdeblUxaZimCDnCSPikJplUdB2wTB72lGfGYSDRMLAbzQlgd4gAtse3eIAGpVHOdyV2_J0DfO93jOFCHAtDOyQPmqmptQ0Uh3UatezUNt8dL2p6CvFs78UoUxCeYv21skPHVfTkeRiXeuuHFPniyVu6LxaGZQL5UgCSa16VZqRhktdD4EdcQd30naBUtQWt43_B_jvgWi7OkZWVwMFUMmaoe95TJBDFVopZzoPfqBevvu_02BVzamMyOyw2twCu37vFiRabzSM5J8u2EM_bgLq2R2E5l2E72ntJP2quy_GFEv7B_TKEwPyACXv6FCbaUtklnIL-YNn2C_x8mJNglqbbUb16kybxen395dxsCWXAcEoHwmTkdaVcoPG6ZCCFxfb3m2UivLUHcLSFkVlWrtmLRSKt7el2t0BFwcMQ3mFFpMNsR1DHV4DWHF0YRdg43aAruoY2OanTxR_vJpPnc4Wdv8Swou2RB9ptdx8m7xdDcMlHVLkQFt7aIprIC7jUw2wd3l7P4tYcBTwQBpXr7gwGtKzO85Uhp08_fj9_3TOp9sbwOOyre4BGcC-se1NNipdhnXVToh6D6q3k5Vn096z-5fhcngGls5j8Vrn9cilFiFJ-0WxW3OP_8wFM7HVnuNAsZXCdHzbWHc3EeHGa2TD7s0z69YBzNS4kC840V3-nw2oJ084MABfNSnLDXVIFHDrUIspguEndsTc8CMCQ7fM0ah4P5W-pjzPFDnevSJQ5cRNmVSR3K-Mztrb3CG77PLAQKPGr\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import asyncio,numpy as np\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,de=await helpers.camera_frame(io,'head_camera'); a=helpers.image_array(im); z=helpers.image_array(de)*.001\n masks={'red':(a[:,:,0]>110)&(a[:,:,0]>a[:,:,1]*1.8)&(a[:,:,1]<100),'blue':(a[:,:,2]>100)&(a[:,:,2]>a[:,:,0]*1.8)&(a[:,:,0]<100)}\n out={}\n for k,m in masks.items():\n v,u=np.where(m&(z>0)); zz=z[v,u]; p=np.stack([(u-159.5)*zz/358.6421814,(v-119.5)*zz/358.6421814,zz],axis=1)\n tf=await helpers.relative_pose(io,{'frame':im.header.frame_id},{'frame':'world:base'})\n out['tf']=tf\n from scipy.spatial.transform import Rotation as R\n # relative_pose returns pose\n out[k]={'pixels':[int(u.min()),int(v.min()),int(u.max()),int(v.max())],'camera_range':[p.min(0).tolist(),p.max(0).tolist()],'median':np.median(p,axis=0).tolist()}\n out['tcp']={d:await helpers.relative_pose(io,{'frame':d+'_gripper:tcp'},{'frame':'world:base'}) for d in ['left','right']}\n finish(out)\nasyncio.run(main())",
+ "description": "locate block and pad surfaces"
+ },
+ "call_id": "call_4a4596413bcd40e7a90d0776e1764dc0|fc_0df8288370165955016ae2688b8a3c819da1f7a4725b5bf751"
+ }
+ ]
+ },
+ {
+ "id": "9a8e8452",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:26:44.722Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793222803.632560113] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"tf\": {\"pose\":[-0.03200000152,-0.449999988079,1.350000023842,0.9486832972651139,0,0,-0.3162277683730379],\"timestamp\":0},\n \"red\": {\"pixels\":[77,0,115,67],\"camera_range\":[[-0.16374677337382487,-0.2402380547197954,0.707],[-0.10597470674429707,-0.125013181174009,0.862]],\"median\":[-0.1355138980314043,-0.1914066542090244,0.776]},\n \"blue\": {\"pixels\":[199,55,244,86],\"camera_range\":[[0.09508362866543728,-0.15700467742024501,0.8140000000000001],[0.19417403643976383,-0.07631422464909199,0.873]],\"median\":[0.1445019651556246,-0.11359511544617211,0.84]},\n \"tcp\": {\"left\":{\"pose\":[-0.30032357671522697,-0.193827798419468,0.9419981020126762,-0.000006960933310190554,-0.00000395167326060435,0.7141423608015681,0.7000004917460364],\"timestamp\":0},\"right\":{\"pose\":[0.30523323124039986,-0.1928057309036048,0.9409978556569187,-0.000007012336903923293,-0.000003885552193758481,0.710633293626997,0.7035625927553112],\"timestamp\":0}}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "0a37bbcd",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:26:59.090Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking possible tower view**",
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+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_camera/profile.yaml",
+ "offset": null,
+ "limit": null
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+ },
+ {
+ "type": "tool",
+ "name": "read",
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+ "path": ".kinex/devices/left_gripper/gripper.urdf",
+ "offset": null,
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+ "call_id": "call_c0a71f1a695641ecbf5210f719cfc840|fc_0df8288370165955016ae268a2fdc0819db5d37915c56eb0a4"
+ },
+ {
+ "type": "tool",
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+ "path": ".kinex/devices/left_arm/arm.urdf",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_4b667940abd94b938fdbc184dc5c8612|fc_0df8288370165955016ae268a2fdc0819d981b1dd9e7ba615d"
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+ },
+ {
+ "id": "02612523",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:26:59.094Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: left_camera\nruntime:\n domain_id: 83\n nodes: []\n ready_timeout_s: 30\noperations:\n image:\n description: RGB image measurements with encoding, dimensions, row stride and\n acquisition timestamp in the Image header. The frame_id identifies the calibrated\n optical frame; use its stamp for tf2 lookup. A new subscriber receives the current\n frame at once, also while the world is paused, then one per camera sample; reading\n never advances world time.\n transport: topic\n direction: output\n endpoint: /left_camera/image\n type: sensor_msgs/msg/Image\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n depth:\n description: '16UC1 depth registered to image in millimetres along the optical\n axis; 0 marks missing or out-of-range samples. Rendered with its image: same\n stamp and frame_id, so pair the two by stamp.'\n transport: topic\n direction: output\n endpoint: /left_camera/depth\n type: sensor_msgs/msg/Image\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n camera_info:\n description: Projection and distortion calibration for the image stream, including\n K, D, image size and optical frame. Use the declared distortion model and raw/rectified\n image space when projecting pixels; intrinsics are not TF transforms.\n transport: topic\n direction: output\n endpoint: /left_camera/camera_info\n type: sensor_msgs/msg/CameraInfo\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: rgbd\ndescription: RGB-D camera (D435 model) on the left wrist. Native ray-traced RGB with\n pixel-center depth from a raster twin; calibration and the optical-frame mount on\n the left_arm flange are in the profile.\nsource: introspected\ncalibrated_at: null\nmethod: introspection\ncolor:\n width: 320\n height: 240\n fps: null\n projection:\n model: pinhole\n fx: 358.642181396484\n fy: 358.642181396484\n cx: 159.5\n cy: 119.5\n skew: 0\n distortion:\n model: none\n fov:\n horizontal_deg: 48.085891406656\n vertical_deg: 37.000001358777\ndepth:\n width: 320\n height: 240\n fps: null\n quantity: z\n scale_m_per_unit: 0.001\n invalid_value: 0\n valid_range_m:\n min: 0.1\n max: 65.535\n reliable_range_m:\n min: 0.1\n max: 65.535\n registration: color\nframes:\n base:\n translation_m:\n - 0.07000001149\n - 0.031999994336\n - 0.065000047158\n rotation_xyzw:\n - -0.589367966393\n - 0.589367919412\n - -0.390698641271\n - 0.39069867358\n parent: left_arm:flange\n"
+ }
+ ]
+ },
+ {
+ "id": "68017fa6",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:26:59.094Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "9ee747d4",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:26:59.094Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "76aebf4d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:27:07.599Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Finding red surface coordinates**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae268a62cb4819d86fdf845c114c0c7\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Finding red surface coordinates**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4miol7YCcZWjPkg9abxIqR_fyDvWlc7BMVZCDD6NGKylIPKikIOb5WyGfpipIpFFX_l8G9uH7LICIlVkYjcIpGphz21ariTkPGwbcRBEi-CwrFfQ4c89qsxHTg3m9PkMyftjCRvPcQIzkV17ChdW65CaF14Jb8EXUOmt7p17ubauQSVsLK73i6uxkxaw8t9C-hkNS79_4ltu0jXwn-VXXZGwdgFDjgK9261p3r2sqjXnmvV_MzLSEMtjWF6yo73ntiuPZTO6x4cFamHGBoRTP_SjaiUQMAd2TMZygu75pdtscTp4zk9H006kaf1jl1eDCwvxj569Gmbsent8x4_gSzSK7PGNh8Jn7q-H-qtauPVzpPNzFpBzxkMt-UH96r31T6A2Jws_ArFBl8xfrlCizes0uoWzZPLoqzOazjKSgZrWjdvG5htqxGPgqQUmAfz2okXqgdz8kBHBKMiZu_TIYr9XbJh9BQzZQLx-aSH-Jw7kI6xjexPnHZ8akmUfGFQYjpV1myykBuFBYVTpTJrNgmqGBDSURBEJAMUQvaAWcTFAt3Arbm7RVqtmT7G4mmipuaTUTF8MMz3aIjWsjVlRUS8m8yOaxzvDNoHJLU7neWaIOaWWRZfsj3AXfoHQP7SiEa8e3USlUOrWwztlbUeTXFIaFncCcwsuzxtGzWTPHu0w7lmePaX__AUtidaAuIR7cbMgDsEozVJS98FrRyV-rdccMUf3u22qxW2L5ijb6_TjDwEJnKfL3lU85nA0u_5vi3DL89cdBEldr-TxvEFWI87K3gvWrR65Mkxp-_Z6sOpprJJvDjL_-5JP564BLoBWkpvG91UXaz4aSl5f-rXu4Arv_HdZiJ-DoASmKmxiUjasFjqluEIms-5beZKPgYI1b4sYcfgLWNN0AYkVej2Xc9GM22qdQbtf24K2MosXmkHDOM6saiw9lGeCvTYPrBp0OOdyIT-KFm_uKQZkNbraHjflj5Ni1_4uCdrVZACzGrxdyOp_fQuseUtW2ezYa7ff4Nf8PMzj3KBNNcdyPfy-xuScXBnE84SEoW2diA5H_cJZMkczBYvkUQCADXMbMuCsYRap66_R9AyunEQNbN0SI4QPPn2GNFSFvUnGyiRfjUxjIxaiFyIQTW5SftDvxyjZMEbewEfRgfyOAGPw4JhwBTqMs2oFTpc9_6qXBgPUt2MM-PEm2SByENAhzCgy3RVc-bJaAEFC9oSCWB68lrOt6OT85a5pH5HBkfPLEj0WJypbXBfltquSANpBzkutLCctrXBqOp0tnQKxhjWZCVpBXJd8MySm0AR8-MfImintuDGukLYPCvNV2vo8yu6V0VdC4W2IF2GuIOoZr22wILYdRt8y8uUNOqu0fDoPSMu5BcoiKR7kU08xCwkJxdIS2TF5GQ-dfgwfqosVubBv09V8yEQ9iGut3Kapsh984JfsCSSh-lV2MqdxnOQSlS860M1JFtwam0EMlB8Tk37G0KnZICaiejR_LrZ7v4AlTH_8sICvceIuwjNomVt2oE3m9tnYfu7bi_NfTQR8atHME9jo1BHSV747JYa-q4947HFRbVTpxui50RBRBftltbiYS_LVGXkMqSlmBK9Jjq1zsajpHgzx-hWpVQPVuOkfqPyjqZQoOBQtdgmCYK1krHJFCsuct-6qg1J_BuiDQisW0od6DAQyt3zVKhgUYmK8jiDF7gw-C4EaWRdZGb8-s6t8ym2qQB1sFnTmBoXnV3AP72TIMQiFbSGu2UY_eANXlkpMo597dsa_ANeqyKUDIuMIY_Ks6beU\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,de=await helpers.camera_frame(io,'head_camera'); a=helpers.image_array(im).astype(float); z=helpers.image_array(de)*.001\n tf=(await helpers.relative_pose(io,{'frame':im.header.frame_id},{'frame':'world:base'}))['pose']; out={}\n for k,m in {'red':(a[:,:,0]>110)&(a[:,:,0]>a[:,:,1]*1.8)&(a[:,:,1]<100),'blue':(a[:,:,2]>100)&(a[:,:,2]>a[:,:,0]*1.8)&(a[:,:,0]<100)}.items():\n v,u=np.where(m&(z>0)); zz=z[v,u]; p=np.stack([(u-159.5)*zz/358.6421814,(v-119.5)*zz/358.6421814,zz],axis=1); w=R.from_quat(tf[3:]).apply(p)+tf[:3]\n out[k]={'min':w.min(0),'max':w.max(0),'median':np.median(w,axis=0),'bottom':np.median(w[w[:,2].6: raise ValueError('IK branch jump')\n q=nq; t=elapsed+duration*f; ns=round(t*1e9)\n points.append({'positions':q.tolist(),'time_from_start':{'sec':ns//1000000000,'nanosec':ns%1000000000}})\n elapsed+=duration; wp=targetp; wr=targetr\n plans[side]=(model,q,elapsed,points)\n for side,(model,q,t,points) in plans.items():\n await io.publish(side+'_arm.joint_target',{'joint_names':model.names,'points':points})\n for side,value in a.get('grips',{}).items():\n await io.publish(side+'_gripper.target',{'data':float(value)})\n wait=max([p[2] for p in plans.values()]+[float(a.get('wait',0))])\n if wait: result['wait']=await io.request('world.wait',duration_s=wait+float(a.get('settle',.16)))\n for side in ['left','right']:\n s=await state(io,side+'_arm'); g=await state(io,side+'_gripper')\n result[side]={'q':list(s.position),'grip':list(g.position),'tcp':(await helpers.relative_pose(io,{'frame':side+'_gripper:tcp'},{'frame':'world:base'}))['pose']}\n if side in plans: result[side]['joint_error']=float(np.max(np.abs(np.array(s.position)-plans[side][1])))\n paths=[]\n if a.get('observe',True):\n image,depth=await helpers.camera_frame(io,'head_camera'); paths=[helpers.save_image(image)]\n finish(result,file=paths)\n\nasyncio.run(main())\n"
+ },
+ "call_id": "call_83515ff0f7274002a9175087a6022bdc|fc_0df8288370165955016ae268bf32bc819daeef75bb1c85047f"
+ }
+ ]
+ },
+ {
+ "id": "ed34bdb2",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:27:44.864Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to /workspace/.kinex/tools/cartesian_move.py"
+ }
+ ]
+ },
+ {
+ "id": "bc1338e6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:27:47.996Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "moves": {
+ "left": [
+ [
+ -0.167,
+ 0.045,
+ 0.835,
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ]
+ ]
+ },
+ "seconds": 2,
+ "grips": {
+ "left": 1
+ }
+ },
+ "description": "approach block with left arm"
+ },
+ "call_id": "call_0bd080577be548f4b8adb745b8436cb7|fc_0df8288370165955016ae268d2b184819da58990c63104de48"
+ }
+ ]
+ },
+ {
+ "id": "c76dfcac",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:27:50.898Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793222870.183791116] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"Traceback (most recent call last):\\n File \\\"\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 40, in script\\n runpy.run_path(file, run_name=\\\"__main__\\\")\\n File \\\"\\\", line 287, in run_path\\n File \\\"\\\", line 98, in _run_module_code\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/workspace/.kinex/tools/cartesian_move.py\\\", line 51, in \\n asyncio.run(main())\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/tools/cartesian_move.py\\\", line 22, in main\\n local=model.fk(q); wr=baseR*Rotation.from_quat(local[3:]); wp=baseR.apply(local[:3])+basep+wr.apply([.12,0,0])\\n ^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/joints.py\\\", line 41, in fk\\n q = joint_target(positions, self.joints, check_limits=False)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/urdf.py\\\", line 114, in joint_target\\n vector(value, len(joints), \\\"joint target\\\")\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/geometry.py\\\", line 19, in vector\\n raise ValueError(f\\\"{name} needs {size} numbers\\\")\\nValueError: joint target needs 6 numbers\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "2a226851",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:27:55.238Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "edit",
+ "input": {
+ "path": ".kinex/tools/cartesian_move.py",
+ "edits": [
+ {
+ "oldText": "local=model.fk(q);",
+ "newText": "local=model.fk(q.tolist());"
+ },
+ {
+ "oldText": "model.ik([*lp,*lr.as_quat()],q)",
+ "newText": "model.ik([*lp,*lr.as_quat()],q.tolist())"
+ }
+ ]
+ },
+ "call_id": "call_8a1beec4629348509212b3929faaae45|fc_0df8288370165955016ae268da030c819dbf655887159e5844"
+ }
+ ]
+ },
+ {
+ "id": "5eef5859",
+ "role": "toolResult",
+ "tool": "edit",
+ "timestamp": "2026-10-28T21:27:55.247Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 2 block(s) in .kinex/tools/cartesian_move.py."
+ }
+ ]
+ },
+ {
+ "id": "e3336eda",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:27:57.609Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "moves": {
+ "left": [
+ [
+ -0.167,
+ 0.045,
+ 0.835,
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ]
+ ]
+ },
+ "seconds": 2,
+ "grips": {
+ "left": 1
+ }
+ },
+ "description": "approach block with left arm"
+ },
+ "call_id": "call_ef852ce2a3fa42c1b7603121b673065c|fc_0df8288370165955016ae268dcd920819dad51574c26d56fdd"
+ }
+ ]
+ },
+ {
+ "id": "a8adce0d",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:28:09.087Z",
+ "error": false,
+ "parts": [
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+ "tool": "read",
+ "timestamp": "2026-10-28T21:29:50.142Z",
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+ "type": "text",
+ "text": "name: right_camera\nruntime:\n domain_id: 83\n nodes: []\n ready_timeout_s: 30\noperations:\n image:\n description: RGB image measurements with encoding, dimensions, row stride and\n acquisition timestamp in the Image header. The frame_id identifies the calibrated\n optical frame; use its stamp for tf2 lookup. A new subscriber receives the current\n frame at once, also while the world is paused, then one per camera sample; reading\n never advances world time.\n transport: topic\n direction: output\n endpoint: /right_camera/image\n type: sensor_msgs/msg/Image\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n depth:\n description: '16UC1 depth registered to image in millimetres along the optical\n axis; 0 marks missing or out-of-range samples. Rendered with its image: same\n stamp and frame_id, so pair the two by stamp.'\n transport: topic\n direction: output\n endpoint: /right_camera/depth\n type: sensor_msgs/msg/Image\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n camera_info:\n description: Projection and distortion calibration for the image stream, including\n K, D, image size and optical frame. Use the declared distortion model and raw/rectified\n image space when projecting pixels; intrinsics are not TF transforms.\n transport: topic\n direction: output\n endpoint: /right_camera/camera_info\n type: sensor_msgs/msg/CameraInfo\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: rgbd\ndescription: RGB-D camera (D435 model) on the right wrist. Native ray-traced RGB with\n pixel-center depth from a raster twin; calibration and the optical-frame mount on\n the right_arm flange are in the profile.\nsource: introspected\ncalibrated_at: null\nmethod: introspection\ncolor:\n width: 320\n height: 240\n fps: null\n projection:\n model: pinhole\n fx: 358.642181396484\n fy: 358.642181396484\n cx: 159.5\n cy: 119.5\n skew: 0\n distortion:\n model: none\n fov:\n horizontal_deg: 48.085891406656\n vertical_deg: 37.000001358777\ndepth:\n width: 320\n height: 240\n fps: null\n quantity: z\n scale_m_per_unit: 0.001\n invalid_value: 0\n valid_range_m:\n min: 0.1\n max: 65.535\n reliable_range_m:\n min: 0.1\n max: 65.535\n registration: color\nframes:\n base:\n translation_m:\n - 0.069999999887\n - 0.031999976227\n - 0.064999980711\n rotation_xyzw:\n - -0.58936798274\n - 0.589367967612\n - -0.390698619841\n - 0.390698640561\n parent: right_arm:flange\n"
+ }
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+ },
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+ "action": "load"
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+ }
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+ "timestamp": "2026-10-28T21:29:57.196Z",
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+ {
+ "type": "text",
+ "text": "{\n \"deviceID\": \"right_camera\",\n \"timestamp\": 8.6,\n \"frame_id\": \"right_camera/base\",\n \"width\": 320,\n \"height\": 240,\n \"file\": \"/tmp/kinex-observation-hf7pp7dk.png\"\n}"
+ },
+ {
+ "type": "image",
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+ }
+ ]
+ },
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+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:30:11.820Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Saving colored-mask helper**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae2695a61b8819dbc8b0d83052fb30b\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Saving colored-mask helper**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mleQTfSlwFci4caijZenZ7em1fLdgdLajhqyPYYxYYCt_rhYpR20Zrm3wqgsHFNzyeVy3ZyWZEC3FO4cq-m8vxLvQ26s1-P4QlSANC60G0Ry3EeOhrVdueWUrBi5n0Y9Aq_4stdzAYvRsd8ihvcNC6uU4QtdE33jDgXHcLjYhMOKWfmmDD_HFHiXZE2OlNcUyt6qGNHP55QPWG_4-CQsWtpdbXKLQltoLayZupfo1kYdpYDVhOzm1zEzuHJJbEovtI8UsTT-EHcqXCYOEiROtCrmNJY7V-aUrFXktm2u-UzUYU3TW7cA117OMLQITCAy181GtvKaNFClx2VykO5R2hU2TU6XveunIxDP6JAQCGFStDYr3_MjFlHbKZprn7N69Hwm8hD4eisLIk-MRM5R7oMDFVxMF4gGqsHm_kytWI4XDxhKa8wGISclHts6NJoJZCzM2UtPNpaR6yjVVy_StIhdVFEtWH3X2GJ7fNr9C7XoJbEYVZTujlwRrJc-n3OOMGaORrpD9LofpAq3E2rCwCQT7ldKdW4MyB7LKNWE8t05gPkBn1X_lTihnftezMyDT-XxEW5Ja8u1_qtJkt5uPlyrLQUD9bjJAF4Ce8LUCY9my47v4yssNClq2PW1-y93OTIZE0eErk_minRp56f0htkc_-hSzmKl3RtHxwST0is5tvN30ae98PpGux-v-6bYpkPvIufzx7L6_42IODjNFFrtX8FvgxPQB88qRJozEFTtZ475zTalbo2_7_caNlm16tw5sgTG-byAO6h1yhs77Pd63g4DScDTJkJFumM-hUchX-hcsGY6eL_dKoSPdglsziGXBKpijlolPfcyfPicM2FCDS4bXQJl0gBWPoqzC1bL1pZXwxPOmkfug7_fbR8bcpQGoBRqMKSh8QK6Gi_IOaNsye7ERFIhupGNElHQFY-vgG_EVH8fz1mVIHasrcA3XJolySUo-HPxyC1wUsyRYb8kLIwXRjwEMFlZwn4AREp3OmDUa5JuEGGbsKC8eVey01kTE2RU7DPnb9xehyZdCjgAwaQD5TiY8bdi7PryZeo3Ne_vcF-KFzpcne0ssUurtNAHoRzi0ZZ4bNkciWRKRZsnyHT2IqE3vVEUMoz7HWzuglgCvhPmPvgP0PEezwIAylTzAhLMPDBv9oyOC-fFo8RQHCZhaJMBO1vZNsB11ixaxpqOHo_KpUxwZCu-jSnWhoLPo4-p8iNbWmcwb0jnb5BVvAn3d7NBrwUtohgr0h8R8fu7vLA2TSlMPQGKrFq0TCQWyRHwQgpJCzZEE3jZLU4-nY2k3hg7K8M0u11OytwfwTSE2mvwNbnCd-3aZ-voVP7E2dRd5HbklMrySFTC0f5QasGo3zwFegaSZRRhEViBcj6crmk75sUXpjtRioUempruguuH9ueVRNnFH2GVvpm7LgAbDy8e-ERXnsn4MNsmAzVe-z_oVHYXVjMgJXxRVHspdGQuZMUSQBC1odkLA8B_LXKMm00QRBerd2W8MEQOj5pw09rUOKdDKhw9Knu9CFzHvHobDTNiATUq1jj4p5ulSz-jviV8DMIUCRhdyl4MQPbDaaKdyOs1n5U-JiH9_D82_80-ziMm5cXfJTF6_KAwjAxu7vmOZZAuOEhQaDD_7VX1X_J7p1gDCVBhz0zEgo3gGhTfdKwhGFlzNjhk4QWHblC67FbPw8upjgD7XS3M1wR6u0mT1BFKM6FWGJV2nCTQLu9SNl6x9GQ0hS0NRhBMAbHA8A5govlFMKL3U0_TNXxUU-9P7QwoT4bwdgy9SKpjc_1qJ6bI6-jlrs9QQCePJLqlepfT-Ss4ky4us1w2fSG-FVm_4U8dMHioDBdvlkgFU6o9SepoyB83rPnhiLQBBwmlmqHbktGFyefw_F-sIEJ2uO58EKUR1yeZIsrCWUVb6PKEpmFC5xEZtlPh6y9gIBmjTVuVe7ZI8VO7sMui9QDqzooJ1ghq8rTA-Nc62TJuN_-K2EpI_cBNaTbAdgZeyzz7Nl3aoVIoY3Le_WatR10V9T5Bs7395oW0WbJ5AYV3O1P8S0xtn7WrOdSa0Qtx1c_4XbrfBkWKm5XsoeNPY00k67C5aDWNKJl63uW41v6-2RnE4pUOwVuVkS1vDX6DA==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/color_geometry.py",
+ "content": "\"\"\"Measure red block / blue pad visible surface bounds from calibrated RGB-D.\"\"\"\nimport asyncio\nimport numpy as np\nfrom scipy.spatial.transform import Rotation\nfrom kinex import args,communication,helpers,finish\nasync def main():\n out={}; files=[]\n async with communication() as io:\n for cam in args().get('cameras',['head_camera']):\n im,de=await helpers.camera_frame(io,cam); a=helpers.image_array(im).astype(float); z=helpers.image_array(de)*.001\n async with io.subscribe(cam+'.camera_info') as s: info=await s.next()\n fx,fy,cx,cy=info.k[0],info.k[4],info.k[2],info.k[5]\n tf=(await helpers.relative_pose(io,{'frame':im.header.frame_id},{'frame':'world:base'},timestamp=im.header.stamp.sec+im.header.stamp.nanosec*1e-9))['pose']\n out[cam]={}\n for k,m in {'red':(a[:,:,0]>110)&(a[:,:,0]>a[:,:,1]*1.8)&(a[:,:,1]<100),'blue':(a[:,:,2]>100)&(a[:,:,2]>a[:,:,0]*1.8)&(a[:,:,0]<100)}.items():\n v,u=np.where(m&(z>0))\n if not len(u): continue\n zz=z[v,u]; p=np.stack([(u-cx)*zz/fx,(v-cy)*zz/fy,zz],axis=1); w=Rotation.from_quat(tf[3:]).apply(p)+tf[:3]\n out[cam][k]={'min':w.min(0),'max':w.max(0),'median':np.median(w,axis=0),'low':np.median(w[w[:,2]w[:,2].max()-.008],axis=0)}\n files.append(helpers.save_image(im))\n finish(out,file=files)\nasyncio.run(main())\n"
+ },
+ "call_id": "call_2a4098686c3d47a28c6a9f6357ff86a9|fc_0df8288370165955016ae2695ca4f8819d8273fa4384997686"
+ }
+ ]
+ },
+ {
+ "id": "29a3cd49",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:30:11.823Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/color_geometry.py"
+ }
+ ]
+ },
+ {
+ "id": "66cfe9b8",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:30:15.191Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/color_geometry.py",
+ "args": {
+ "cameras": [
+ "right_camera"
+ ]
+ },
+ "description": "measure suspended block for transfer"
+ },
+ "call_id": "call_392303a6dc4e4ae19df80bdcb6b5dc8a|fc_0df8288370165955016ae269664b28819d967fff24cbfc385f"
+ }
+ ]
+ },
+ {
+ "id": "1953a6e9",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:30:17.881Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223017.267591956] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"right_camera\": {\"red\":{\"min\":[-0.07704535908917484,0.05037363663380437,0.9359792452628558],\"max\":[-0.010132965239384423,0.11802476366946671,1.0577161411202283],\"median\":[-0.01790569017331503,0.08437329579285988,1.0223647101538353],\"low\":[-0.01968119294135831,0.11215254015326631,0.9426068395053633],\"high\":[-0.025401475412971358,0.08528556780882164,1.0568718285682772]}},\n \"file\": [\"/tmp/kinex-observation-wrxb6ic4.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/1953a6e9-1.png"
+ }
+ ]
+ },
+ {
+ "id": "df80a3ab",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:30:27.842Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Aligning the right finger**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae2696d118c819d8817ecf4da247997\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Aligning the right finger**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mlzvLOVGNL1BjcDTyABUmK0C4Hxa_XB7nSasKyAYiR37q1jHyKA-LdgUF232YXtqCGLxj8OJr-Tee3XPmPENNi9amH7UBDJW-LLyMSrPX0KRMtDmY_YW0M8Xj8prfoma6AYWjJQfZEzNcRBlgsNiz6vgQ0ikDrNvjWT3blGeXpQC2_3MvDzflbQ6S71343BcVV5La4gVScMTMbW5lMbhzEVr0qwFs-EZEtc-KPpc6FPypp88dH1bommoky9LWYomBlfeQjHnSgG5GOyu9gV9HRi6xaFZnHHR911EZqUOtAmP12dDN-lKu7C7oXU-8U8NuHcFZpP2LKzBN3vF1yLEB40uUT0BGDfPvoQD8aF8rmB2jFyMIab6X8FlwDe5b_rf5qQh4UxBWgvYXkMJEPNbk7gsS3lAXdKzK5E_INFJf9h9EBywscH--9b0gaMKxQ3jILGZa8sA0C18R6Iyiv2pwLl4YMHAZGkblErlgrdKVuP3KaaEAZ0ZB8tM0NaXm7e96Qx71zgnJoSYYNh3FW0Gx8yzX7rbVktQ8NtUbian5HdPxL_0s84jrz1PQ1kKtRD9loCsZM0DU_QmzkS8mrvcjII3n43cdn8qMZragIfs9vZNc-s3xaKczquWozcr86GkCBXMaJPRXsuTNbX4NDSlRJfc3R03ccZHCqS7un44notlJMHZggCQ3xZRrEB-cCzEIvL5t2VdjGW3iYUOy5sYYJadPezBtTypixRm9MqX25TyzCkk6UQPfawvSdSRB3UVvWSHxAGGPipvCkmMLgjqzkeQcxvHNba45nSibfnFQxy1JzYi4Hl_EoIEzTimvsyG-ji4upwyJ7ku6k03nfu1SqNpU8WU9x0_T_SdWrpJYqc1F2wD2gOmrgTrJnqTu5GnW-yr9-dIQK2adMJRKCKcJtPtwPK_o4ldLs2zi55sYUBtPqmDiIwDKtmyv8o-arl4uJH5Z2u0mslGFbHS-MXy0qpJZp4W5dlbVFnBVTH8JkiHsL5AsupCY7RzPNuJntHbbzHDupqeLEmiCrmIyWZQiUU3GKj7vUr8pyJHaD3y-ln7gksLzlw2N4cGhWTqImZeVVgNPkplxtYOjx5MT0acZusprr49Ld3X-WkdtFSoJAKp2A5OpIhe7SP-fzxzKXyTPZtFtzULlhIUnfbwCDiXbAKlPOf9Eokoxh2J7PV_oMlMdUczxj4ZhzaWmj-z-SPtvlnVAGJtUIxhIjmDcTmO9BSYh1ZMP4nS5SA0jiXeLu8S-Reg8c-SaK5yAWfWnAPwuaP0onUsgqd8BKXbeP4-I_V2SHJkb4hwSD4pkwW5D3vV1q371XNqz0qXSedDhxWimJcRrdFBTR391QQFRhej_UPdf3py7Y-rhFeuIXmg8rQcn57MxwkP0SmOt0AaLuWVfzVw5IeERk7l9yn0-5fY-2J7osIQZUpl5TwEe3jQKkeMZUYGgZ5xUqLry4g3HQuZ8xLmVR-nigNGkoE-GfS0IpAe4ewHJAr1Yvl6QWhjVTgs9iFOgfyfht3lVHI8BgWYRhVTkWaPeiy5VoXi0Mk60UAEwSY-NYoPP9WUO_Z5004q6Ce-KRkQCrK0lFIaGXymECXeFBF7SlU8U8i6qeV6UKlBNJRxSscMwSQme2-dg9XdxrQ-5RwkuSI6MgyvRRlPv455ASi6n7o5Jy2_ocA7hKHAdizYu3seWDssXIJOGNjhxkGR3MrVe_QnFCDiOXYnghQqHFB2MrTEqHFO9PkxcZuZKH-UwlwRHLMnEfsGA_0VocB1StXlIhNCXUidTbDHCRXnRR_KqGhqv9JgO9PY15bnbyx0VieyXqhGnzkUjwasZ3unbeG9wp3CgdJL0R70ZNzf-ljsltobi-C_uwqxZJUvt75F7_bnpJOpN9lBs2xpo8LFKftcdwZjsHmYOSZVz7lNRIV54TouWqSe6LAV0-OQnmjCAKtL_MgTKz9tSIyqWGCn7yDpe4F973r43K3w2b5iYv-NTTSOwokJIhLZv9r4oqX_hScm5O97jMIixafOfaruNf_4iwaVSWy7n4bVih1Nnh42LvM_G-hIn6L43qsOaibcIgPQ-YjnSqXvkgnxLDadpoqH8QkX5NF9icVOuICPuptaG3EZrl69TD2vwI2A2VQ9BudQcBkJ9Ro-8d5kSsQggbnMl3IKdHyVkLRuueGkhvyXekQo8fN70NKnkOHTENkU9vkQk6LDzWVuEd-uNsHqoOTdTqdZ3qnEf0QOmegcLOev8YTru8bedI3mdBiXbg_ZFqkLAf9dP1CYEig6HPMnnKTIcvx8fwjuI0zUWFLeGlSjXqcWZKURNvClu2FnYcXa3iiemAGroXNmERYlXG4yW-y9Y7wn8clJdyZ_p28oCKt9KWblrcu9z6VtsupVB2V1CqP19AvlkiF_QfII6DUgVGPWtk2Rm_1g7XXRUKD2pGct8EEJPlnjTAvEjO4TtUokKl2CerB2kdhRrznwppC9DdANbbtzZwFF42kf4gocNHPd-gSrcK-FSwh-2wMOSGmB_TojvHSjWAdWl23pU7Zk9uK6nubPdBwAogQGRSEj9xkEYZcPNJL1iQSCKjMlU_YuDbblXlJD_19ivmftqMKzEtjdpYodODZTIhUIVmogVIeEgZpRoMrj6zfpeNmxklGNUuIz4mxwJD64SX9FjSLs5_2xihlp1LkaF_yf5rHtKtxcURQByj55fK1IQEKsV3CEBR4Gv1WsSCV33eO8fx4zjDXqZnXB1exXgShCcZlRZqbKdu47mCe_0RSLapsvtzaM_sO2zW9SGbmZNSNL2k3B5TISaeBnt76kWrxyS1c\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "moves": {
+ "right": [
+ [
+ -0.044,
+ 0.084,
+ 1.025,
+ 0,
+ 0,
+ 1,
+ 0
+ ]
+ ]
+ },
+ "seconds": 1.2,
+ "settle": 0.32
+ },
+ "description": "insert right fingers for handover"
+ },
+ "call_id": "call_05f5697e44044c43b3be8540c2ffa31f|fc_0df8288370165955016ae26973b0f8819da4025981a45f1519"
+ }
+ ]
+ },
+ {
+ "id": "5c5beb92",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:30:36.669Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223029.805918588] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"wait\": {\"success\":true,\"message\":\"ok\",\"time_s\":10.120000000000001,\"waited_s\":1.5200000000000014},\n \"left\": {\"q\":[-0.5804733037948608,2.104207992553711,1.1955286264419556,0.9432793855667114,-0.6488001346588135,0.010548126883804798],\"grip\":[0.7495477158914913],\"tcp\":[-0.09106256375115962,0.09291270090328957,0.9573460230231323,-0.00019867867634500307,-0.014277350018817896,0.7457316671533772,0.6660933856508923]},\n \"right\": {\"q\":[0.28108417987823486,2.3755812644958496,2.0089495182037354,0.41051310300827026,-1.1974685192108154,0.03320124372839928],\"grip\":[1.0481817857785658],\"tcp\":[-0.00454658121577145,0.09928463248112668,1.0355422699375194,0.00233159746702242,-0.005923685166572289,0.9996083980399332,0.027249296786112258],\"joint_error\":0.07316711639015039},\n \"file\": [\"/tmp/kinex-observation-skgw42gu.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/5c5beb92-1.png"
+ }
+ ]
+ },
+ {
+ "id": "57b52148",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:30:41.248Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Stopping after contact**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae2697fb380819d8b684f39f1b632ca\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Stopping after contact**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mmBxH4HEKYAFVTM9X2N-PqC6TM3lSM_pkmS2b0eEbHypvzL0AJ49oQyOrsuXkxOSR24KQrwzDFs9IVCIO70UoZvkTSoTRlDh-TSgeF3-HdorO1_VKR3ErcqYBNBp76bJDTsKvPDI-CS15MffkYbvS0Iz5ZYLn5ALam3tw10OcyaK4fc2L6CAz8G1OnkDcuTapPTHyOSbciNfWCQocZIivrYhJ4QXU9cFLj0K_29_lfLBz8FtucjJR6zsPb-6TPH4FoZvqTUuadWHTuzcgcXEiHUW-EFMeglkjEGyHoHKrVJBE6c5t569umTV7XsvrBIIkNcutJJIagAtbIA73coitEuhMRHpaOfRt3IY6Ln4Hq3xGmKiE-_h6xbY3xWHCC2kgPUiQYhufiEx4veCOU6aNaQVTZ24dnNSG5tP8uDs1z4DzMNaVceMKmfO3aJ58_FFtvAjq_GUfz53tqeGZPogCuwqr7vkvAjgYZdkCOmvNGOx_NxqXxr9Q5pR0oDUo2Z3LqJKBZulFOIttD-ZVZO7a6o5wB400YVxomubefza-jjzYzfi0pewjRZ_XgUq3ScA2QUEKTGvX0Hzipguc5JwJoFuXRkPLtUiG9mBTMym9V9kmBMHZy6GSPPz0FPWbt6SPPl8cbZRqDfGPnprdNGBOpO-5M46Q_8CdyAug6LKkmfGGQ1wGfNHDqd26JFVS6hGHLyAtLfizx5pM7wmMbR1ZT_y57Z1e0jsc8PsmBs8vlyFTDprSRnXu3ldQJYbCWsKcWuWBSdj_I1aHJYG_v_6zcMvT-bIZS6vqfEpvVc5HizaRsQpLCRvsUxQ9bCIOvSe6xvCW0d082YV84dqPYgBxMlaoMpS2TK22T_eonRtysFYXJMij-ZT1HaBUUoalP5utz5BkJdwsGn4Z4UTVTJoLusFFMdNHVKfDohu0JhvQHiuuzz-u7tGVQ4Jh30m4-8Xrlo3eaFSrDakjl5lmt500fA1lv_rRxyd8XdNcJnAN3sB8se71h3T3SuaGwt56IRr68B2uZP7kqVUdbbMYcDCbFQBSfEaWOT6kgMC7H8jCpla8kRxIXW-Fort53Hm35Pi_gFxRZcLWUG2O2mXGSeYzVB4iaGn9r-zfKLGoUrl2QvLT1ipciotLBCLZciASF8Ra8hZSdCLkXkHtcMe1fqiNK1T3cmG6mm5qAogAKDBRlNgFUXI7WITpkiegEccJU-xBT0ozHCnWgjuwpQ1PTasnuUpRi3A38q2qs6AE2fzcH0oK8ZhfI2KaRAmDLC84UKcL1JJkj5JxvaRoS9YsfJ1YvUUx1mMhk7jXBqmRJThxDnW2CTLqPycQ71GJ5ErwDdstKwbX2jLLvlJR34q4TQf9KdYrPZEpXIoWa_vr620Bh69KZomT9bSLhPWNGiGv5G8o4nnwA31uOUxBhADG6VyKGeDEhWoGmtjBH57Zzf5xLSlo_mCWooyQsHH7PIJS0zLWBC8i2b26gOEziBKlbNZIee0Tvlv4_ODO1Ab_9e0EzuIuBH7WG9eg7ssmuwJYsM6PkJBdI9Au3WRzH8au3_j4ttxwbpMWeQBsMPvLlesSm2B1RFWTmkdG22RIRY1sotGFlOKD2uCHlxIxXVjFaPOQ5MoCbIR3tk6QLUZsLTEzvB7IiAB6L9Db1YdA2RPWm4XEOT\"}"
+ },
+ {
+ "type": "tool",
+ "name": "device_stop",
+ "input": {
+ "reason": "Unexpected handover contact displaced the left arm; hold both arms before adjusting."
+ },
+ "call_id": "call_e5715b20a77640bab42f190a5e5e42d4|fc_0df8288370165955016ae269811e7c819db816fc229d8738d1"
+ }
+ ]
+ },
+ {
+ "id": "ae3dc1a7",
+ "role": "toolResult",
+ "tool": "device_stop",
+ "timestamp": "2026-10-28T21:30:41.346Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
+ ]
+ },
+ {
+ "id": "c3238e4d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:31:01.056Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Testing right wrist orientation**\n\n**Checking gripper-camera clearance**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae269840ea8819d9f3b163da656f14d\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Testing right wrist orientation**\"},{\"type\":\"summary_text\",\"text\":\"**Checking gripper-camera clearance**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mmUOIM7xiIjcgS6oLqcRcaQW9N9TtMgwMxnRfD4aQ8dhAniS2mkLiDai66HvTntgmkCbTL-H2lL9mjIrz-6sGT57NoBonPdMIMoCVzma7SB8SCe200nWUO4FvfgBtXnrlk_I-yRVbtvt75wrsb1863oO7LgMju-arN4ELNNTnaWJDR1ejxnrItE2Ka-r60DuweaDXMtGfGEqKFIozCghqB9yUfwRq-n4CqK2nQqYfw8JSJwjbWDC2xkix5YFwM8Fr0CZq0KHTvMk-dws4IlDansItacHKibfbuIYYTtY8Xo9kFH3zBopSUAZnKRkeB-OE53t-EF_z63pN6F1jJRuWt_5OyVEG_p3meIESBM5HELFDYXjp-HJ-P4XvXG497670rTw5IPfREgxWJ5YCq6pvAcI-1Z6oHIxtqxgXIoLTjxDHZUAMm9Fjf3G0dLHoWC4kTgEltEalKtdR5YE1Fa_fmcfSkn17MJz4RGIewwk_g-posBJDMuHya8_-8-icUsqAcfYv9K3YASCt_ERRjNredy6tfdJYiBMgCzhIiR-qg3eu7NxpNUC68lW2SvkrotySkB9JZ4g9hu9DWnthh-vu2oUlaOiggADT1Vv2PHdjN3l2CQmbTsryVr9uzTTMdX4WxhbsZV7ReK7VH3qBE6xxDWbCPVgEWDso72DBL4xVp4c0EVBN_LMjeBk-1xtCwSAF4jbKLGmNX4iYrEhH1Dhz6U8FuGCBNMqY7sNfjvcBY1iWEONU2mt34yTm25CKBaWK_nUiONtcpC4DqwPU0h1wZf00lypgzWreuKdU4dC-f0oh3pwkXZ07soc0wTYC044HcKE7URMT0iZ_wuYZ70zf9Yf8r5wzxSODhNierlgUM8RfvNH0rnO7YhJ1t83ba2Wye6Sfn8Ro_L9v5Rv26reRskcapA-AtNspMH0546Rl0m1uZdKFgEl7qw2IrBdaOAbg5qr-x2pnvVLSvBt05Sw7JYrw9_xnyI8Pkiki69xpGZx0o6NDjSzzOYoqEEF0vYVKxUb9FEUKV3H0FXeq0rp0qEze7ULSLE8yxoGX2n-2EcmDpQMbaopXxtFRe8JB5lBinvIdV4VNoQuyxYXHt5elu0Xr9qdjI9dEU0GKj37wAJFvDytXfwofvxg6EPtZCvbIts4U5pBl5pGEr4BIF_DL9VRKoTq305pgcKVU-b8l8aaBIkpzcVkC_WEGcBhyKDmwPOPGlOgxVQJ2B3j4cwhVTQby5cTBlZUSZAAxqG69-R_5A8bdNlo3zGNQ3cd8btQZjt2jEO2RzW7bU2UbCbkQ72qHxVY2xizrkNYcOonC6iwBUQKkdGh6GSpZdGyG7VlbyBG0dircb3sXs-aDX_gOCjYUeHU55O41V9l__1ySQX9r_DXgGhjBozzHlB4L_Y5BUxDZwVWW8t0EISkocOhYDzFAI95l9fn0D1ARmID_fa08lXIVF5PF0ruhV5SsdXeaSeaOXjlRYp5nHFOGxotCyA6Ugz_iNXjByJgpJN-3l0f2V10Tm6MIcMwo91wdmStkWSfrLzNK5Z5E3GbKdOshg_5w9ey7e4k7s0ULec7j-hqygGD5wQ1DdC4_qAVqEEVN0ZXtQWStV-ZwNzh6fcmTglgOhv9f0c_AuGcAMyu481xJOkFZBEP8K8SsgEtwnpIp-vgA1PUAg9AOWTXl_vEci3gyi565MRzhCR4wB499hoSi-qz54OxwkdHMBFUZ2wh3F2HU4jKOSQWKZ69M-oMy3QDedJf2DTCKA6pXcgo1FZGjcqAj1u4kGAsVhzzcPQTTTXZqmIgSLZO08INvXUxZj3fl7cSqC5L_2ggmQnQKZpFtOBUxcH8gb-_C-FqB8o26mengWkdfjnWFgosPwIDfFlhW2Ms9ZFrxCbwj4l_CVVtEv-OWEiBipREgzMNB-gJnIYH9S5UaKpJ8x3UNLuTTKAjEkgkhxkh9Xf2y7Mr02g2RXosd-kUCA7z6S0atmTgaQBuKhJ5nQfT0fk_ql-bP6iZgEkOjkaRYr3z7GjYjPaRl9dpAHy1V1nTZaUji1PFsY2_Rhcx-6ut7Qg_QDG4bW0rqy9J6d9TQwLAkcMr0w6yYu9dIs4ZNV3AJPB_ResL0kbonPpGTPLOYl9kCGUZ3aJqTtqaIx78J0KaVGNiWJAdeMuMb7dm_AOGdnTI3U4EcezJKK4Ih3l9ARKk1o1I4VAiI0cY6LXAY9NAWGolowAhLFV3YVVaKGAixviK4ZJbe16VwJ1Rq23OT5O6TiIi9OqwrRzKotNyx4pzoUuC56v57Dr44adG3Qw-JKJRgm8Qq-h8W6jpk5XtLWOFiB1tc1-JRnyo92VjNAF4m3KQrsbtCCOsKx0li6J-U9mvh1WQjRAnUNWojwXF3qNfcSyPtl16FJ3D-sOAy-lDa4utZAH1pmkivI8k6Bilw6uEUvwuKDogay2ikWMcT0QGYFz7IxbfSINd4Wnfs9yKPTc3nGvTRAQ60tEP7tqV1IDdKi2FeJCJTs1ka5AuHBfQZl622gKa1p3YL-okvr_-U8WqFNwrFqarve0RzRNR76-nOT9pc2VOrK2UiHsSqTqLU6iWHQNCG0XHyIKzzAFrrSt26dk5s9mZt2Trund8YjRrofIOJ7xuEH102KEOP9C0Y3xzhWuvH-_aqeO6nuvhn-Pt7WWkoVFJDUxsf4x2knInmh_6EK2CSfhPVMwkPsHRsqGVznt8rwom1VCSjxHpHDcIBRy-HXbe24bQtudj0wNAfJH2Z11qLjErDFYLApG6yuPhjY_F8ptA1jhThJw7lgYht_t8KWjEvdsPxgkQtKefk4CQWqugMMY5TwVG2plMxRMCXgtz4Rlqg3oyFoX8BN5Z9tWY8Xc1XfRn1IsdQjtexFQ5gDDH9yBHZYJ5FlQ2AXPtP95oFioilGML-BFazRnuQWd504BHR4k7HvPzMfoNAwtVPbBz4vNPdK4FqFcgZ2fZJp_OUgVaKBIcI4YAe5nLyE-Z3LVIkO0KEe425fahVdAjSv40dPniMyGXa5M8DljUNRhyWJIVqYf3zx1B_y1wotipFaQAT6VJu6JITr7eIdicrP7mpUswRYmJ9QNIwVXV8f4Sdl2ZiSH6LdCRi3RN4x7BWukY_5nRgOLqJb2nKby5CU9W0BkWteuv7W6xOw-sUqqez5TRTSFMvcU1UBh34xYm9Y8bGvrxp9QNr_6dB4OXNdGv6IHm97W4q_IoYA80gH3RP8GR8p9Ozjw1RJR7mogJrl6bxeM989QSs4Qj7dz01GM62PxxqZMZjfyPTXBs-aSHYb_ixYNwqGqB2XAd5zbg58lwcwhzlx_APQq-cvMFuHsA3oEMi0Z-ZLb_mOZjxQqPzQfPRm3kdFGJX_YgUaIP3CE4g55Q_XATjqbUrYZqvIKrCarq9YkSpBUKYIPpupKTuA-pSFVpqGoE7xNNiD-gvpYRhtEuQv9CyiSTUK074iDUtuHMFOHR1dr2k7KJOwHUg2qtMTzNBrJ1EZyQUB6g5HJm2z-OdQQ1Iagm-Uq6dLL1Scxnfz61Eu_qAaoy6sXChdd698TrOIpth7gfh-qxIiUzBNDV_GiMu0bDA_jY0SZ-qKN8auMHnnCRONF5bSbg-dOwPUGuxPuXxgNXgKTMtMNSeFUmu1718bN6BbHm_5jV4bADVzGzfxz_4G97R6xUnI72Njkk4nquJNAi7x_dRs-lcb8xMeZEdpVnthbETDO0-SQwS1KRiAG9d-1KfhO8TcHBirb31kuUud14iWBnHkv_81A3Hz39tFN_YtNDJzS47ei6MPQyffzhY3EZWdPNoZVegvhZ1_8fbPrXtsnfxWS6ACZeoPjnMmJP0XZ-6lmZPxPs2K0xStkKRDmAj_L7bD0Q_WHehbi45MHyINfg1gpPVWc12HqJcV7N4PHV1XlBmZwYi3VhtoOB9qi7wKAUvQCwrwN63om7cb5UtbRR8eO31JZ7s4QASEyMuJnPz7IgDDpVvSR1hR2iW6ISw0kojgIgfR6K_Qf8ySCu6Zzg1QjASnBtMuI8OTFm1zwrtuHDvOZwfxAtmiJtJysoVo9E1d4wGzlmGnit5DsTVFjxz9_dCUg10XMjaVcE1t9Oz0BBfyJk43WBjpBIXy49hgRfGTDIz7LCMb9oIze0BcIE4R_7gl_PvU-k3KrbxmA9SzciBeOuKMsX_CbUdm_4xVLj8dM5nbDzb-J5jViUz-n8786CeWuW9UMVSCEwZ8SKo4d36nTHnOKVWPJyRPH-Ef6ObUddTcKnfYjAq52hFGAkuWBFeGn8IgJhidOM9YFouiNyB3U37X_gk4gfSthd_z4GuXlaM-k7T_RlvtN58jpGFkpUbIqAkp8M869lbnIMGsaKsjdKTVKB7kHhbRVwJXxRxfwOG7A_wifbSfZJMXTAexiJPzk4H1ZRiJaZE_VrttZtRIunSiWDl52I4PrDYbRdK3QmeHdmQX6qmg53r7ndyPqrGieq8pgS20nNNhgst2srop601lRwzC8AHTmStf6sGkBDM23lRUQYx_UaNIAu4Mdp3sBReGbiGH5dvtYMcdJKGfm1t1gAMz-wE_QfA675un7IaYnAttfkxTRBoWmNieb82h6e1kmlmZQuG-S7uqRdWOHQ-9ADOtWTOZUnS8jbn9T907Znx2yVDh3Ujx3pF9LsUduee3PiszJf-a8DgsPsXE7mxAi66nbM95v4S2Mj1VjF2oE_XIrU2eFUIcNUIcFrOTP8cpJuriC36D6Xw33Y40hYavqmjMrzs5HZwizLnJGAr1zXc0HddTRme9OPrFthWv6pS5H8uN2d8GML_Aks0djwdhj2l_QWWKf76LUA5WRAFN8_UMgvFHt7nCIiff-hpK1qQMP9rOV3iN6DJsa4lEgOaXIEmrZtihWXglnqrfrz09mAxy6iFJjPVi4ZDzpuEp3UvEjTYROKda6TLpC6RSQktSwA51Fb6JuTStsmfufOaf7WiZrJMQWm6Qan0WiAhatPOOxxY2EGNG_iKOnRV048oApJdtz6I2HMzF-adGhg7ZstmKpUhT8IW70pyn76HYZgghvLrP6u0txVcMpjBwFNHbLquUr7KM3Ydk4msQgWkeU_rCwEWZKK7N3oyvCwvf8uLNJqC4Kg8420cw7mXMC87WjexfQKgY211cyU8cnvwrrqWi5oHLkpntEnyGRlA-KHWChM1jiuhIln6ZDVWM6w_CwNbfIMV7YXa29vQ==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/color_geometry.py",
+ "args": {
+ "cameras": [
+ "right_camera",
+ "left_camera"
+ ]
+ },
+ "description": "inspect contact geometry while held"
+ },
+ "call_id": "call_bb94d9acc5464dd6b9f05f68aecb9b32|fc_0df8288370165955016ae26994f0e0819d81f48545801ee34c"
+ }
+ ]
+ },
+ {
+ "id": "86db988c",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:31:03.947Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223063.023708069] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"right_camera\": {\"red\":{\"min\":[-0.1384726838486533,0.06276790815003651,0.962540244023994],\"max\":[-0.05922303365747568,0.13124786536745542,1.060490489585483],\"median\":[-0.06550222925211087,0.09469825304345947,1.0415251530870966],\"low\":[-0.11114994769135768,0.06490913732700883,0.9669796277877257],\"high\":[-0.07376581631004708,0.09461002694122791,1.0596298811854297]}},\n \"left_camera\": {\"red\":{\"min\":[-0.15688127335414823,0.12266262357040175,0.713505453118275],\"max\":[0.037058832820139165,0.40054043859581245,1.0031299882724507],\"median\":[-0.07028974145388796,0.40000044254322253,0.880343311680841],\"low\":[-0.12835342427817242,0.4000191366344823,0.718829186316962],\"high\":[-0.06946718738984804,0.4000030238401364,0.998369265895211]}},\n \"file\": [\"/tmp/kinex-observation-95p9oprm.png\",\"/tmp/kinex-observation-8vj3yjvv.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/86db988c-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/86db988c-2.png"
+ }
+ ]
+ },
+ {
+ "id": "af89524b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:31:28.561Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Retracting right grip**\n\n**Retracting right gripper**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae2699bb50c819d9d8314be0b1f3524\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Retracting right grip**\"},{\"type\":\"summary_text\",\"text\":\"**Retracting right gripper**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mmvbrW0hvVOx2SZ6YI8Fgym_FnpHR4l9pGUBd918wrBHyQxk_zVVK13W7o5K_fBsVhn7j3V9F5O4kPCB9Qn7rU488QtL6S3tnzF-F67WDp7je4cBnew4X5TZMjrGr9HU8LfepUKPiMM9yfgueGmcTWkXPzKI7-lncTRER6FcWRoe13hYkSND8YrMEYJSKf11DgnO6N2VVz3j2tU9ZUuibOc9UfGY5cyzKghyKAE3SdO_lFFc6aX3GG_1ytOImYp9Kj4xvXN7aAErLrcQOS8r1s9mGFWXD32QEilwMZLBcC0NO_ezApJp2i9p122nBJZVnfEoYgs2nBVloY8vFHOrymcveKjcKaZcZkHzbE4hWjcgryQg2uHhW05M-Ltl6QZlBzcDPGLkokIVL-H92TikQ9xNC8kiDLB1s9HlCAyYuIZEIIAjN7Pc4tXF8gEXKZa3WPy5Svvw0xLwnBaj7rwVijhqXnfsVdz6RF78ZeCDH8FvJqWG7nWJoY6vYCJbFLbQwHJFNmx_J5tA2q9agQoed0c_PA6cG7Vqq5P1nrb10DDK9ba5vpQnn0t5zJxOKqlRDkBo1wVUZKWks2Xq0VKm7oJjzc1Zp6IFHanoY_s62byajCE5KLjD1CVrUJkvj6j0uDj4ToCeKryAh7toOGQ9xNPn8XmRi2NoTQg0-bRHuwZwwKZHy0MkI1nF-W7qBXQqSzTIDUHdqiqMRHc2liSK71o7ExXb2COfiTUPWEEsIKRwLUNT4R8-zTIEnzdMG6muzoaixo_2MyfEnE_ODc1-ZC8a3DUDDrb3SAoIUoqv8GadPeqfZCLroT5FM1aXUiJykG27XxRLAuWu0g_wL7AEM681JFxi_o1nNctUTnQa-o6U4jg6wCNJ4nTeKbUh0G3sO5LnLCDl_TEypDKgull7FhS1Eh0VoMKCdTx2uTE1aILiguM_RmIRbB-yV0_fKeg8HlPrpoITRJMoDAljTb1JqHLAWsfEoKfim-XIJ95Y-jNUfEIj3VdNllZQ7ffGLprIft0GnxCw0Kqzonf3HIs0ZTqK54jRTqQMR4PER93FFqSfvASQPg114D_-KPB-S_VP4Qlc7S70mNvcNhK4p_hYnf2akZIE3AwPc5YUOI0cAbceUvh_TIR5PXnLxje4fCA3sXVQhQo4rf9qWN3Br00ISc1_fe6-wNZbuVKxoqzX83SeiTjJHyV4GlvgjQIJF0SRknxATmeIz4O4sRaoCUeT6MYqDCOPT6zbCVea2NoHryoMW3js3PmTAp4-B14sReipMFblJF-m2lfdvWll9T6JYlnCDliTebVa44bg49CxzvjcDNmvaqDxX5fT-eApw2tAL7wPsC6vbZ_5HMN93zVnbrDNyQIl9jcs1VVQNuF5ko-_D8G-4kjDb8M85jqpC4RZzZBhrFuKeuljkLTDJuvwuDT-As_F5LV_YGY-xOoSQlh-DFpLLBLgZqafENb81ZNsw_txZWa5iYciR2A1wIyBEIDCkDrgevwBcr-MAwHVGZr30pxh1F5BRqfMI0iVBnwR-7_KEBkdLQg5nO3wBtlOdJrFe4jvA5264QHcNMrxYyduRnJrNX-ALZ3QNelFrXd7G8iR7iB1SMlVjM2znVmc9abG1HuMwHDzGAmkRLT-3TUepWjscaZOer7u4L4b--nc4MZp80bKMltzht-tPYNB26r2c-lov_zsWHK1z3cLS-xGgCL1_39fgf5dtIxICiYxlwEfzG_h4vv48tRlrgpzHgE8Luerw8gZ8CGUF61FVBHXFcBtUo9DqPWM0pqt8iO2tkz_FAAm5HtqerA5HhDJoqNWqLPX9jIYJzAtni3FEgCWDS3KjOBqybSBffi748hz7ENLVtZnMfy5xW9EfxB6jZgTZ_BkiKO9u1JTde9aAH4czs2xWfbEeYtzHDcSiGvPFj-GAhkyuoz3iGYgMV6SbRDUQE_3TSLam0tTPHYJ_MdruB_uJ7wv-nMSCBjD8Z7To-EVfqJ4QM6GQ-lIvdqr74dllp1b6z4JvKI5EeZ73XH3PFd5C7FkCfkWf1aTARV6OWEIjfs0Ljq50ojqDkF_7rhfYM9wHvhsOkOHYfadHPHbMo9aGYUxC27DSuhnRizMhaXjd__7Xl_PLeOhXz0rDPORtw-CNRY7Bn2rwcv2MyCXG0nN0d9PpO2ykXG9wJkfHGug3HWwaGBYDyYDLpCQKNsP7748092uw4vKp22A_iKo_tfZYDxFy2yq4PGaCrRkan15TbNVjcd7BBUm8vNcrOb08ezwehBZwkjujxuKY69pC-uX6eQ2RLMZY1RhO_M5Coqzioa220ytFWjLW5FH2MnZyqbiDxookKVtHWdE_WQCmbpMAHdBTy6hc-qZM_5zzCTMIvugAiX4-ynxTdaWZzfeONm2QeeDeXX9L5BWNXXvJewfVI2FK_UJ6hXon7bRYmzgFGhuNKNT3JAmczOc2rMk_Nj876nqGxlGo8Za30XoW7y0ePpHoZQjDw6rSAianHmp5TknVbWKYubOaHgstieEJKMSpHCLOsPbJY4SXxqAGYeuaHHN1w0eIlI5v8ymGK7bljGif_T5RoOznX_RlqiKK09E_BDrBBWrVS-J6_53SLxLRgAU9PRPIlqzxEHi9f2EU6s34HWkvPgJPlb3Il8_BGpImqaq_g35aPUmh340O5aDCayFv18wtKeI08vcBH7bZXoLnFPXY8bHiEynxtHrNxK3lCg1Frvm4SQqXVQlqSFI6LrTK9YCHS5wKiq-2lpf_Uhd0-coV9aKTum6smaI9KZCRREKLJCf58LnBlMHes0OnseStK0iFHzhN0yxIpOazISNFaNLsQct-NJKC1i83eUWqCTD1BLtuGKeXVrnkaT8tEmSNx6Y4oB7ewQqzY2l3ky_pucRKG6QETvec_bf4g1UaDFixd2rU6vvrSlulSaWhWTf7kbpwsp2oy9tOQPDH0zWgiJlK9g4Ap5U2kzSFy-idO3ieC9HQR1jjaFyLEAUnzueKWkQYn03cYqTL-Jb5FWo18F9ejy6VzjJzZQvY_t0beXRPzoC2BJmuVPYrc2GrkOova_Da2bdj-g6AHTDJiobHy7cNF7Ig42-lnhz3eNwiUiyxG_lnFISmkvjABp68ipc-lVMROeyhlP7tAxM2iSr3unnhmKoASLTX01D7GuBfdc4a3fXsIpNwduEbR3V8WRNWzcmRnVVBXW83JGAnaATrUlW7F10hTwodm1bACFaXfCerdPSpOmWrIK4xvMMt_A_8Sd0WWixNbn8-V7G6lgWXVC4Tg-TGfM9UftJYl_KXjEPr_7j2eNTzzo3pm33h2hFJeS_yXDX5Olf5oikNMSSnqtzsZGk_LFiAjg1P99lbWE2DTN2rq3HNzTM1OGwuP6wvZZgDTgIBw7Md-6SZc1bnbL1ptxYcDeFj2yac8BepSjwRhOLo_bMCo-xTjIlH_p2cZr8AjT9jg8L13RaxhMPWxzLKNmvO8f3U-hFX3L2nOLNHMi2uJC492G97vWXu0K98GXhRXKGN14GNxNCcyrQfEvJsjXdOi7Tu29ONuKl4vUlFaqMm4yuDGsn-GxVYnO8yA1Cxs_H4D_ELVhNIP8ryVpglxfzRxyiBgzxD2siSx9-FETB5BC_OtB_lHXZpe07xDaXGQeVMWwXczsIHy6p2epzJc_TyLn_h7a6uVUpshp1oSICFDrfAwiseIoNFLF4ERbXSGCD02dWS-gaWU5Ym5eWXApwSEZrhL3tq5I7AsxVVjS5DiGWhIDwH5QkZNB_14HohR5ypHsIGHBSptGKLIijmnBZ3UfGNfwMrnKRJxd6iMr1a3w6nGNdaojTownWG8jezYwmh8hg7Ond5SiCSqeyHsjS6dQO_rba9reWuZcr06Ng7WCaSF09Az-tZyS6PRSdDymSUYOiHVbzbjzjrAmLYoQY5h_y85-gjqZ5q-GxtzfzJy6eBbCRvHoU8qYs2iOuj-pLh60O3yVcwftzMqhQ0lEYVorYb29LOxH4WJ-5P5QKcHBdJFwKQinvYyxkRZ8TWhDf2Lm8HuV0hXM6t-NaW2x62vDvtUKt2ce5e3Hs2NEabIzi7sdwKKZ0DHaz-ckkMGW3ZCKUKoEWWJbgUJXngVSg-cIJHF2ulT3idmc5lltWHN8aji91joJqpr8a8ZOcjsvu85ym4cNjGuODeOgt3oDjonMI7u7qF36EKWJFqdQUKJdGE_uPxBnCyXd2Og1SzbCDQJxFQWvW3frzndJgJ4Bq2NNjC6LstqjDXSA_CbcFMiblPSQ7-MMhfNsvidlvzuap3BLS0kp-Ucn4f652C5X5ikpLpIEOeTmIhPNRAG8K_Itzcg5WRrDMP_vije76u_GpV1UK0-IlW0RO27-UK5f5u-CbfO0zm7KhrRmW51-dCfMsN9n8TvLVYYOCopFRdOxhez7oZFV9VPBqlssFmBTnd1YWHRwKJy7pixARTl7Qbxi-XHZDM1HbNKLpBcSQLB9qBRmNtaIdRC4grc3QmN3xJ6z6fYus78EeWgGmpV60OoyHggJHK8tm9nBKv3JJRjiKRbCXzQOBfZVU8DGQ-F3EpJId__ViA7DZgGOR6gWT2wYIgOiRKiRZu0rGYKgdDApX-Pgn4gDqWGPpsFUzh-SF2GQxcb0j3477F9Bd6OHc3vGF6UzhNmOUQ9d9IbgkPnp0ud7HshaBa4jxKHlC-gVuLNY6SXi6BnmmE1LYsaQbC_Z-wMdteZPjl0UIQ9I8zV0WV9Cv2CqTpqU0yqWmTbTkF-aVBn7XssW-Elxd0iBZbPvdpM87OX8ejx9kldnWD29D_1a6OJoLcPntyhIt3g-88z06cs9Ii0s0jyEjQmWr8WIbyHXCjxVws1cp9poyNUDcbCVirPpTu3BCuoMtfqtk3mJFXJq9dLEbof_z_dF_Kwie8wpVGA-hD0PkLMDdNl5EzBQpYROUGgPA4r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+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "moves": {
+ "right": [
+ [
+ 0.15,
+ 0.1,
+ 1.05,
+ 0,
+ 0,
+ 1,
+ 0
+ ]
+ ]
+ },
+ "seconds": 1,
+ "grips": {
+ "right": 1
+ },
+ "settle": 0.24
+ },
+ "description": "withdraw right arm from contact"
+ },
+ "call_id": "call_e308aa226da84617af9899822c0d2548|fc_0df8288370165955016ae269aff950819da6e7504915ef17cc"
+ }
+ ]
+ },
+ {
+ "id": "5ffc47a8",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:31:35.498Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223090.836931004] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"wait\": {\"success\":true,\"message\":\"ok\",\"time_s\":11.36,\"waited_s\":1.2399999999999984},\n \"left\": {\"q\":[-0.5804134607315063,2.1041758060455322,1.1955393552780151,0.9432682394981384,-0.6488250494003296,0.010563568212091923],\"grip\":[0.7530979514122009],\"tcp\":[-0.09109739092829977,0.09292400028290476,0.9573646424377735,-0.0001907213903724974,-0.014287166396507055,0.7457598088703344,0.6660616697989699]},\n \"right\": {\"q\":[0.008498204872012138,2.4111969470977783,1.9728046655654907,1.1586765050888062,-1.5211362838745117,0.7175896763801575],\"grip\":[1.0059774978594347],\"tcp\":[0.13843104276620039,0.10128114809864314,1.0534453784964337,0.005817304808264196,-0.001298347103139134,0.9999791132900113,-0.0024992485451372226],\"joint_error\":0.1610297677623429},\n \"file\": [\"/tmp/kinex-observation-cvsfv2kv.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/5ffc47a8-1.png"
+ }
+ ]
+ },
+ {
+ "id": "5c98765b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:31:51.357Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Positioning left camera**\n\n**Positioning right gripper**",
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+ "name": "exec",
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+ "grips": {
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+ "settle": 0.32
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+ },
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+ "src": "observations/5df3e384-1.png"
+ }
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+ "error": false,
+ "parts": [
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+ },
+ {
+ "type": "tool",
+ "name": "device_stop",
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+ },
+ "call_id": "call_00a46d3a1de74717afcc835ecd9791bd|fc_0df8288370165955016ae269d774b8819d964cacc5ae8a6955"
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+ "role": "toolResult",
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+ "timestamp": "2026-10-28T21:32:07.658Z",
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+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
+ ]
+ },
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+ "id": "2aa78fd2",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:32:15.826Z",
+ "error": false,
+ "parts": [
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+ },
+ {
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+ "args": {
+ "cameras": [
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+ ]
+ },
+ "description": "locate block after slip"
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+ "error": false,
+ "parts": [
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+ "timestamp": "2026-10-28T21:34:21.081Z",
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+ "type": "image",
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+ }
+ ]
+ },
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+ "id": "5f69f64f",
+ "role": "assistant",
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+ "timestamp": "2026-10-28T21:34:27.096Z",
+ "error": false,
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+ "thinking": "**Measuring head bottom**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae26a5f9564819dbc0ccdb337a23517\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Measuring head bottom**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mpiLhDIDCSNj3dSi59Wm-wNBMEVyehv3JwpnzqB24RrOzwmFglf4rMDBq0ohLv16poiRY2MEWnhkpSrE9KDiA1hpAhynKkD3ujmNFean_J4UJwabI1uS_4cHG6mvfFEWbiKtmC2gxmKVM8bL3P4BTzGR8wvG09fs89s5R0Vqm32kLjv1x9hVZkfUC2mKWxdoUUGVeKwvLF9MFHwW9f4PHgXZvdVK-NCk7CVfFSY_pSNb6tMrbVA4kbmwya5K6tPWGjhOQEpCXYVhvboZuSa2RDYC1IoNlgcNccVyiVBxjF_ksfFZCkFWbH6Y0l51qKsYotswgtPhTWyFdw4XgUf9PWtvpt5a_J3HhLT2H45ONLyZkFeQEz-89VNc1idT2gTPGAmDqi_PQUtoDPzHpAEWCvNARVC3Ld4SBDQBfbZfHqWNmccVNrlOq8kSxskncI0iuZGyMbobtlx1eDEOaehhIRJxWBdfU2xep1heRu4tt0aZ6KI0tVpE8EGNd5a-CR9Sntvh7FFub_v_3X9K2RBDlAqXQmeXAoT86P2AOvWSf_MNbgfn-VkB6urh4gZazUUQwOVLeU6r-YPt7gCTz-vnJxj54JLinYWdycUaxm3BYptM7chCAD-rygl7pB0_f-vKevEX-pgjwyA0RgiCiAtkSvDSkcExVljZUIvQdWeV3QJ7Eee_WA72r9mCTZlGKoKq1t-Bdb7zY0yQG51GK6rNiHQXj5kiWIKp_I6MZ1_pZMTFqSkIEx6ZAMKaCaYw7Z6H7KxPQd_wPEofz-wdpR-C6tgS33lYcunHy7CVNINErLKbw3iePT4bNmT5f8yxhrQOebfpWxM0z7TJ-Qfj3Ta0Vy8bv6JhvYpvk8PHpxOS1TBRemGz2syVYkMiYFx7nCv_ULBzymOFPqMob__GCZeIo-9A1XdufF3o8Fj-I5-9W8bjs4nmvV8ilfm9HqO0QetWnTPGVpd6k9dlM70f3dmcoeFtmtv9zPJ3k4iN75Prnm9ZH8lk6Umh45jKYq5P_iFbEYlIS5gjAfkNXOeXKjqGLebxPMvyYT8H8kBSvtCgTjywUfFN1-BLjkMKqmAyfj56UrRQIiZilDq518FaIdu15u8hYGw-O1wMh1CFHKlfJffypV2LbGnhw_fneMmK3mOyXDUqnL8nJtIpj3utAt_Wiq0IX1TMKVW1OI-8SObINVryT_Wzs6qXtPrXrSNzJaEo3dFOXjaihcJfMIioP9pw5DbEMUSO5QUP-QUVArqUSCijvhmA3wuq1pJ7Kiob_iO_MQeG3FcMmtPPoq_LC5G0MKYVAJ6Vc0r6Z-xes_epyA5qqxwlTQce6bMjy_ccgOejmrfaq-szRvbpkJUWgHMV2VTmtFn0g51FYy6QeRgddQzWz4dfFb16J72GeOzrBCEtG-OvHtuW6CLYF-DKqT1hxzV-fkNG6UcI2cMHoAfOK0wxzwmU0ys_VJpraMpy66XOJ5_MPpoc1eg5e8zPIdfw9bLff_xedxe8_2qPGVKhY3xxxb1gQwiFo52GpxFYUC3Jrq_hFCUhQD4Wejsd406VZnjcrwwDBIrcXwMWbt1adBnrpZajGfMxLIESKPw477V5_T73iuvrvCHFRHLjrNtaBbToIDi1FymLe0WpfxkuqL_CD0U7KUuaHNKiSAkfj5R0laspH3TixTca7AUJb35D2sDbO3LcQLzuPESC4AEu5xKV9ooF2FvRt3aoAFSiz2HqsS1BQeL4URe4hRWnhLyD3YAk7BGtj2NNnI4Kcjhtk89cAbKztgbmidxvnbw-CMtq3p811vC1W4ykl8dJ-jvVZOUG9X5iDf1WfOwo2797DmeXUU4ak0TThI1_I4q2jELD65ru-KWYdQg2zfG--vZsVfCjYmsS4L6xwWtg5se5VYQXIu7A2C4HQNjZqbruQZRr7W8\"}"
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+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
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+ "description": "measure block offset in right grasp"
+ },
+ "call_id": "call_adac36b50ed2476dac845a7d3e1c6141|fc_0df8288370165955016ae26a610660819db7445f121efb0438"
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+ "tool": "exec",
+ "timestamp": "2026-10-28T21:34:30.162Z",
+ "error": false,
+ "parts": [
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+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223269.388614648] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"head_camera\": {\"red\":{\"min\":[-0.15821772589290822,-0.2987673906932839,0.8398380605979726],\"max\":[0.14645363087424962,0.06300409512308258,1.0602012979118725],\"median\":[-0.0769250015221273,0.06051332279327992,0.921461141233301],\"low\":[-0.07438347114092453,0.05827808110437249,0.8424585763634667],\"high\":[0.14441538763929712,-0.10189180637681439,1.055024763226523]},\"blue\":{\"min\":[0.06308362714636938,0.1010429531080218,0.742188561370138],\"max\":[0.16214894027171578,0.1994037568596595,0.7463403147189581],\"median\":[0.11265531983118941,0.14487610727830103,0.7460899470953907],\"low\":[0.11265531983118941,0.14487610727830103,0.7460899470953907],\"high\":[0.11265531983118941,0.14487610727830103,0.7460899470953907]}},\n \"file\": [\"/tmp/kinex-observation-u10oxgvz.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/c3226fa8-1.png"
+ }
+ ]
+ },
+ {
+ "id": "dc22e120",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:34:39.166Z",
+ "error": false,
+ "parts": [
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+ "thinking": "**Moving above the block**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0df8288370165955016ae26a68d010819da31e4ce374a8e708\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Moving above the block**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mpuea6n4OtlvUVbfOc2NX2AdacA11eE_GtQo1ONsBQzzbnxMq1jfU8MAmczFj-XwAkpLZpbG8mhHCjfCFgBOfFH_9rOHfTK8A6xot0q91okxdn2tCpGumFxi3-wI2ctXrdFEXgppJXEsBIvEAtHGvfOTGC1meqJt3VV7V-Y5x8UVnf-pyEuBmTGUOiwukc9LEglH9mTpqMGfpxngr9ZwZkz1BoI5S1Uwi9YeGtFrePAmOxWJkat_psfl6EvbpiAivazCx69a9NcGd1OCmL0Rotc5B52SQ3AaPXIW4ot9055s_zH0z2pSfzpmmWKFseEbceNDry-TBbEa19lxUWT11JpQqGCIRitH4GAO60oo3rr863wdOeC6prgOL8G7o2lAq9i9WoWfG-DBz-AN7KPudMbFKfG9Y6VG7RMOOZD9_4miJ3d31crYD4gV9mw3iUjhrJ6LvkDLfyMwW1NlWu23t6UuFha_P3N51ByZTwQ03y_bW4VSm4JZ5oJpyiMYsIw32tfTPaRsRiWFvQrv7P5XPl_OVM0ILt1zv7-Z0R_7sUs1VsI0pO4ZrgIpYLnI4MsSPcWS0hnTrGBki4k_Ypc-GVaVtXUlvS-ob0G0l3_cktQWLKnIGnXeYlpxjJHZv6VrxvXavjrfPU8LsnKOC3QHIdDABMKyDH5hVXSU5fwP7dffanErJgemg2ZsU9jDC5JL1tSzpFaAaeBEI8BzrCWaef6kSDG4pwLYyCrc1idAtopNEEblGU2L_5xpiXsdwP49owB1X7U83SzsTLyZ2GdmssEveV8iQNTBDinsXwlvv9wb6sOWcMpov7rkVczenCRouMjtW2IA-DgckgDEiEbV0XZGunNBZHBx-SV6lsw1O8TFV8_x6SwTx33lDSK4lsOIET1qmpSS5P03C9-id4y8G3MO1mDLXULLPZo3HMCbaDAG-SYEeHG-09kn2vrXFQP6NPlp_DEfgjfYZwys_1JBfRLrueZ7HSpvuh68RmArxhzg5vMVLNsC2DtC8ZwYgdghjlYf7IlFq7WEALxUzLglIrj1XMnVQN7hDn0Q4Uh891t3uCUh9ud-en9DLeCM5HelO13msIQ3-_sXiYCsCBOPvJ0CE8oaHhMyr-LoWopFpT4SL0dMOhdgQztQshh01292x65d__WYsM3eYdhsSpK4_qXpqCRxeahUGUheRAtnFff65dPudWIR1CCLFbuj7QXc2hi4GHVYdFjPMhshi5fncidqWMZCqmVuzMVUy-CcYP2iXgqYfnMLg8jjECXNJW7gqqy-yB4U2TvswDY45eAaSFrPr5vc9kR-C-57wSF92RyJG6GrnIRDUXBhwCc2dtlcWDNhBoEat0FkAF8RRy0eXT8GiJG9fvbna9Z51pnjjHAXbmkrWdDhE868pRxG0dOzEfOltNcnFOLmCqoOgngvNO6mDf8djPLX-bUf86M7n61J9yxuDv-6ShG4g4HT5ifop6mPe0Xv0dNM7_hL3EvDd4MvIhpZnweKW-3_pMSXJ_7zn076HR4Io7qB30aAzHtsbmudX1E-PDKg3yMzHB2iTaALCjBxLygYlOcyK7OzZkAmq7BBysBE2bGN69ZiV_gSqpUUpKCAM0_jVcy0wxqJK9VsboNmNWQxDNSUaI9xJjbe5yyegHbPWwoSU3T0c2UMGhUNAc2L-5n5569fIxHfspE-FlPcJ34Tp9yrSpuG5LNANXMRAJh1Nij4yqTEw5f6EVR4jEEQLTB3hafF7G6XBOeZnQjREgRt0IzFgooU5pw_vLZAmIUF8wEEzpFUcMUkgdS6oUDwr3fR5j98aqvvLZSjDpXP-JD2Zpz-QEdmdpKELJrx5tlNKx0E8P2DFmeG8qAHIa9RzFELRslnMgI70ioT82d08Ws65blS-UMBz7iH0npTQ36J9ffHwwkxrk72nErExd8erLWDba_6UTOTH9N1aP-TeTaLQGuC-mTVsRRSKrndlyoLMnHZjiS3FJU-WDFgL3ykwyGrmGCBZarFEQLvnf6W5GLk9uVAQrpzN26Rhz1rsZnJX1-pcs5By71Y7iD9XiTYQtZTkrZ-kP1VcET4FhzcJ85vuNygq63j5t1U9D0lE3bkNt36gllXRM5R3qBfOSfeLEVQFrwMGCse7D_9smia-a2lPmziXuNqLTr3CL0qu-RwrSYrF72svE3Ch324t2RlTY1Bb2wJW-NXmhLe5LmbRO0Zncd4Fxd0-zPNDZwyADuBCUj1jkVA0VfrC90RFqPmPb1toGgVY1mKS9QgHimxlUbVAyi9svpKkm1xkt3x_MqIEByj8C5vUxQJP3C1FRKPAuliqIpQvnPFvWQmSY5ITZOOPbtExAxkvcIrPg49z7la5gQwHiK6T6qP2fHmQG1ku-LnPqjt8ObiqCb51pIQs8q0nwRJCxCHXofZIiK-AM0PLFPGuVoZ9BiDUM9hDSEx06Fwl3juE4Iu_CmIvYS08xyFKpXwGl6xu8TTvWwq5hEnQcu7BFaOszs5IJ0gifwkXUMozwLfROpr5IPoj8vDonD6rFlTrROwgKFzonlz-kno6ok8bs6JmqKU8_m-R-vLG2YJRDwhvecDuLOapq1mb1upvSN5fm_Btu7pPBdp33qz6KHLNdd-DvEkaH0niUXro3Zv3cmCxh2fPAYugVvAhfx_EaN2FokNz0gsQxRIH8nubkrSFy6yKyNr2s0\"}"
+ },
+ {
+ "type": "text",
+ "text": "The block is now supported by the right gripper, with the left arm withdrawn. I’m placing it at the pad’s center and will verify the release.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0df8288370165955016ae26a6d4848819d92e39831a6de33f0\",\"phase\":\"commentary\"}"
+ },
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+ }
+ ]
+ },
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+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:34:56.718Z",
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+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "moves": {
+ "right": [
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+ 0,
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+ ]
+ ]
+ },
+ "seconds": 1,
+ "settle": 0.32
+ },
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+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/memos/handover-block.md",
+ "content": "# RoboTwin ALOHA handover block\n\nPublic interfaces: read harness.md and refreshed profiles. Native period .04s; 800 frames =32s. All movement needs sequential world.wait. Load arms, grippers, head camera and right wrist camera. Normalized grip 0 closed,1 open. TCP +.12m flange x. World arm base transforms are calibrated; use TF and URDF IK.\n\nReusable exec scripts:\n- `.kinex/tools/cartesian_move.py`: args moves={left/right:[world TCP poses xyz+xyzw]}, seconds per segment, grips, wait, settle, observe. Precomputes Cartesian interpolated IK then publishes JointTrajectory; returns measured TCP, q error and image. Kinex FK/IK requires list, not NumPy arrays.\n- `.kinex/tools/color_geometry.py`: args cameras; red/blue visible world surface bounds from synchronized RGBD and stamped TF. Bounds include silhouette/depth mismatches and red highlights; inspect images, use interior pixels if precision required. Wrist depth is unreliable inside .1m.\n\nSuccessful transfer geometry observed: vertical red block ~.06x.06x.20m, table z .74, pad top .746. Detect current xy each episode. Head camera clips tall block top. Pad center from min/max xy, not perspective-biased pixel median.\n\nGrasp LOW with left TCP at table+.045 (not +.095) using yaw +90deg quaternion [0,0,.70710678,.70710678], approach +world y, fingers close along x. Approach from y-.15 then insert center. Close .5s, lift .10m. Keep vertical; rolling a central grip caused a slip.\nRight approaches from +world x with yaw pi quaternion [0,0,1,0], closes along y. Target ~.03 below measured block top, ~.12-.13 above left TCP. Too little separation (~.07-.08) caused collision with left wrist/camera and displaced the block; stop before recovery. Lower left grasp fixed it. Right camera gives useful top and side geometry before insertion.\nClose right .6s, open left .44s, withdraw left frontward ~.17m; verify block remains suspended with right (grip ~.75 for .06m block). Then translate above pad center, lower upright preserving grip offset, open right. In this run transfer and pad placement observed; release wait terminated at 24.84s after .04s, before requested .8s. Last measured right opening .761, velocity positive; full-open motion not verified. Native verdict remains owner-only. Never retry world waits after terminal or infer success merely from termination.\n"
+ },
+ "call_id": "call_9777e5a5cde145f7bb58fc5722c35986|fc_0df8288370165955016ae26ab42140819da786d33d904a69af"
+ }
+ ]
+ },
+ {
+ "id": "322916b3",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:36:07.940Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/memos/handover-block.md"
+ }
+ ]
+ },
+ {
+ "id": "3824164a",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:12.040Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Transferred the block to the right arm and placed it on the blue pad. Commanded the right gripper open, but the episode ended during release, so full opening wasn’t verified.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0df8288370165955016ae26acab3fc819d8b81285de4d79e70\",\"phase\":\"final_answer\"}"
+ }
+ ]
+ }
+]
diff --git a/experiments/robotwin-native/kinex-1/usage.json b/experiments/robotwin-native/kinex-1/usage.json
new file mode 100644
index 0000000000000000000000000000000000000000..da8540887f97daa54ad75e94cf5a3c11e85bf77f
--- /dev/null
+++ b/experiments/robotwin-native/kinex-1/usage.json
@@ -0,0 +1,428 @@
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diff --git a/experiments/robotwin-native/kinex-1/vla-io.json b/experiments/robotwin-native/kinex-1/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..250d7787ec0f8bfa2091df6ed87e28970cb2b3d2
--- /dev/null
+++ b/experiments/robotwin-native/kinex-1/vla-io.json
@@ -0,0 +1,43 @@
+{
+ "calls": [],
+ "coverage": {
+ "recorded_inputs": 0,
+ "recorded_outputs": 0,
+ "kinex_calls_associated": 0,
+ "original_temporary_image_paths_recorded": false,
+ "normalized_action_tensor_recorded": false,
+ "processor_tensors_recorded": false
+ },
+ "contract": {
+ "request": "policy.infer(obs, task). obs contains three ordered RGB image files; no joint state or agent conversation is sent to the VLA.",
+ "image_preprocessing": "RGB conversion, then OpenCV INTER_AREA resize to 224 x 224. Model images shown here are reconstructed from retained input pixels with the executed preprocessing.",
+ "request_paths": "The logger replaced temporary input filenames with retained image-copy paths. Original temporary path strings were not retained.",
+ "service_response": "actions, inference_s and call_id are reconstructed exactly from the logged values and the executed handler return. raw_actions is internal diagnostic data and is not returned to Kinex.",
+ "agent_response": "Kinex helpers.run_policy consumes the action array and returns actions_submitted, duration_s and ik_failure. The language agent sees the exec tool result below, including feedback and images selected by its own code.",
+ "output_layout": [
+ "left_joint_1",
+ "left_joint_2",
+ "left_joint_3",
+ "left_joint_4",
+ "left_joint_5",
+ "left_joint_6",
+ "left_gripper",
+ "right_joint_1",
+ "right_joint_2",
+ "right_joint_3",
+ "right_joint_4",
+ "right_joint_5",
+ "right_joint_6",
+ "right_gripper"
+ ],
+ "diagnostic_layout": "Left 6 joints, right 6 joints, left opening, right opening. Gripper conversion: 1 - 2 * clip(opening, 0, 1).",
+ "not_recorded": [
+ "normalized action tensor before denormalization",
+ "backbone processor tensors",
+ "exact original temporary filename strings"
+ ],
+ "backbone_prompt": "Reconstructed from the executed QwenOFT and QWen3 implementations; 16 action query markers are appended by the model, not by Kinex.",
+ "model_metadata": null,
+ "executed_sources": "policy-contract/sources.json"
+ }
+}
diff --git a/experiments/robotwin-native/kinex-2/analysis.json b/experiments/robotwin-native/kinex-2/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..173c7424b55dc703beef2dfd0a9d4fa543647d4a
--- /dev/null
+++ b/experiments/robotwin-native/kinex-2/analysis.json
@@ -0,0 +1,3 @@
+{
+ "observed": "Kinex reconstructed the shoes and box from RGB-D, wrote a reusable dual-arm motion tool, and staged the grasps, rotations and placements. Native success occurred at frame 337 during final release."
+}
diff --git a/experiments/robotwin-native/kinex-2/artifact-index.json b/experiments/robotwin-native/kinex-2/artifact-index.json
new file mode 100644
index 0000000000000000000000000000000000000000..7020d7b59f2d2904f15726291079e843831dddc8
--- /dev/null
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+ "sha256": "bbd68386e6b1360de4e802262dbddeeeeca6220e0abfaca9ad2754d8a1ba359e"
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+ "path": "experiments/robotwin-native/kinex-2/workspace.tar.gz",
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+ "sha256": "71314c04c838ff7fa9b7717be16d80887bfd5c3c35d259c94c6c7a2f70450a81"
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diff --git a/experiments/robotwin-native/kinex-2/detail.json b/experiments/robotwin-native/kinex-2/detail.json
index ce903fc3db50fff7fea2bfa8ae0e9346efb1de5d..8170570bffe5b59cf47883ab2f4627c2e92c2e33 100644
--- a/experiments/robotwin-native/kinex-2/detail.json
+++ b/experiments/robotwin-native/kinex-2/detail.json
@@ -292,8 +292,14 @@
"usage_source": "provider-raw"
},
"cost_note": "API equivalent sums the native Pi session cost estimates. Subscription billing is not reported.",
- "media_note": "All three native views and every frame retained. Frame timing is unchanged; playback starts at zero.",
+ "media_note": "Three 960 x 720 views side by side; every native sample once at 4x simulation speed.",
"artifacts": [
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+ "path": "experiments/robotwin-native/kinex-2/analysis.json",
+ "bytes": 217,
+ "sha256": "513dd587eab60fc5ea6c7639536d8c28038c0bdd355dad8b08b18717402e2189"
+ },
{
"name": "artifacts.json",
"path": "experiments/robotwin-native/kinex-2/artifacts.json",
@@ -420,6 +426,60 @@
"bytes": 27425,
"sha256": "9ed95bdb74b07353de2d3dcb7504e31e5ac36192966d15676fda7c505945b514"
},
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+ "path": "experiments/robotwin-native/kinex-2/presentation/encode.log",
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+ "sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"
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+ "path": "experiments/robotwin-native/kinex-2/presentation/frame-mapping.json",
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+ "sha256": "e732646face25f676a36a5310f2971838e063d50a5e4a528d2c77fa5da55e723"
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+ "path": "experiments/robotwin-native/kinex-2/presentation/media-validation.json",
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+ "sha256": "48581642441de6d895b4eb1e292d85cec2203383f939a3b30a8bd2dfaf08413c"
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+ "sha256": "054a62dff2660b0539cdd0ccd85a27481b0915c22e4d73a7665aec52466982b5"
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+ "path": "experiments/robotwin-native/kinex-2/presentation/recording.json",
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+ "sha256": "922ab146099d0503337e437634b85b03a6610afa182691183b44dcc0930c6389"
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+ "sha256": "c38bff140c1928f07ee061e0d93265e027f5ca044f6d0777ef9f48aebb0ecfa4"
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+ "path": "experiments/robotwin-native/kinex-2/presentation/video.mp4",
+ "bytes": 3737529,
+ "sha256": "3311871fad3acde83e150af9b580ee59942654e52f56636545ca6b6b085e636d"
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+ "sha256": "122ff28f9b10400f178d95015c443b73fcdd4046df29c1c9003e4ca9dfdb4551"
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{
"name": "provider-requests.jsonl",
"path": "experiments/robotwin-native/kinex-2/provider-requests.jsonl",
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+ "sha256": "113500cbd48b6bd86f6fec6370a9a428c954354bfba3f6ca7b1e3b7e88d98046"
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"bytes": 7438,
"sha256": "ab08002f929415f5870eacd66548fe357f729d9e35d5536cfe059dd363ad4859"
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"name": "workspace/.kinex/devices/head_camera/profile.yaml",
"path": "experiments/robotwin-native/kinex-2/workspace/.kinex/devices/head_camera/profile.yaml",
diff --git a/experiments/robotwin-native/kinex-2/presentation/encode.log b/experiments/robotwin-native/kinex-2/presentation/encode.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/experiments/robotwin-native/kinex-2/presentation/frame-comparison.jsonl b/experiments/robotwin-native/kinex-2/presentation/frame-comparison.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..8a3aa3ad96493d0762005f9c25eb1c40a8d6a723
--- /dev/null
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index 0000000000000000000000000000000000000000..071b6832aefc953d84af1954686556d95efd8d6c
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index 0000000000000000000000000000000000000000..1b280b43050414cf1ec531ccd2eec17b70959ac7
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+ "output_fps": 40,
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+ "maximum_frame_rgb_mae": 1.6074283123016357,
+ "decode_ok": true,
+ "pts_verified": true,
+ "playback_kind": "simulation_time",
+ "resolution_kind": "independent_720_high",
+ "agent_observation_video": false,
+ "camera_views": [
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+ "name": "third_person",
+ "width": 960,
+ "height": 720,
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+ "coverage_basis": "Every scheduled 10 Hz control-boundary sample, plus the terminal state.",
+ "frame_mapping": "Each captured sample exactly once; no appended or held frames.",
+ "sampling_note": "Samples follow the native simulation clock; model thinking adds no footage.",
+ "scope": "Live owner-only spectator views; no replay, rerender, upscaling or invented frames.",
+ "recording": {
+ "schema": "rosbridge/recording/1",
+ "run_id": "456c61025989",
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+ ],
+ "fps": 10.0,
+ "topics": [],
+ "error": null,
+ "bag_messages": 0
+ }
+}
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diff --git a/experiments/robotwin-native/kinex-2/protocol.json b/experiments/robotwin-native/kinex-2/protocol.json
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+{
+ "max_steps": 600,
+ "seed": 0,
+ "episodes": 1,
+ "control_frequency_hz": 25,
+ "provider": "rosbridge",
+ "realtime": false,
+ "stop_on_success": true
+}
diff --git a/experiments/robotwin-native/kinex-2/transcript.json b/experiments/robotwin-native/kinex-2/transcript.json
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+[
+ {
+ "id": "2624d288",
+ "role": "system",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:27.076Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ""
+ }
+ ]
+ },
+ {
+ "id": "0493caf2",
+ "role": "user",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:27.076Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "# Task: robotwin/place-dual-shoes-aloha-agilex\n\nuse both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open\n\n## Work to do\n\nSolve the task efficiently using the running rosbridge environment. Follow the\ntask instruction above, including its completion requirements. Read `harness.md`\nand the device profiles for public interfaces, units and calibrated frames.\nReuse your saved tools, skills, and memos.\n\n## Limits\n\nYou have 600 native action frames. The execution mode is `stepped`: physics is\nfrozen while idle. Use `world.wait` with `duration_s` to advance the native clock.\nJoint targets are ROS JointTrajectory messages; gripper targets use the units\ndeclared in their profiles. Reads and command publication do not advance physics.\nWaits are sequential; concurrent waits are rejected. A command or elapsed time\ndoes not prove arrival; inspect measured feedback. Device stop holds the device\nwithout ending the episode. The safety timeout is 28800 seconds.\nDo not launch or reset a simulation.\n\n## Completion\n\nReturn when finished. The owner finalizes the episode and reads its native\nverdict. An interrupted or rejected wait does not establish task success. The\nnative step limit stops physics even if your requested wait is longer.\n\n## Saved resources\n\nMaintain reusable code in `.kinex/tools/`, skills in `.kinex/skills/`, and concise working notes\nin `.kinex/memos/`. Improve existing files in place as you learn, replacing outdated\ncontent. Create a new file only when no existing resource fits; do not create\nper-attempt reflections or numbered copies. These files persist across fresh\nconversations. Update them before finishing your response.\n\n## Robot and device access\n\nUse Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place."
+ }
+ ]
+ },
+ {
+ "id": "c292d17d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:29.943Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "harness.md",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_367e99d2533843ab8b2927f77681118b|fc_0e05b35c94578fcb016ae26b55808c819199906d0ce7db8551"
+ }
+ ]
+ },
+ {
+ "id": "4e139be9",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:29.951Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Use Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place.\n"
+ }
+ ]
+ },
+ {
+ "id": "c61aa38e",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:32.445Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "ls",
+ "input": {
+ "path": ".kinex"
+ },
+ "call_id": "call_7ce3085100fd420dbb7436140ec43e28|fc_0e05b35c94578fcb016ae26b57d6788191b2062cc3c6a54dd6"
+ }
+ ]
+ },
+ {
+ "id": "7266cd3b",
+ "role": "toolResult",
+ "tool": "ls",
+ "timestamp": "2026-10-28T21:38:32.449Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "devices/\nkinex.json\nmemos/\npython/\nskills/\ntools/\nworkspace.yaml"
+ }
+ ]
+ },
+ {
+ "id": "cbd2c355",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:35.253Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "bash",
+ "input": {
+ "command": "find .kinex/devices .kinex/tools .kinex/skills .kinex/memos -maxdepth 3 -type f",
+ "timeout": null
+ },
+ "call_id": "call_267b6ee82c144a20a1f2c3245704c3a6|fc_0e05b35c94578fcb016ae26b5a73808191abbc02c144259293"
+ }
+ ]
+ },
+ {
+ "id": "1467eccb",
+ "role": "toolResult",
+ "tool": "bash",
+ "timestamp": "2026-10-28T21:38:35.269Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ".kinex/devices/left_arm/links.py\n.kinex/devices/left_arm/arm.urdf\n.kinex/devices/left_arm/profile.yaml\n.kinex/devices/right_camera/profile.yaml\n.kinex/devices/left_gripper/links.py\n.kinex/devices/left_gripper/profile.yaml\n.kinex/devices/left_gripper/gripper.urdf\n.kinex/devices/right_arm/links.py\n.kinex/devices/right_arm/arm.urdf\n.kinex/devices/right_arm/profile.yaml\n.kinex/devices/left_camera/profile.yaml\n.kinex/devices/head_camera/profile.yaml\n.kinex/devices/right_gripper/links.py\n.kinex/devices/right_gripper/profile.yaml\n.kinex/devices/right_gripper/gripper.urdf\n.kinex/devices/world/profile.yaml\n"
+ }
+ ]
+ },
+ {
+ "id": "9962d2a6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:37.160Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/world/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_a523247bf39b433e98fc113a09b276d5|fc_0e05b35c94578fcb016ae26b5cb7f881919f83c987b965d722"
+ }
+ ]
+ },
+ {
+ "id": "a56669e5",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:37.164Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: world\nruntime:\n domain_id: 83\n observation: time\n nodes: []\n ready_timeout_s: 30\noperations:\n time:\n description: Authoritative world clock\n transport: topic\n direction: output\n endpoint: /clock\n type: rosgraph_msgs/msg/Clock\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n wait:\n description: Advance or await duration_s of world time (finite and nonnegative).\n Zero is an observation barrier. Waits are sequential; one requested while another\n is pending is rejected. A terminal episode rejects further progression without\n exposing benchmark results.\n transport: service\n direction: input\n endpoint: /world/wait\n type: kinex_interfaces/srv/Wait\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 120\n stop:\n description: Cancel the pending wait.\n transport: service\n direction: input\n endpoint: /world/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: world\ndescription: Scene reference and authoritative world clock of the RoboTwin 2.0 table.\n Kinex supplies frame transforms independently. This device exposes no task instructions\n or evaluator results.\nsource: default\ncalibrated_at: null\nmethod: unknown\nbounds: null\nsurfaces: []\nframes:\n base:\n parent: null\n translation_m: null\n rotation_xyzw: null\n"
+ }
+ ]
+ },
+ {
+ "id": "8539a895",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:41.459Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_arm/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_4cceb880d6784989bd7c305d425d4dfa|fc_0e05b35c94578fcb016ae26b5f6d248191a72c4e3a2ad19716"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/right_arm/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_0ac1df91f68e4f75a427082873c0a21e|fc_0e05b35c94578fcb016ae26b615f4c8191b9d12716aaffa541"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_gripper/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_e23d1a1ce4e3491598e87028dbbe8b60|fc_0e05b35c94578fcb016ae26b615f4c8191b6a76c2b250df9eb"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/right_gripper/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_57217fff6fb842a2ba2ebf0be8d60587|fc_0e05b35c94578fcb016ae26b615f4c81918138bbfb49b2064e"
+ },
+ {
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+ "name": "read",
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+ "offset": null,
+ "limit": null
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+ "call_id": "call_cea94425e2fa4e5f85a2ed68057a9bdd|fc_0e05b35c94578fcb016ae26b615f4c8191a3b10ce3816ee991"
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+ "limit": null
+ },
+ "call_id": "call_e6b73f775a6747bd9a935378ace8ee6f|fc_0e05b35c94578fcb016ae26b615f4c8191b0a29903d0af9be0"
+ }
+ ]
+ },
+ {
+ "id": "fff103a2",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:41.465Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: left_arm\nruntime:\n domain_id: 83\n nodes:\n - entry: links.py\n factory: create\n ready_timeout_s: 30\noperations:\n joint_state:\n description: Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4,\n fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition\n stamp; do not infer motion completion from a sent command.\n transport: topic\n direction: output\n endpoint: /left_arm/joint_state\n type: sensor_msgs/msg/JointState\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n joint_target:\n description: Joint trajectory over all 6 arm joints in radians, timed from receipt\n by strictly increasing time_from_start and finishing within 120 seconds; velocities,\n accelerations and effort must be empty. A zero header stamp selects now; a nonzero\n stamp must not start in the past. Points are absolute native joint positions,\n linearly interpolated at the native control period. Replacement clears pending\n references; invalid trajectories are ignored, so verify measured joint_state.\n transport: topic\n direction: input\n endpoint: /left_arm/joint_target\n type: trajectory_msgs/msg/JointTrajectory\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n stop:\n description: Stop arm motion and hold the measured posture.\n transport: service\n direction: input\n endpoint: /left_arm/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: joint\ndescription: ARX5 six-joint left arm of the RoboTwin ALOHA AgileX. Geometry is the\n sibling arm.urdf with flange (fl_link6) as the tip link; measured links are on TF\n as left_arm/\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "36b3b3e8",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:06.893Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Inspecting shoe-box kinematics**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26b776a6c8191a11f9f6e5ce53643\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Inspecting shoe-box kinematics**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mt6vnYRDQBwuQJIVH78P8WOrs8Lkjm2f3UMxpeSOs03nIaFBa86aGG-POQCENWnik760a9SjNLRP22DW7_GWqPOJuQ0RsSBErV122y0oY99XwTN0AAkE1R5wMNOkv5SoKrNcDh5ooUc_RaHM6bSI_zLKmCtiUszHvMu6wDru4Xay4pvzH3ERBgHnpJzTMDwitpnWvuTB05RWxfEzrhh8CiLvbPT8aaudh0NcOSb97pmKob0iutdMWQLfJ-dt4LB5hE75rl4HrYjwvEObRy88lFgWb4VCKa8-w6rcFF6q2HLlzisHq3xvTWo5UsoTjVl_3fuY_O7vIvZOEOVKyxIU4kxCOZ264Yp5WlIvB3GEL74BZsL34QleTkz-PKlSLLG3s2JgrpCISgtW7uiqrEbolcpvERDnrKQqX9FsEIkg9clqTWryXrgaDet3wM0GUtvxQ3ANBMHhUQDeXS7gRwdK5rDmY5O6ajm8TZu8LO92soahplmYu28fEhdCvNO7A1WUOnu5csYXLJXTqXCTaEEt-RvjOWqk9U6XUBcXMHOBpnYNw_Z8zlJtSFs7LLb2zLCioDqevJ4t8b0v_iVigjROJRKKgULpdz8B8VrxzzIaKGUF1Y_xhVt3WZOXx7Omu75SGBuSwCtHaL7jVBVvyKO5ev_m7IZxD2i1rIFoOzSXm9Ymmx0phBB-ESKNTZO3agbxTDvn07HhQrXjYWpQpCaSZkT0RrUt9dbitYr3pbcibcmfTZnV_v1Yk8nnb8i-Q-vzfoUMSTAsdux4SxKyBK74AJN_PPiIh7DDKAiUREX0u-psWaWKxewQSVoBV8DeDhR3H8fhFqM14gjsFLZHMDB7yPNKzF_n7mCnbPKxmHMhJxeIJCHLtWbO_KhdORg7w0TxFGG94jROVbvgqVENVN5dD53QrQJNhPMCqZZ4CR4hKnZJerMoAZU1Zq4rmDgYkXs8snxuAfhbFthkwp0FJ02l8nmK3FPgOCwdoxkEb94r2NDv9edwhBiLi4kksEScdfrYKP3xqik7u_8Ft7dFhV7I_Q41PDuxpplmSuybvGSFjJNBR2SshmHhiO2bqKwThZ3cxVBa5bFrs7p5K-6I5fKCWSp_FP8waxE6YOzMQiX8ZO0HXkyh2Ujyh6Dr0sIEHQ7xP3VAtAqzYibR4AIYwdweAK0zhDPNF8l4xzDOIa_4JX8GIC4Lt_PTZlW3fvi8-E4hGa8NesYxMwF_ao0T6EQys8T21d7zvUESRPT-LZbwJLizypsrVKW8nz0uJkXGQVVkWnrVxsV-KlVQ80pxXYi9yj-LzzUcP6iQ0Lczp2ulgsWBorQDI7H30XlS_RT8Cx6tnECQwWzUpMoFngJunTCcih0JXGZAq67kj4XRKm_ZdKMl9p7m3Ys9sITq0PouFsrrNUEWifOl7-PBbSPScpCcqAW_THxWEwa_dm347GcXVmBy-0XYz-62Hbczzer7IFLr06gk2LHKjoz7pg7xcvNtUZjO0dtDsJX3JS43qOjzQEpyYgm9FX8ECijfUumvL2dp1pmX4qASvNeP9kTJNLmFawcM8IoWOpMsceK0FpsHufIQsDBFjbktlwKnAAziFQxhVK1POUs0T8ytJYZoFdK-4FbpOn0yrt-cpSMa5a8fVK_utJwIxDubJ006nHzX44N2ETq6A87CJUK9R53XTqYvW85ZtsMv-RfHU-sUQ57xUSHva9l-myQcKPvw0_Gd5B3yID57HVWSQGO_jKh6FjfFCLLkWJi1rvN3hv01_RyvD88jyheSx6Ys0DIGjHupVQvg49pNs76FMHPZdjzQsCbPki73m2i4IQF6nbKGkq9KGDmYbpAsJirVYUmhxJH3kd0WkPAYA3CAeRHNp93Xv6eGDWPWeQm8SGHiUL7S-D4rmi3l4q2_ic9-I55_GtxwLzlgrES7096T0o2cEyNWdrtFhz1a55AbhyCbPV0lsiPjqpS-mU=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/kinematics.py",
+ "offset": 1,
+ "limit": 300
+ },
+ "call_id": "call_33489e3730f749d496ec9b7b34d2fca5|fc_0e05b35c94578fcb016ae26b7ac83481919db7af8831435ab4"
+ }
+ ]
+ },
+ {
+ "id": "ed5f7847",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:39:06.897Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Joint device kinematics from the device's resolved URDF.\"\"\"\n\nfrom kinex import profile\nfrom kinex.lib.joints import JointModel\n\n\ndef joint_model(device):\n \"\"\"Load a joint device's model without device I/O.\n\n joints lists the commanded joints in URDF document order with limits and\n rate limits; names holds their names. fk(positions, link=None) returns the\n link pose [x, y, z, qx, qy, qz, qw] in /base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 14, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 8, in main\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/joints.py\\\", line 41, in fk\\n q = joint_target(positions, self.joints, check_limits=False)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/urdf.py\\\", line 114, in joint_target\\n vector(value, len(joints), \\\"joint target\\\")\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/geometry.py\\\", line 19, in vector\\n raise ValueError(f\\\"{name} needs {size} numbers\\\")\\nValueError: joint target needs 6 numbers\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "6b962d6d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:26.606Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import asyncio\nfrom kinex import runtime,helpers,communication,finish\nasync def main():\n async with communication() as io:\n data={}\n for d in ['left_arm','right_arm']:\n async with io.subscribe(d+'.joint_state') as s: m=await s.next(timeout_s=10)\n q=list(m.position)\n data[d]={'state':m,'fk':helpers.joint_model(d).fk(q),'tcp':await helpers.relative_pose(io,{'frame':d.replace('arm','gripper')+':tcp'},{'frame':'world:base'})}\n f=await helpers.camera_frame(io,'head_camera')\n import numpy as np\n np.savez('/tmp/head.npz',rgb=helpers.image_array(f['image']),depth=helpers.image_array(f['depth']))\n data['schemas']={op:runtime.describe(op) for op in ['left_arm.joint_target','right_arm.joint_target','left_gripper.target','right_gripper.target','world.wait']}\n finish(data)\nasyncio.run(main())",
+ "description": "measure initial scene"
+ },
+ "call_id": "call_ebc53b54c9144398add4c4510616f6fe|fc_0e05b35c94578fcb016ae26b8ba19881918312f9fe01c977d2"
+ }
+ ]
+ },
+ {
+ "id": "175a61e9",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:29.070Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223568.172439105] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"Traceback (most recent call last):\\n File \\\"\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 15, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 12, in main\\nTypeError: tuple indices must be integers or slices, not str\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "1573d9c6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:31.726Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
+ "offset": 1,
+ "limit": 220
+ },
+ "call_id": "call_c2b8d5d34932451c817efe51bdba851d|fc_0e05b35c94578fcb016ae26b9318f08191b9765db7a8ffc3d7"
+ }
+ ]
+ },
+ {
+ "id": "74e73206",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:39:31.730Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "d7788a05",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:37.269Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import asyncio\nfrom kinex import runtime,helpers,communication,finish\nasync def main():\n async with communication() as io:\n data={}\n for d in ['left_arm','right_arm']:\n async with io.subscribe(d+'.joint_state') as s: m=await s.next(timeout_s=10)\n data[d]={'state':m,'fk':helpers.joint_model(d).fk(list(m.position)),'tcp':await helpers.relative_pose(io,{'frame':d.replace('arm','gripper')+':tcp'},{'frame':'world:base'})}\n im,dep=await helpers.camera_frame(io,'head_camera')\n import numpy as np\n np.savez('/tmp/head.npz',rgb=helpers.image_array(im),depth=helpers.image_array(dep))\n data['schemas']={op:runtime.describe(op) for op in ['left_arm.joint_target','right_arm.joint_target','left_gripper.target','right_gripper.target','world.wait']}\n finish(data)\nasyncio.run(main())",
+ "description": "measure initial scene"
+ },
+ "call_id": "call_90dc0d2cd0e74d118298a624ddad2d76|fc_0e05b35c94578fcb016ae26b967e8c81919e4629fbd557a833"
+ }
+ ]
+ },
+ {
+ "id": "20d81030",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:39.212Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223578.614148509] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"left_arm\": {\"state\":{\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"fl_joint1\",\"fl_joint2\",\"fl_joint3\",\"fl_joint4\",\"fl_joint5\",\"fl_joint6\"],\"position\":[-3.016615224282759e-8,-5.666987590302597e-7,-0.000004835828804061748,7.701128623693876e-8,4.63164752773082e-7,-8.158995683515968e-7],\"velocity\":[0.00000265039443547721,-0.000010050378477899358,0.000024748725991230458,-0.000004255349267623387,-0.00001595680987520609,0.00007239235128508881],\"effort\":[]},\"fk\":[0.1056935554023861,-0.0011901315627094447,0.15999839199046592,-0.000007715996484952103,0.0000021542621098628648,-2.4666643061721644e-7,0.9999999999678809],\"tcp\":{\"pose\":[-0.30032357671522697,-0.193827798419468,0.9419981020126762,-0.000006960933310190554,-0.00000395167326060435,0.7141423608015681,0.7000004917460364],\"timestamp\":0}},\n \"right_arm\": {\"state\":{\"header\":{\"stamp\":{\"sec\":0,\"nanosec\":0},\"frame_id\":\"\"},\"name\":[\"fr_joint1\",\"fr_joint2\",\"fr_joint3\",\"fr_joint4\",\"fr_joint5\",\"fr_joint6\"],\"position\":[-3.258066882949606e-8,-5.65274206110189e-7,-0.000004838918357563671,7.693390813301448e-8,4.6469963876916154e-7,-8.163781899384048e-7],\"velocity\":[0.0000026605034690874163,-0.00001006854472507257,0.000024771599782980047,-0.000004258563421899453,-0.00001595234061824158,0.00007239227852551267],\"effort\":[]},\"fk\":[0.10569355567032844,-0.0011901318683733137,0.15999839080293787,-0.000007716210574917094,0.0000021565576609891396,-2.4864112524367e-7,0.9999999999678738],\"tcp\":{\"pose\":[0.30523323124039986,-0.1928057309036048,0.9409978556569187,-0.000007012336903923293,-0.000003885552193758481,0.710633293626997,0.7035625927553112],\"timestamp\":0}},\n \"schemas\": {\"left_arm.joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"joint_names\":\"sequence\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"right_arm.joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/right_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"joint_names\":\"sequence\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"left_gripper.target\":{\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\"right_gripper.target\":{\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/right_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\"world.wait\":{\"description\":\"Advance or await duration_s of world time (finite and nonnegative). Zero is an observation barrier. Waits are sequential; one requested while another is pending is rejected. A terminal episode rejects further progression without exposing benchmark results.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/world/wait\",\"type\":\"kinex_interfaces/srv/Wait\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"duration_s\":\"double\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"time_s\":\"double\",\"waited_s\":\"double\"},\"definitions\":{}}}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "0c9864a9",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:51.107Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Estimating shoe 3D points**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26b9df59881919df1efdf584f4c66\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Estimating shoe 3D points**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mukxVEV_WwTGJOtSMONVrD6qERYmMQEzEB-28fe46bXYqR_7gsWTWnaI8oaOA7bCRzznxqoSkmskmkpbRo1l2Dw2AkaOzyqwysL-ACcApzeIocD9kacb5kn1Rlbe26pSkapeIIkXaL--4FVj0PFqR2_LRlmPgh52H4HfJEovCp-RYdPM0vSF0lYI0aQkFrp4Cii9BK7ytE0uRD7j8fyYvV-32VPutRzlCzsUCapdIJ2HrGUwNi08k0aFodRElW9Q-gplnCvwM1QVeovtdOPB3U5qmxX3KPwy4SDpNkNrXtXG846n-owte_XtMIq992GEEBLs6tphdHVc9PJHBherbp-b-TGCG2uUIUrrG1UY6P226tPkr2bW98Ezgn_W2Kl56K5UPK21J5NN-CaB9oCCOtJN8MX2Jtgfaqq32k4IT0bHPkB_zMqsurqhg3RCaplaPTAeurP1BvrNmXBtheYJVFmWoTDV4fTXN2TZsxgdb5Pl55Ys0hliIMRbNWjPyLNEfQbiqJ-v56YVergFNaC53wW-tMLRNL7r6Xf9qr_Oi12LgMGvQZvu5ZUfhs881F2HKQcuPrnA50FbLMhcbzYUxt9qbnW7jirXeKl9vXUnt_QIIHvMPTgFrMzmSk2wyPxnlmTG6B2YnNU09qQL9sFahtm60Kn4jxAZj_YUgxNMkcwoBp6zirBjfQb5W3hKyLAq92xBxQnUG7NK0K_WUFXWffrnerO0yI5d70By4kR7EjA2kLhblFjdreBMfkRpsaS45i0qXLVPCoXaCAwaJOm0oso-YMqL7DRr1Y2KZKac3OyLZtWxG7WJwdWxEBDPOVzZYYX1HkW--08a0cvpwzNPh___xbP3-NwRyLGbhCtv-Yr7WqxTZVI_UwlBXonsBo91dE5nxd9jWwbAITIUZ3gNXMGJfZRMevxOsHj_e2Lw3QT1_7hHlM6CImbI3riDvXYyzzkdwgFsjRGEx4DUDq2JZof0L6zwzbN9p-oKFw7Sm8G26FFPK5G3i1CcbXYpbi4qxhzAsOTtk5ExFd1U5YBlWILxHMiEdZTBqfKvKDSGzkN2yl1Vf_r32OTRjWsq78Z8pAdMAmLqV8KM_PouhuaGgK_OWotb_9m2NGXgWWHyFk7ApwnTVjmAMNvmPjD6JBmxMzFY6xf1bjaiwwZMk0knsOyzdDXNYYLRrmCOFUtGl-sMlvtVEfRMVndC_stPg0KtCFmZ3Hk914TMNn06uws3yocIrNCT6tRCWdHddleZSoelFTGopj_h2IFLO_MSRvcm9mSj8OVTZZL0eEXrzo40M1lvcu2zTQa7tHZrtfV5SS4s2y4Z2oj6efjyz3xCLzGAxST327xJUFeatjl3Wguwi6leVOia1vBK3xKdItAqedkHZ3YwRMMWVqaRGIB8amxgAAPtDcqHrCQpMWHI4zR-YWJdviflZeG4XgvzsZJwrZH8F-ChwIc1Ag8tWjKOPIreK8wcxRCPNB5PADyKGbZa70l0fxNY1wPwDF29Wr4Kow_HI4F61CDJN74MvsRc-XJ5poadMzkytg2ACymWHZdVw_MeRtAXIRtSBPWrwO6lKS7pITEFdbcF2OeklNC13CMON9g8DfJ0oWBoRQNHhoEVMMkmODG5wRRbLoaTDvTKAmGLpc4_Dwu90wpyOe7FQfc2LQPPeJPDvvJ0nYKS3qr87xA8SYYkGHlaReMAK022g_6muvP0NSbQPXFXF5byzGkiiSiJKNZ_GbdecXevaC-UioxUZmKb41w7CNsMR9HoiQ8l0AHLVzqdLJuAQq1e_BrPz-g5BTGFUCi9VvpU6vAMQc366IXu7etBnSZRPH3lwb1sUOnfy9Xaz6H8PpHms3_NKxHmc2d5IN6unCqKQQexegqZNSyRVJup_vcRzqoJyilLUwbbpiOVli8TCyw3ZeJxsqIlOTeQmJyL-S2Ie-_R2QCRY4uXCTE9fodabd7ulWDR_t7R4a8DPe7fo46L0Anvdw2kLoi9dEey7aA2KQ3c-5WTVN9iAeuTba6nZDZJzX1oLO4aXss498Y4YNX8_WTacTqz7ExXq5zYETEWDeLP4Eliz-7q22YkOqUhXEhzWHM4bAeArtK0jlUj-Pn9cdL1fd5Buu-Tx66dglfs-0JGCAy_mf1F1qA73YKFwGFtZdvett78KEuwk2pomNMO-Ebg2L_MC2BAMG7j0aZpb2te8Ezbmh0L71AjhmfNdxWtxDoF4YAGTO1fpFWZLY0XvH9eGtdQLsNiHRn-vBkliXm0MaaXNe2B45VW9TnXiU3seeofmsFRh8rceVDBlsIhp-3Iit8p1K4Qh9D6bUhy_QCWXooZCKK_LmW8ZZDKODRaqhey3w9Ei99zM4mXPK4Uw5R7AvcnZMchsKxaLMhUrEsjtcGKB6lG9LZ82WQ3BBe6fTHQ6_rHpzTsXKkygqWAWC8t6Y2GMZTU6THkCJvo_1zjY6XsnxDETa9bOw2xIDhcn9T0_5FD9NUwXUN35rh-kZxnCOtHqqyeRRhAOMQJYTrSy5DIA==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import finish\nf=np.load('/tmp/head.npz');d=f['depth']*.001\nrot=R.from_quat([-.948683301192,0,0,.316227769682]).as_matrix();t=np.array([-.032,-.45,1.35])\nv,u=np.indices(d.shape);p=np.stack([(u-159.5)*d/358.64218,(v-119.5)*d/358.64218,d],axis=-1)@rot.T+t\nnp.save('/tmp/points.npy',p)\nfinish({str((u,v)):p[v,u].tolist() for u,v in [(65,124),(70,137),(78,156),(83,176),(258,109),(260,127),(264,149),(261,166),(120,145),(235,145),(111,214),(241,214),(175,195),(175,170),(45,198)]})",
+ "description": "project shoe and box points"
+ },
+ "call_id": "call_d3bf3218a40449379a6d81f7d8ad6ce3|fc_0e05b35c94578fcb016ae26ba2b72081919637c5b5562ccdd2"
+ }
+ ]
+ },
+ {
+ "id": "a69f3863",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:53.041Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"\",\n \"result\": {\n \"(65, 124)\": [-0.24701096162197103,0.03140910949709719,0.6910568320592497],\n \"(70, 137)\": [-0.21991292201045629,-0.027594196989208564,0.7255543520299529],\n \"(78, 156)\": [-0.20947912417886824,-0.044987609248771654,0.6775092925698912],\n \"(83, 176)\": [-0.183232908521803,-0.11395591142723871,0.7157830657360426],\n \"(258, 109)\": [0.19705560076620107,0.06993367883975005,0.6974502592814215],\n \"(260, 127)\": [0.1815303772690653,-0.005548079149456486,0.7308389405389644],\n \"(264, 149)\": [0.20284967663312783,-0.01943781830802399,0.6654216358573333],\n \"(261, 166)\": [0.18054192688656984,-0.07729713643164932,0.6907771470716708],\n \"(120, 145)\": [-0.11416267255569326,-0.0448333771340384,0.721374966820128],\n \"(235, 145)\": [0.12504510830265422,-0.0448333771340384,0.721374966820128],\n \"(111, 214)\": [-0.1258512028897438,-0.1798917686242506,0.6850811723963807],\n \"(241, 214)\": [0.1259359683794026,-0.17950256367990514,0.6841230761030037],\n \"(175, 195)\": [0.001018982875912705,-0.12026751685270726,0.6422993613618274],\n \"(175, 170)\": [0.002574851178966185,-0.060117673106498126,0.6424117444706855],\n \"(45, 198)\": [-0.2752759024607758,-0.12622992376337028,0.6403275561418671]\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "5fef81d8",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:40:13.207Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Planning shoe grasp**\n\n**Aligning gripper for shoe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26bab1d54819186e23580d6db2f52\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning shoe grasp**\"},{\"type\":\"summary_text\",\"text\":\"**Aligning gripper for shoe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mu5R5ezv4JhNS5Vljjq4o1_swTW3lS5WTXYSr8vccTpbMFhqe-zVyipej_qn53WTufhXo5xF0vS_Ku53KE-IO61dfXMeQMSTYp4Xw2pL-BxNGopnhyyDDjycS8tOtRSJGBi2qSnDN6s31CUZtz0IjYn_eY-N5JzQof4kzBGJn3uPg5nInNWV-JN3lVwO3TdCh1NBpextPALc6rEYK5DVFkaEqdl_bVfHn8pDhIzKzNZztYeYkCOFF--_IExPWHyLKoXv33kDdNflS1ZIus0IB7CA-ScHYQsq0MhCgn_DGYKO-0H80ue4vpHCOhi6iZibwe6-QvYxP-JGkBuV4in1eJPGKARD6nRYpVEKXrSsm_zX5NVrep1oth6e0oxBJpHavr6bFoujZ3zrRYIh-s-ag--134NqsIvOD0zUt9F_fDz3M8SJtdAzuDZF7fm6FWHeJrXPf6wJ-T3pyVwphQt_-5vF3Ks2TF8HmTyMoxS_jlXlTfrGNAH2DKTia-hD9x8NR9AOxpXckOEZ2rVPfWBBhep-pueGSNW30QTvELZrSPbWrRSRgTFABYKeheqd3VhfQG0jckSVDHI-LCV1nvMyxtdXq-Umn7acEVmT6t6eA0LKH4nSMVXEnWvpNJc1jfD7pYgBb-7Zl6hX651pBunizvpF31UOCAAwc--e0Vn1wwDrdpriN4al6Do5v78ceyBAqPFyfcSauBJva-GeNsGntt52i2x6o70gksMxA2vM0-4TCWLGkBoPoO40a47KE2PSPrmFuVZD-r9LQOZEV7F7LxW-hLU7QnIh820kym1xTrO3TwOW909spBMSRiyj3dPoZPUc6XV8-nBiZeHKDvFnGsK5e2xExFi_eXoe4suN8do1G7-JQ__qquV1G-5ed4c1KnInYZ9DsrC2qgHXxMnU2TbayuOTIhpbTIlM_mzvx6G0kyBbDVFHNQCkz22cUeloOuPrDO_snvOXhQJSrhdEJC4afFjjEAr3dyipuwfG84Z0ctKORi8MjoKS4Ov0POlPWtD4T_z9EYb0V9inEhXZmQGwlWGe9YW7efzvSXrEJbwKd3FWMpA3b7uGvlmGbnBmUJa2lVCABPnPksMHsYL0t84l_xe1oLM9AonwFrlWUMX1A0YZUnXyVhnW-NZUns7oLFaH-s4IaQS4A_NQtFtBA80O8KdSQc_eDN0irX1z2srCOKc59kR9aE8ij1TV1v0Bd91lD6NhsDzycq39V4vZxjJg7TGRzNC28sQj74PJeB6MPex_M-V3vC_grZOiJLyB42KSz5tQz17y7c8CoeENLuIjJE6WY6G5SvuijxlkZr7zVWVTzM8MsOWf87DQ52zn6E1Ng2g9OFVk9dTL9Nl__cvgNJWEYieFuXIegdRTnmPK2AiwruWujeBJkF5Cg2hAWPSF744YTacgsVDf722vzIQPSWyT0QQ-sUMWopliQWMXSjcMO6FVW4zDrMz7Wl2MXM_ZdoiAz5cWawGnYlG6TNs9SDFpA5kEb_m_FU5ktxeMDKKJ7QOn7GtpLEAdKYP5h_fhAQ0PdgUquKpLLP_atT3WiCURYwSUfmf-ZmkV2KkYsSyaKcD3AGs_kNaRYhg4wqvSyrS6PHyxxbNQEZU1hR7xAZ4BrfhKKoIbZsQEnSIfhrmq-yppaQ-CDJwrij_9xs7NtWVKHCXLPQ4zg3ruHCqUb3oFWaxR1mYU66cUFAKOD6GeJeHzPndJWZ9tYkGdlIEtFs0DQsB96jurhC0jj5-Txs7rcA9dQM6xbxRiCY0RM_eCBhkAjPxj0JJWJpz3UV2Iq3_XNmQB4J-vFVpH9UYVMxLfx55kTisIMY_NR8lBLgrlnzUBGMVtEhwCDPvMk3nEmdoOlYR26wGF0X7uE860AKB30QeWFIAtrpE3ao_jpz-J0kO-mYTfAkotSF3UxcpG42FW5yLZQmwWfGA8Jjtns8LlV9APOcShpTpUX0mDv9ts_w72JHmbUq-gVlXPeT-2iih-YShpOXBbxmmSDlyxuhKi8mwESgTFFYl8hPMWWl6jnIqxNO2pe58_iPzZd7zqIiA2kdWyDSiab9y8dy5RRAGjbfrJZp5lr3ftF6CGtdo9oTp5d7bnllJ3jI5orYxJpcSabrfqnD4gJR3e8yLfXMpX3h0E1phpLX-pF0aExJypnBLhM9V658pYPcFEhKFoLflQPVN9z_Ww7jgoDkCOSfDmoKxJ-14s3JnAiGIkeB51zRyL_eXwXQjTOctyiW9-Yx93yW3MFnIfAHFDHu27xzp1LdjWUKCRM_IcAyw4Dy-7ey1saWPuF6YQi3HZXuf1q9FbG3j44KAIvrW6ig0nQBNfJL4UKgUy_FZDnNWTU_5Zn8seaK8W7J3_UrJezl0XbYJetNzvLSFIVMKsM9oBLzdTdyHgolMf-sF4DZ8eIi-2rL7_27-aERdTiLDpJAHbRAEtl1VK4G-XVjOqYsqVSATeKatPXc0DgndpB_7vaeTx1B7LRMqilRo9cewem1qUOvq81rXloy33CcIpgrlLKwszwU4sCTOrwbx37aTLf5cmos_QP1fViiMrF81vyogxV_lIcTvIbkLvg005wVpxKxuFopOs1AHIHc5AXaH2HCLJhxdE3B4mCcpzW8oG6p3_vU7XvMnu6DwQQEoLRHfsVjjGWkmuCUu8caA48vlDIX1_s0z2PjFM6nXumA47wB4kE5o3T2j26Q3rBOOUGjzVkJBTnDX1GHfHRGef1hTMTcaUx21IXbUrOBRyF7pB9laeKH1OR7Gbx949wuTeST-Wpg0-ssfrWDPYYBKUkXGe4c_CH_6MHJCT1FTpyN0g8L0eoFSgkrb5FdcfrV8A_qeIJL4FBrDDvG00ibnYyrVE1SJW5Pr8KltboG3bx_f74fFWvg2seVswwpssDqRElhzI4zSnmzkvknSSnZfPeRQz7NmBZUt8Q3-oMthQx7kRmcvm5KDgzZYaN-9g0d1NjVL6D2-uobvvz7uHZ1Ck2uAuCbmsrS1_6HSaiQ5EPCCeRo3LXXEftN-Ob-Ro0K6grPyP7-s3If2r4NXVTveOKtxCUrZ7Kx0xwhSmDtcPfz62C28hlLLI2Y59muuLA45SVOzeyh12p1AM5EYpFQYs0eOa0NmnpwXFAqeWEUNh8fZfzxBFsG9DUWN-ej1RxFFXm1LxB8xEVPkqU0XtV4dTlAaLVWHblMTeDme4uoWwloeTQk-ZioiGhmWzvD_owU1kXTsm6yFvZEbk0CwmoQun-Ej_nD8Pe60aL_798qgv0zaePIvj5YoOPwSZo-VAG1dS_wVm0am-0dQVFDMIAtYRXWIdNgS1Tv1x5sfaZK-Lmdw_Ow3dsvLnsuXZm2A1wJrldojdQvwetAZ1hlP5JUKuu43P_VQmxlotoxhnVScVenZmiYCRVS_ZRAI4NpSm6-s5g9GccPM5E5tXUP-4BXiQJiQAoR5tOpjas5obRnUSR56usmJJXG53M3YPoiMxfZotd33ii11ggzt_A_Shb3olSDL1A7q9s_duDBSXeqBDmeDR6fG5UruUDYKY8l6vntm_PkkGNr5MbHzLUega6NCHfa-jRw3emOMfWDFcEG9FjgkkZNM7R_GOU8tROdqHd6P8BHnLLVy42ULCBsIdy3-nZGys5MEZ8dKIrh4oxOXnYvijw-DEMVbxduYaWeBSah3LwE0p8NPbWL-pMsP7E3ZiB1vRpOpEgz7t50bmlOSJntfxkzIkB7BVBQjF-upFC2cPnC_6iAP_a0ghdeBlT2b9_pnR_famzjUPFz_HFsyUZMJXyj0loq5NBYPDMu4kUoGrJtWrxbr7ZQ97pZmf09p3TY5LI9QJyNMuF8qN3ZqI5jOV2OzgzXsvPTVb9ih_aD44oCb8sqDDqik-H0VwALZVbTWLo7nsJTsVO0GlvItoWtMng5YNfp3P1Hs9V50MmOuXx2FnBAgURcRsyxaWMuwASwTNPXf1DV3mxtOJj4lg4MHoHN14PMgGHOx7WxGInLaIVUaflbEYKcHb0woCX39pOGOtXOF0_n2W8PGwKBCDeBSlXTGznSOyQLXjb0LfAz0kd1CbiLmFXc5csESDOf5t-sF-0Xg9TwPtUavg2V8FgyXty34wWj1ra5GWeL-1L6AMb_3F5xH-EkYPNkdhgn2D8ZuyRrdQuMEhkBbMHuewUMkhpw3Xw259ub3TSVJG1ABpnADN9SCsyqcvrGXlJKjPq-3kSuFX71HVHKVTRvtELbkndKvIau-JYBqX8XnSclAvD11CRWXzebjYuAScyDJ4zPcCU94mH5N6Evh72H28rwHdP_FFLqEdvDfsuWvSvNQf-plRnv2QYmFWOAkXhnT1YUoH4I88-cJOidlzqpsHyKdr05nucym6aX5KIr9hoGahioTWd8mjEtFeFWIp4112ER_ZKdt6Go1JHqoxo2nSEUNj_RxDpLk4DA-fEx5aNddzQ4msQ==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import numpy as np\nfrom kinex import finish\np=np.load('/tmp/points.npy');v,u=np.indices(p.shape[:2]);out={}\nfor name,mask in [('left',(u>45)&(u<106)&(v>105)&(v<194)),('right',(u>239)&(u<287)&(v>90)&(v<180))]:\n sel=p[mask&(p[:,:,2]>.653)&(p[:,:,2]<.78)]\n xy=sel[:,:2];cov=np.cov(xy.T);w,V=np.linalg.eigh(cov);axis=V[:,-1];axis*=np.sign(axis[1]);proj=xy@axis;perp=np.array([axis[1],-axis[0]])\n out[name]={'bounds':np.percentile(sel,[0,5,50,95,100],axis=0),'axis':axis,'along':np.percentile(proj,[0,50,100]),'across':np.percentile(xy@perp,[0,50,100])}\nfinish(out)",
+ "description": "estimate shoe geometry"
+ },
+ "call_id": "call_359440a490204ab5b768a4249857ef22|fc_0e05b35c94578fcb016ae26bb92b4c8191aff65d64307ea8e1"
+ }
+ ]
+ },
+ {
+ "id": "0f2b928c",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:40:14.556Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"\",\n \"result\": {\n \"left\": {\"bounds\":[[-0.27703949870034816,-0.11849672931365157,0.6530756384513174],[-0.26232817835314304,-0.11589681011362746,0.6648956826818977],[-0.2084795206185731,-0.048453607301866264,0.6989171661594558],[-0.16517033707524315,0.04587652017197147,0.7280738549115844],[-0.15957980670316027,0.0673668820840671,0.7397426331669105]],\"axis\":[-0.4348054796080431,0.9005243999486185],\"along\":[-0.02822664134255312,0.04733788568632173,0.17347461851403906],\"across\":[-0.2438903331252665,-0.20888409446241507,-0.17148698275945262]},\n \"right\": {\"bounds\":[[0.12579376536245684,-0.12617690826397737,0.6530134103302274],[0.16420628560756578,-0.07877877371633266,0.6623519701729963],[0.19117578484493938,-0.005752951117641736,0.69816639561117],[0.22156610312819316,0.09690986291317003,0.7299211106280531],[0.23969001705265122,0.12021601950746491,0.7417706810964337]],\"axis\":[0.16462025977367772,0.9863570195786345],\"along\":[-0.10348059217440107,0.02641075351907217,0.15416704938916012],\"across\":[0.13832065240589805,0.18958687182277106,0.2274015727704394]}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "c22adbd2",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:40:24.192Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Refining the box mask**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26bc06d088191a4802d85f5e70b70\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Refining the box mask**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mvIwEo3ph_jd_Q_v9uUFbhzXOJpfKvgjNyykePedbhXad6hG9wta6_g0JUWF3T2zmI_w5xus36nbkNac3a85WhyNl3BGLDKb-jOp33QhEM6amY9JcLRrxN0vY0P26HDeqxRIHzveGPN1BRdBISV6FCVznsIHu1NKnpuv5OCFRYrZdwHtPwqHi8CyZofqGglZBZUoKBOmm9hjokbX-U83_DmjrOuLWs4ANiF9_hUuX5q1lRJvllzjlCTzMPZBGDiQZ_tG1tDwCkkVrAahAKvNJ9JTq_8ux1yt6pLa9udeThPmsBl178Ip234iJRVuExukrGsba8BuOGCpLY5IHcd4WtDij3N1whcGfKQ-u-pW-gG9lK8-gOj8ALiyMxh9-wTezZnkxNHMRYvlGqALJ9VTy3PY_3mZfF2vYXt0PPKof2pjkfRLug2WMlkHkpWzjNX3yr8q7Z_lkXQo7o0nGGopOM259FKOdDoKRkpKgGd3j1mhgamgf7IZhH6vGGXBta7loyS1n63bkj8fS1yhtiwWDRPDknAPCizsxpqLtXgCue1g3HDvb1jG_abVWryySWXAkHc_iEphZ4AV7awokQCmvKNBzECWjG77OHvsiczif-Wszm299rgk8W_6iCwIAwfp1t3DpfSe-lxRK7nTWgQjrjf3ugkZnSz9q_pjrbSRRtVhcO6H4c8_r8SMxNhqK70uENw2qH_lmyPhXOqGlbjPkUvTYEJPN2CPjFD0Uv3NJvSea9jNXxaSGpiyRl2c20BhwRrvlCaNZj1dD_sRvpdxmk8CpXRnOypn8-C-tLsrgeUjeUoQDEiKLbkzsQhY5Qo4U-hV38yOseNvbUxrhZJVaqMwpeHahCXAvRSteI5Qj7iKeVkWmBheaK9rEvWbizUUaPqIjpPkPspnYoqZ3Z5xZs7WeDWzgKAGsnX8hNGCkjznV33PEf61hcyBj8rGUkCQSwJgokxxVwIdFhsZNRWrhH-2c4PqGA1fNg2dQFp001pV1v7iXXlVGkCfRfwf6ruULbqUV0LlafJnEDU5yk9ibT2Qb1GkzUAQlQxwd2k1k50fD21e3afpmHrUhDP8POoCKjh8GH56WjigbOcLM4zYHUAW2P6_rECG5ArWNeWQrQZPFLH9C87trouvF3QnXkHuvsft6kYlZ5jezrnNOmoX3dF7tiJmuur514Sp4hX7Bplz-v8qgIj2U8CEWySp59LMMcuPxZyM_d2mER-yCR2RJpi_FG4LJGyVLGkLWmz329FdhyY5c2HVHL-z5Er6f2TZwGlh3ES_NFGBVONXzO2Qb492upm7_W0wzC7nvW2Mdt2FV90XK0PFRxPT47h5HsgG2oi56hybxUQpqESs4wGdZVbUE-7MdsKkyQAwzXQCyEt-b8nXSq4Z0_PdBaw0X_V_-9rM3o76niPRq1oTQL65386C8r9ki5GBk8stCz-BenKbHcY8zkFlTjeyl5EfeL_xT39Rw2d55M4QuSaARBuCEgdj7vjC1AcOWsv2NYlJt7r4qDOv5phy7hOJL68LMi57hg5Zv0UnyPFqqsQVMAqeff06JDo10Rn1gpAoKV4FmVylAa9xdSRb-TqrdbgoC89-cLq9xkgpdACXsnjZjD9fDz6GFqn2htrXEgavTD7FyHNytCk0OscmE5NuVheZOUTR-Kg61gpzSYzyRzFVGVMdpUDv_yULyPQXAPljLbSdNOnh0l70dsP_D1wckjjiNixz9S5R0WHGkQV2j9sLLlVG7XHwa9EEp59kZgi4HHTXWluGQg5vztYxehFVdG77luxAYdUVSkOY-58ssmViY7mt5Ne4SAvSiAPDw3AOh3x0YDRml-xYd16SwlkXzUBKQOvPVeibqGU11wUIoHrKaWnds1Kn8WRnaEB85TzPOAxxUxMnZSb8XcMZuPJsjacqM3PKMGsxkqd0ECoY-Gz3uSQtOMyoiJfvXL5GTT6B9rSVHRTy31vXV0Hb8AKME7CnEnqZMROGS9Mg93VNzdKvFfdEJ7HhYIPYb0G9MC-g0_lbygy-jNfL6QFFSCMt_gt1gRb4dswGj2w5-cJmT2cnvgMs3z4yFScd9k_ukxPCEJAfDjCbIcErM7oNwzcB7zeOnrtGESIOAgoV39LCwxsSLkgtCiM8NFs5zM4iBkbnITJyn8cs_FCTeRbGVNfJPYbPQV_cXyJDVxc3nzFxBzFyiRf83BsyHxwkD_3gdDoRxQ9pQnoGVR7cUPjXBB86XRUCtCDmhD3UZTE3AbVFWprzVrBjrkLxWPwus9D5WKKDvT7Y714rLZIKdCN2RwbmTtoHx2B4_D3ih0a4qpw3y-q7XivZ8gvl3QNDnjSRU9jzsVoec4KqE4tKLa4DrBeZYCBaA9v6nMsrPbwFTA90VDJC1J-ZtYkvRGcF4tahReH1ich9YGTpher8TGuwrxrO2wDMnurMwMxEifxZgkVgvMvreDZVAo7pJLpIs4BpOw9COzsfNgjRUSceB6clpjGB8-u9XinMSMzZheYkfxhuWmZRIxQOLq63tqw7azeCGUKyDrh7LP2CrOvltI05Kk5z_OVBg4vYFCp31Pmy6DyXO0z45WVFHLmpDk8-IobT6J8jco-FzR_TBMXY3aj14njcLU1Zh3u4YGXWJhDryn54ESIB4oeBqW6_axsyaT1WcWTlgv8IgT-0vUJweaGNp9zm5b9lkVcOSMS_U9yJmTU9q9ZzWciGfaTTx4pYQCiE9K9RhEeI9wmyx6r95rWsC7iBRYwzp9ckZhDXijbCaws-5zFWPn3clRaBjJobG-l2nxbsoXnE4NgigDANCt7KM9frm5amoDLoSywH-nhSe3j51a1jEuh23Z3YBlHIckkJ4qC5sB6WI0k5PIyjKuKVwFEK-CD1juKOZ5GaavwWFazgaf02F1uFSK6Wx_-E9EfLv9Y2EOqf7EBduCBtb8ZS1Cwf6ul_U8TYz57igmYpm_V7gq7dQ0odLnRPBh1bfaKXmQbueNDzgXGmCb3iHEgdrpiV-t8lJFpFSdFGbte67Uqsuj9cA4uosEnUgFqB1gjeZoHyqvFfCT1tflCFrJRkrZDWDKxp6tPmlcXHp6dc2fSMMWHsSdNWuVdzvQ8dGyPgXJAV-Kwhgp930xo96AdTWKlh1brXgWziwUle0wnrSVXgTtNXl1hPhjWzCnlcbCLdOWjRz4A3sB-ziCmjK2CDHrailgIqqGo_RGKLWi5rMVAy0DgyOpGMdUxa3wCM_bS4z1FZvVmpFjyRrtYgMBhroTTq79qc3PljQpc\"}"
+ },
+ {
+ "type": "text",
+ "text": "I’ll grasp each shoe from above, rotate the tips left, and place the initially left shoe in the nearer row of the box.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0e05b35c94578fcb016ae26bc653408191883718d5ab5020b1\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/lib/joints.py",
+ "offset": 1,
+ "limit": 240
+ },
+ "call_id": "call_74b06e15e6d5437b8dbf59b863ebf7bc|fc_0e05b35c94578fcb016ae26bc810f88191bbc88266170ed223"
+ }
+ ]
+ },
+ {
+ "id": "86de06f4",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:40:24.196Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Joint devices: URDF command vector, limit policy and link kinematics in the device base.\"\"\"\n\nimport math\nfrom pathlib import Path\n\nfrom kinex.lib import urdf\nfrom kinex.lib.geometry import flat, pose, vector\nfrom kinex.lib.kinematics import DEFAULTS, Chain\nfrom kinex.lib.urdf import joint_target\n\nHOME_RECOVERY_TOLERANCE = math.radians(1)\n\n\nclass JointModel:\n \"\"\"A joint device's commanded joints, in URDF document order, and its link FK/IK.\n\n Poses are [x, y, z, qx, qy, qz, qw] of a URDF link in /base; link\n defaults to the model's tip_link.\n \"\"\"\n\n def __init__(self, profile, directory=None):\n if profile.get(\"type\") != \"joint\":\n raise ValueError(\"expected a joint device profile\")\n model, self.tree = profile[\"model\"], profile.get(\"resolved_model\")\n if self.tree is None:\n if directory is None or not isinstance(model, dict) or \"???\" in model.values():\n raise ValueError(f\"{profile.get('name', 'joint device')} has no resolved URDF model\")\n self.tree = urdf.read_tree(Path(directory) / model[\"path\"], model[\"base_link\"])\n self.joints = urdf.commanded(self.tree)\n self.names = [joint[\"name\"] for joint in self.joints]\n self.tip = model[\"tip_link\"]\n\n def chain(self, link):\n link = link or self.tip\n if not link:\n raise ValueError(\"name a link; the model declares no tip_link\")\n return Chain(self.tree, link)\n\n def fk(self, positions, link=None):\n \"\"\"Link pose at commanded joint positions; mimic joints follow their sources.\"\"\"\n q = joint_target(positions, self.joints, check_limits=False)\n return flat(self.chain(link).forward(urdf.positions(self.tree, dict(zip(self.names, q))))[0])\n\n def ik(self, target, seed, link=None, **options):\n \"\"\"Commanded positions placing link at target, nearest the seed projected into limits.\n\n Joints off the link's path keep their seed values. options override the\n solver tolerances, damping, max_iterations and search budget.\n \"\"\"\n unknown = options.keys() - {*DEFAULTS, \"budget\"}\n if unknown:\n raise ValueError(f\"unknown IK options: {', '.join(sorted(unknown))}\")\n values = dict(zip(self.names, project_seed(seed, self.joints)))\n values.update(self.chain(link).ik(pose(target), values, {**DEFAULTS, **options}))\n return [values[name] for name in self.names]\n\n\ndef home_start_tolerance(profile, joints, target):\n \"\"\"Strict devices may recover toward declared home within an angular margin.\"\"\"\n home = profile.get(\"home\")\n if not isinstance(home, dict) or any(j[\"name\"] not in home or abs(q - home[j[\"name\"]]) > 1e-9 for j, q in zip(joints, target)):\n return 0.0\n return HOME_RECOVERY_TOLERANCE\n\n\ndef recovery_targets(actions, joints, tolerance):\n \"\"\"Allow a bounded, inward-only prefix; the final target remains in limits.\"\"\"\n joint_target(actions[-1], joints)\n previous = None\n for target in actions:\n joint_target(target, joints, check_limits=False)\n for i, (q, joint) in enumerate(zip(target, joints)):\n limits = joint[\"limits\"]\n if limits is None:\n continue\n margin = tolerance if joint[\"type\"] == \"revolute\" else 0\n low, high = limits[\"min\"], limits[\"max\"]\n if not low - margin <= q <= high + margin:\n raise ValueError(\"target outside joint limits recovery tolerance\")\n if previous is not None and ((q < low and not previous[i] <= q) or (q > high and not previous[i] >= q)):\n raise ValueError(\"joint limits recovery must move inward\")\n previous = target\n\n\ndef command(profile, actions, joints):\n \"\"\"Validate a sequence of joint targets; strict limits reject targets outside the URDF limits.\"\"\"\n if not isinstance(actions, list) or not actions:\n raise ValueError(\"actions must be a nonempty sequence\")\n for target in actions:\n joint_target(target, joints, check_limits=False)\n if profile[\"limits\"] == \"strict\":\n recovery_targets(actions, joints, home_start_tolerance(profile, joints, actions[-1]))\n return actions\n\n\ndef project_seed(value, joints):\n \"\"\"Bound a solver seed without changing the measured configuration used for FK.\"\"\"\n values = vector(value, len(joints), \"IK seed\")\n return [max(j[\"limits\"][\"min\"], min(j[\"limits\"][\"max\"], v)) if j[\"limits\"] else v\n for j, v in zip(joints, values)]\n\n\ndef measured_positions(message, joints):\n \"\"\"Order a JointState without clamping or silently accepting duplicate names.\"\"\"\n if len(message.name) != len(message.position) or len(set(message.name)) != len(message.name):\n raise ValueError(\"joint state requires unique names and matching positions\")\n positions = dict(zip(message.name, message.position))\n names = [joint[\"name\"] for joint in joints]\n if any(name not in positions for name in names):\n raise ValueError(\"joint state is missing modeled joints\")\n return joint_target([positions[name] for name in names], joints, check_limits=False)\n"
+ }
+ ]
+ },
+ {
+ "id": "bc292a92",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:40:49.414Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Creating staged motion script**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26bca9d408191862210e4fa5ad8a0\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Creating staged motion script**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mvS6fqLdZmMTyYsJhATvVwebiYLckDoBzo7ScLk4Z64pqQy5f9lqbQBt5nTeP-q_VoDhwq4bPEUGFlqIoC6IUwo_WJBhwaO44XHmXOpAmTqVmvBJs3hha_fRModQGdQrTysE7WTr30aw1GsYj-hIIEVviZDseg9oj7rK8b9As_1NWFFxAuJG9EQHAN_hsWr2iwOTW5BlOUQbGwcvhkvNyRpF0nxtE2-HbHoFed0MmIn64mgvqPTq_RvGuEcd_gjAv7ggLUP32S74nrqXGg19GZ84d8iF5kmA2FjoJ7D2tJhdjhiXC8iQMzCMVektrcM2PxkDPMLWd4DjHCuv2jL4grSKbuNoXUB5RMqL__7c36p3JoWIKQgp6UDemEvMJL4B2eaHoQpMXj7uClvPDKD_z8e61A9iOxh1if0xqUUpFlthf2hLo0swvdUK2vaNlLWpuVXAYxTM61y8ioViC2HqDjMyE2cHTbz1js50tnYinOSuY6F8NuNwS49jwkI4vPnJlk2CUzc0WN08AO0ivywj9ua2s6l0rJMTTDlTnlwytqn3lBiaXGDREwlhnQk5tjE1ear9pm9kCQ21hp5malw7OOb8vNhZcCacJCdTZGr3iShQ_AEdxleeQB3w9wRzUmx1vRa4XBziTU8B59EUdsMg3ikE6F7mCodp1LKCHT5C-IV-0bsRM8Na85qG-uJDi3PLvNdrFXeGjbb0VuGtfzSte8ClmNTkpTDc23-D4j7JzPVOg3SU6iuHG8BOSnlwdgreZsEsU7J6RmtxlltJeOVXmwZXCkSowVdCnlPPT27aUYchvXXz2nkkcQ5fvFsgkC7Ix2LPgreFrQ4WrqIeRzb5RkJDn6zPWstthTIUJz29JTbHI-7aJ08j9sp4IYNVVL4hogzsBv-DDLK2Z3Z_2gkKfHkLzTEA336x32MZkdiep8MGCmjaj-JHU9f4wcax_ZkyivUDgAKe7Lbq7nOhXj2eJvnSyoufUJem5UGNlgushXWvxeJgs4kj0bUl1usj9-SO_ZoOa9piIO7LQCzx9Car_fuu_ZAUTzN2UKkNOO2wRJvkjEPhjxuXtfW_ZFysslWdH_1nnM2R8UdyB7_ylJ6WxBQ5zfGyyHquaCGU3Y_FqCs57zfL7sBfnzQ6RMFd6yeVD2iUzZuhI-8BvW3T3R_lwgBdJyF6JWFO957TiMPjF-EU3nxpIEj4Bc3Sn7NtWwQaJf2ErjtuXbtIDNy9BgM420c3zQqhvuWP5uTFwZwu7QME61CGSD3qqvWeDyMnOdIQcFsR2eCkRGR0ksRYjMuqTA-Vy9VMVLzINE1JqvcvSBNCuwH63NcGiZzT8KX_OpVyV1rJbQ3qE9LOII_R-9-b0t-4eAYIgHTIpEnJhwjLQgk5yiyE9LOxZ-_KFJAQQxGqfU8lU2gyIBXVoM-9x48eWu2J6RYHu8_ksWJ8OUP20vl6j2MHN_Z2tKOMjItlAe-b6erVpQIU147g-swgO4jUfBhJ883tCogwJesUzQE8xzmIk3fw6ObmZPobrT1ZSpMEeaLKtJxl9MR3Uvr4bHTBOOdFbu3hSgfk4RPAM2Gfq-72K9Le12rGwZPLmN8vT9QQC_Vkol_k7gis1yFd0PVNgwnKicB2_HiTisJvjpCocfiErdKuXv4xqHCWuHq3XefnK-dxOuEGps4FcnG51C_qKrqPX15vlQY7WidwhtbNexYh5FhMn3eUWBDCzaQOIPkAyFPlugAWZVQx7nUW6EoAyVk_8J_MKtZrXOkLxSQvnym4ONZ7HGIRYWL5cDNoIEd8v0zVVu9N0dNHLDs4PsA8wIQ_8a8kz1TaTsZmlT0YO4fDrZrb1pv-lfVblNXyaagvZOeoQFVWpxAr_8oVhyAQA7hZZHSnqRlDxJv-NKrxwJYplmCaTjjWVb_3BU03OoKp7xeLyVFowSYNmW1bCYkwt1kFSV-eA-i4deKZR1VfYwcmphE2oRY4o7vHunl0Ip1wWEVLlZpAY_oll0ZkY35-cXL8o3Gx_z03D1VnrfGzl3KjcvDYfji1Ir5_oRUeU3r1Hj-DU1deEw_jqxDGz21VnIipan0lA0oY06SxYy-X-N0-Bolup87k_QjsCJoH9MM0B3IFtRNukhTqSGrGbl3mckUYXmVwB-7x7YEQx9_UFm239MvmOAVqFloKpt_KdS8KJHfM6iaZYwqQkXw3qiYqHXvCD23nZH5Ul66gd_jWwGtUDxOVrS3w_i-wAF6EaCDPgjcD_pVnb2qwvC6lJS3-XWa9BWCgKVsiHzHleyWYWSb81stadUFaUcuZ8cY07XxpSsCFBHtGF_pFAKZM0NYEo5QBZoeafjmPJOLg6Sq4O3dKJkn4IFVa0Oe5WgpIUg--wH8RCofj39IBp4oOUDpTmVpHb5sAa3ru4RSdD1i1R016ORjzpO_pRtaaGlqgu-298Ce0DS5dGTf2YkoYO3HsYRWfevm7pW6W8Z6C_qBC328gyJwxKygflrkjt24X5x4JvPgZVUSLBxeNysGbd-X8pnDr1S4ar-s-mrqhch9YhiBmlVFMYBQcyWZn2kkiPkPRcOiq_ucoNGMRA9d8ylHlQMBUECOsP3M11waFcPc8viRDfzYtZOvpUZAugiM-tqTcvl7YbicZ6o6GcfbjdiY7-kQfjYMhs7BbpcGuxvcSvsYWhre7mqlj2MKxcR22nLdAl5_y6KptPUiSqt40uI8C9xKjghKlcWvb-0eXMcguYdPKPnPrzZtSpzpLRjbSvUkbOru6dJWZeTQNZ1hjqP3pjeRZLnJ9VwPAOwg5sNOx8lHlJyfGyy-QJ2KSlMDCUIPQwexyFXQ45dugANnRq4ADgh53t2DY9cEOazjIHv3dkHW3Twd0pqXBXo9bdL-oe8QG509rHqZD79RYbUTLLb6Q-qCjoK09UZPPmDUr-IdmhwbYH3xrRZvSO0DpoaOR9fX_0C1t3M5cBtXjmrp-I3ql3AhGn26MIvp7RZXVWdtjy-mBak_KqQR_LEjl6i90jfUH7O02IfxoJC-qZ8FpuezWrRjFw==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/dual_shoes.py",
+ "content": "\"\"\"Measured Cartesian dual-arm moves through public Kinex ROS operations.\nInvoke with exec file and args: targets {left/right: [x,y,z,qx,qy,qz,qw]},\nduration, settle; optional grips {left/right: opening}. World coordinates.\nA dry_run solves without publishing; each path uses measured start FK.\n\"\"\"\nimport asyncio\nimport numpy as np\nfrom scipy.spatial.transform import Rotation, Slerp\nfrom kinex import communication, helpers, finish, args\n\nasync def state(io, device):\n async with io.subscribe(device+'.joint_state') as stream:\n return await stream.next(timeout_s=10)\n\ndef matrix(p):\n t=np.eye(4);t[:3,:3]=Rotation.from_quat(p[3:]).as_matrix();t[:3,3]=p[:3];return t\n\ndef pose(t):\n return [*t[:3,3],*Rotation.from_matrix(t[:3,:3]).as_quat()]\n\nasync def main():\n a=args(); duration=a.get('duration',1.2); plans={}; report={}\n async with communication() as io:\n for side,target in a.get('targets',{}).items():\n dev=side+'_arm'; model=helpers.joint_model(dev)\n measured=await state(io,dev); q=list(measured.position)\n base=matrix((await helpers.relative_pose(io,{'frame':dev+':base'},{'frame':'world:base'}))['pose'])\n tcp=np.eye(4);tcp[0,3]=.12\n start=base@matrix(model.fk(q))@tcp; end=matrix(target)\n interp=Slerp([0,1],Rotation.from_matrix(np.stack([start[:3,:3],end[:3,:3]])))\n points=[]; max_jump=0\n for i in range(1,a.get('segments',20)+1):\n f=i/a.get('segments',20);t=np.eye(4);t[:3,3]=start[:3,3]*(1-f)+end[:3,3]*f;t[:3,:3]=interp(f).as_matrix()\n goal=pose(np.linalg.inv(base)@t@np.linalg.inv(tcp))\n qnew=model.ik(goal,q);max_jump=max(max_jump,float(np.max(np.abs(np.array(qnew)-q))));q=qnew\n ns=round(duration*f*1e9)\n points.append({'positions':q,'time_from_start':{'sec':ns//10**9,'nanosec':ns%10**9}})\n if max_jump>1.0: raise ValueError(f'{side}: IK discontinuity {max_jump}')\n plans[dev]={'joint_names':model.names,'points':points}\n report[side]={'target_q':q,'max_segment_joint_change':max_jump}\n if not a.get('dry_run',False):\n for dev,payload in plans.items(): await io.publish(dev+'.joint_target',payload)\n for side,opening in a.get('grips',{}).items(): await io.publish(side+'_gripper.target',{'data':opening})\n report['wait']=await io.request('world.wait',duration_s=duration+a.get('settle',.2))\n for side in ['left','right']:\n m=await state(io,side+'_arm');g=await state(io,side+'_gripper')\n report[side]={**report.get(side,{}),'measured_q':list(m.position),'grip':list(g.position),'tcp':await helpers.relative_pose(io,{'frame':side+'_gripper:tcp'},{'frame':'world:base'})}\n im,dep=await helpers.camera_frame(io,'head_camera')\n np.savez('/tmp/head.npz',rgb=helpers.image_array(im),depth=helpers.image_array(dep))\n image=helpers.save_image(im)\n else: image=None\n finish(report,file=image)\n\nif __name__=='__main__': asyncio.run(main())\n"
+ },
+ "call_id": "call_0868a220b62b474994731df198d503cc|fc_0e05b35c94578fcb016ae26bd23c40819191af04b6129b3ae0"
+ }
+ ]
+ },
+ {
+ "id": "ffb9c778",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:40:49.418Z",
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+ {
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+ }
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+ },
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+ "description": "construct grasp orientations"
+ },
+ "call_id": "call_ae9204374e2d4a3cbfbeb1673bf19662|fc_0e05b35c94578fcb016ae26be3d0a88191ad5024466f984815"
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+ "timestamp": "2026-10-28T21:42:28.145Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Rotating left shoe**\n\n**Measuring box interior**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26c31600c81919e3bc1523f8b8ccf\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Rotating left shoe**\"},{\"type\":\"summary_text\",\"text\":\"**Measuring box interior**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mxDJsOQp9p4jT9Zoa-aKQujWGVPVX8ZaSDdpXCxAuZ84SY4RgMf4ZvUHJtLg9dwYY7tT5c9r-6o9oTlNLDcLycGY-ryaal6JPHOaab-BCiDol1USLy2Cc3i3Xir0ay7KWZcEgSQFsfwdK3F4p4nRsuGo8i0E3jWpQ7w9DYvI-F3bvOtXkYifLv3jXSuSfSTPk-dLR8LQngVmZ_atCWBZPtOzvP1u0tzMXNPtZXtMA3fiQgwK5yVoBtQKhUhGSUVaz7VJCTUBD2j1lje1mSU_hlbAPfenAx0hawBO1_TjIuejCYR4IVtB7Cd0oo2FMm8DZUUDbNy0p4enrluy7kXRBc-loZfVHzDBRz3TDpFmHdsdL6msqMb13AD0Kjq1kNBIhF54UOpy7XuszxeVceNKwbQKOOOrQUrQYY-1Wv7PVxHIGdVXaroQ35x3iXrJgos1nIk1s2qypH8ozIKIfcI7cBl3m38iY_ccLTlAUxH-sfOSHu-savPxw6xlRoSR7fZAZaklhNlax2U4YcRGd5bxlItC347gRTtr7gmCiGMdSLhHTy6wkIfWlw3pdFjfyBoEI22EoQuqW9FmeDDjuqq_vWP6Kcg3Jl0qeCDmJWTQi2QMCoKKCTJKzrnSE7sD0TjJmdnR23BPs6SXNrbKieduz_INNssIAkZtF1VIcDK5zKxI6SB_fmQXd4GbXF0rz0UJFcYM1Kp7blbLhxZuIi0EVlSKncydU5blCe28QcRTGMUkytFgCBQOTAPF6lF7uy8IO0B0Ho50zZ1wISOliVOjMo9Mz3lI7T4AIzhxUV_Q6JFtRrocFgTGXa-LpGicm64bmYiJNKDte6TV9V1WtkEtYTf9BHqjwqKOB1b_VaARh594zdCqP6XWyLv9dmoAniJEQ2c97HiMOTGL7-RWI5PAcOk4R4SmLMTg8XprjL_EeWWpWHMNhgEfhchlku4yDT5taHt2NrarsWdyC4Qxj4XbWkpMFnFRcpQ5a-lbIbT_Ypog2w_UPD4hlKncDr57qPTqslLuTARZTVIbI-DiipEaWhP7lA54l4Q3U3So5xRk9EImI0-ErcxW3bhYgishmbhMjO3f3Ev96OgQXELqbSCiDzlBPlbVypi-EF3rio-tvE3b5qvnJYAkiEKZBu7C5aqj1XzRMGb3CKn8Ua5AVkvnzDyKrR18iTCrJgg9gMegSwHTSeOYxoTHF2K6DlJfocwiohZfOX9DIC_BMWzjYcQi3CLPxSPkrYWmAiBzwoX5Cr0Bx-8JgJbLZTqznueDIg0KuUc1AcC7_NgBYGIHZOyB-FU8i78AuSYwP8O0ucoYypxyWnE4Dz_NpqnvGJAn2aWQnB_KqxF5aJUqPkyJwzDcAL3vmJH3kq4AIcspliJEZUMBfYxQVa6GB_bHd1Pbd06q0QkgTFWXIKtvaHhFIWptPnmPzj7HuvfFCcGRe_E3of6nWU0ZXfXdHCmUi7rbfg2XhMDnOyd6tZy9mxYfIItgV5W4AMJmmJMUOL4QP1Cn1a4kxfr5ZL0yv9dAFplGjs3nl9SeigTBGJR9EZ_Mr_26woWzYDYj-KSaX5GFfcLFeei8UPv3TlK-yL71fh9-PRNbyZlttOJuyd3bElnZaiZYemgp4yLY-qwnOtsuC6nmM07a-_ybLlT1vPVfeqzry7woh1y0K6DtfKFn8IsB_lh900sESKkFNyc-PTbgr3ewUOmQ25kB7akTfPpOZ7EfKZYKfZXBreCIy4-zdGwDcg8UXCAKeXePJ883kx61o0TKbC-so2jBe5qwv2bAKBQxGb2lg3JTHEU9mJJr4ItQAyUOO5azdg23NPKO0f_HbEIuRchIv86QjOHX_-lm1J8jVlCWOaCpjcHn999Y9m9rxsHO4_7HQpLHWbvjkwWe9wPs-f02jLqzdQPGBgYJriQF6c6S-3cAf8-DxJBZGytaU3vuSRQzBqqPvg70gTCV66UzQK2UkiqXUA6gk9iu9jNqNQ7bCkEvMNydfCDFf92lhQtioofFL4MZZLPJ6s7SbHVdXHYSvjZOOfqCe314RmWP-CqC12_dWShKfObcUMuDhcQb1JEIcmNWqJh17-b3Qompiz2u7LRWK9dYS1XBe-Xd9WjMeq-H-cNNdl1Kma0WA-5ZV-_Ar_9EmNKictFegEwvpbJjUmxoxZcUKnWw00LPBj0p_XyMe2HAzrhvyxIzpQl6flKszlzadcjqtEg4qJ3rt0Hxu67OLyBl1WsdLlj_G-06lWpp_L2r104xkk-lnH7_bOr8Z5zQ-8gkFmm3RgP5xs2_xkT4j2vBdyxd5t7hESCD9Mt-nS_DTcoCDcwfIMlN1nOAKF7rZq06TG6QsrOR45rtgh4kxdc8-49T5e2nKbfQNJjoTd4cJux1PcAAMhCXr4vAQtx8OIvP36PSJO3zTVOrlrm7uNnwejXxQgPvtwpgNRwsklfwR_LtFoDyvEaagCKxi5cG62o7Pw1YWo0LIhyjpkFlmPtxv2otHvhIXwwfWEG-dJKUSqPUb6tdB3EuCpekAxkTNhsHiToZH8zC1J7PAkwSq4g5OdOqSt8rQQ3V5atVolH_y9yVczloczuXKmS-w_kzF_X_lGljhR6DyEKDh1R8qLNyIXVZiAL68AdgkSKCvXwfJQFo3kxhD9MbjwuNWcOdqALP6VUQufZnISPMYHzkHg3KX_mIzF7KnyFneZILJEOTZy02M89mDjpqLevk5vFkUR1QIdLlzcVs74sKjTsbeYU2-QEeqQl5ke-G3wYIs1jytLemtC6ZHpVj-2MIchWC7mFVDAcrMXcuIgA9hG8QMwXT7sCcB2f8d4UMZbg1zYewlJKk4iKbEx1nNLbQcaJ_A_x4mRO0Vf6-cBG8YgFtCNWa8berd9-iIg7i6orqiyiIgRPaPST7fc-Z7dO612PPjoJqQ4SJuiGvOYzmavYrmYCKXnbBn_O3-DBgNtE3SLOJnhiGERGIki3P7sYc4F-C3ZcDY_34t67xCVamygVXt6V-GY964KDMH6eP_7wEziPdEnqGgMpzY_KluqJ5-2Rr1s0ATmJrm_qY0VW_0Rukx7Qcmzlg3sF7V5xdmJ9zagdAB4545TguCs-bbMT6GJekQew-dCtJcACSdUEimdJ8Mu34DUoyswAlN_PcBIiFcAPQ114g_1BYeKaMF8RHNNvDq9L6yDLhTnx-9lpTRkWrhkTGReVl66wYu3WUlnnT9ZlxB6NRUcVwkZe1BsZbn1AUSbfbMpVUdrH3PI68IL44vHSQFeEfkwOcwjmEJ-AZdPwQs6tmUwtiLJMdd6i50oZVL39u0Cfjq6TqmTqSGX17KMUx4MN1d-DB9vSgNtRbMRW2dMj2MQI3DmvnOUi3ux3gaX7vcCVsms_aRX1qFogLvJGbwtie9xUi9PjnfyAJEycS1CL1Moo6BzfkGWzwxdDaDqk6VATB0aFkfOtUJpo9yC4uZKGmEp6Kib9w2CeZR1msobL3N5_lQarhrIWmg_nKNtM0OmN36a7d2Bx47P1JENd2CHAhhSBRKGaOi6AP3y6UhGGYfbr8skj9M_5nakwuoh8PQ9PXakcbNuy7tyihI0aS-NS9jfCoXqlZqdG9WZLDVWfLPg9rMk5WstmmjPCIS8Wry_UzaGYBwTKp2UTYN_KETZvq2dRK0ZhDABi1Jvsq0U20fQF7j-a_FZ5GppPbbyGuQXXBAzwtAmRPKPLmgxRF0L24yafKbfzaAMW-idWUrin8NMnzbLdt7VSZnOysLnS-JsodUix2e5dVsZtsD5q6n4al_wzQO_jXQBO-dz1t2kMT3aW8Q4MuFd1A4Bl0CtUa2ow4ZLYkJqbPMWBS5IgkT3PAWtiPWrzjEuL146ff3DqtgepBtO4iKGsg0X9lxfg37hPWuVt2T5XQcOgE5OSl1aBsH1y5ZRie29pBTsiyrTcVifSfPD8mRInjSEETCjYY-H9zSsfinLC0UGtbi4TPW6278HzWhDWavhlpF3t9uhIHRwUZam4F-ICqtJ9OFAeYr5lcY0rMhQZGxqLZwrqSZUekgAt0l_fYofMZjnANzS4RydqSkjr4DpgvQr15NJCLV-zBLF2Va0owZ_FmV-_I2tv638_kGrmvF2y-D9-tF9wFTdQYKFTEVQXGlvZsTYlfkTWwgIjuTlZ-UcGVRKs0LoHKDFtv8BZHvMgY6OQy2Ino2mc3M0ViOPQLFRH6IPk6qMvCi0W128l_wYxuGn5r6_POk_3QuehUU2PAOyzXQkdDyA36y0L3iJcDICX-v_k8JJoL8ULyIJpha8GRfzOa8jA3Ue4F1X0rhAQbO6bnAc3iIpRvbwtJF6m8KLfCuggqSkApLAbLx9mxcK_v5KAaN2u5afoIbjRu_XEPHcuxkZnw6IlHAj4zk2-pW8_-fz9Wb9sOiV73ATwN2fl_aC7MgNlREQWFdrUL_VnWktc458y5Q1HdoEjEjeYbcwkn857fxxs9D5BILF7QibIQuwixbotm5oC89EmopZb74HIMdplv-DkPK4dt8ShwrIl1-qS5D1JSTzqDEqWMMJ-ENuTNFgotBGB7Woo8LzcFYo7OEGdZbkqd7REZkRh14J83hIaxfFu66KNJgXHWr4vRCW1uJR7zSNLArXtcUxf9QDltdeNGweojSvvDGYowDpXuwNmJ4zr7Sf9BE1GLUuLmJ3vOHCk9Lb_rG9-HNqvCDG1i4CcFvpPMOkWA6_S5EGZHKv-C8MbXIu4_u9Hdt44jxCWB0XsTQ2t1h3whJxFjaKfkra8I23FFOM50um9RL09thYZmakaTN9aUHd-HhmXKXMgtWwY2uhvkWAzAIeHcZW4GLAAb67W5fTLyK4iV3sYvrqw7s1Gnl5cC_2zC8WO0h7MiTv2TDx1aWZgpHAVHAvsQPY-rbQ7IK9_RswKMpM35BFqjsbOVXsWF6VWyeAzkarHJ0zx-rp1h9azLGYwVtgjdZ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+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "python": "import numpy as np\nfrom kinex import finish\np=np.load('/tmp/points.npy');finish({str((u,v)):p[v,u].tolist() for u,v in [(175,140),(175,145),(175,155),(175,163),(175,210),(175,218),(175,221),(175,225),(108,200),(245,200)]})",
+ "description": "measure box rim and interior"
+ },
+ "call_id": "call_0b538cf057c14c61bac97c1cfb0cd058|fc_0e05b35c94578fcb016ae26c428a3c8191b797015760f0ed6f"
+ }
+ ]
+ },
+ {
+ "id": "26127599",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:42:29.520Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"\",\n \"result\": {\n \"(175, 140)\": [-0.00040722973521965106,-0.044827186153967746,0.7401296101250818],\n \"(175, 145)\": [0.00024104872438596853,-0.0448333771340384,0.721374966820128],\n \"(175, 155)\": [0.001624042771544619,-0.04480792020862767,0.6813940593653645],\n \"(175, 163)\": [0.0027909439988347273,-0.04511127723001751,0.6474165414712326],\n \"(175, 210)\": [0.00015461159643855027,-0.1537931500053472,0.6421551363302781],\n \"(175, 218)\": [-0.00027757404329852714,-0.17087271682999766,0.6418454611257971],\n \"(175, 221)\": [-0.004858741824511546,-0.21538516883598618,0.7409611222694521],\n \"(175, 225)\": [-0.004426556184774468,-0.2173418458088874,0.7269936144780211],\n \"(108, 200)\": [-0.12591254536764196,-0.17503626728740773,0.7387227986229724],\n \"(245, 200)\": [0.12582025415973105,-0.17167279655086232,0.731245401664232]\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "0e06da63",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:42:54.336Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
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+ "description": "release far shoe"
+ },
+ "call_id": "call_855bae41d79b4122a218708c9f2a6f1d|fc_0e05b35c94578fcb016ae26cab1c3c81918c8ad84d143a629f"
+ }
+ ]
+ },
+ {
+ "id": "44dba19c",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:44:15.622Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223853.744106609] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"episode ended during wait\",\n \"code\": \"operation_rejected\",\n \"details\": {\n \"operation\": \"world.wait\",\n \"type\": \"kinex_interfaces/srv/Wait\",\n \"response\": {\"success\":false,\"message\":\"episode ended during wait\",\"time_s\":13.48,\"waited_s\":0.3200000000000003}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "ef63e903",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:44:21.811Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Stopping the device**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26cb21f0481918656a0000ccd5a60\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Stopping the device**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4my1OPdBKepDEmp8HGLHxtgIAuMeajfd3aQ4xl_T4u4nvlBqm9ps0vTYN6cvyM6qB9oQ9sGbajS7X7v19YLEYMVifsbskkYRz-COPwacaaPEswvMortw2PBN3BKJS_rE4dXoakhwKv7MylYRnBAxiw9fHJBVLH7f2rwVAAjLpfTLhvZ11JNJ0uP7Ko1P5B0P0FS6-DXOf5miMIoXDg_L0IwuZqVqYaxo3N_3Vu_nAkM6htXP0y_GUOX6AeE14QHYpFHeTN0Za8oWfa2oazzcbUQMmc-Fin9kiN8RqODQ9zZAqN32yBAgGem6UWL7m90UdPA7OLU7oVDZ7EVOZ5fZpYd3VXgj9hY41I24GLbYQMPoBlBcP_xkPHB-ju46zXD2oagq4lNKHiGAafpE-twXRFgotE5WUEwndwW6Wp-6kOzubzJLyM9yDUCv6pdBGi5M8rRWZXqyFFwJ7KB_UyrwTnBc17nf2HGPlnj7CG11Bzzhp9mPhwMHYAR2whS8-KN75fh2jNmtPfwjEdJI4EM7qcPaNxyw7xRVT_gvzZwUn6R5zof2SoSJdqmlM0wwpqQ2ueFoP5-mRR53XqKoQQfwBN7YjBgZ9rEdao0Nduu-jSN5NbGJJBACqJ5SvnKWaQEb5B2pCNMCQqkZp7yf1BRvDPtPA6m32f5GdiQ9rQX-iXPkAwInkc7urD4N44adWb2a50FFA8XTOK2MmWUiExzG4W6F72vKKiXIUvie9DcFDFaPFMtH3UPP5Yg7-varl3h2SxNj9GZgTa-X6k2aX3AuWeQnPchLr1zqx59gJNLqZKo1u2LKHvMpVy9iiY0P-1Zr0Im31q6pMN3C3CMQpUTbIAnlD_8M69VAG9YMU1Si0MrnZvrdLVgSOSilZzHPj3knKo8gunqIgMPFdBY5jXxwX2pjm2gFhKu_ddalVYPiGIcRWZlpqj_qzGZOiDEZdjPVs7MewqdEGPpxIAeJziDyH8ovad32H0W_HuZ8jAdh4Paop9i3agza8USMINTMVIS36GWdwnyGc0d6x6qtdvO3eCbDyRlRSGpq7o3BtTchBsvf4_OeGX3U20Tf1F3850CBC4xvr9xhACdTro5vFEgFcCL5lxBScmjEe8poivIuwIcaR6KjkNPV3ckvL1Cn8vp3Agzrtzjrv4580VspJxPe8dLK3QkFWm3Ycfd7Mcu-DsSU9hj73ce2l9DVn2EwU0w127yiL0eIyAE7OSsxV6Q2tHEHy6wo75mpRbwri0M22dadhrwzuZvJWM01eEzMvjRCC2S_xExfqYgpIM_OQgqoh-p8oaUd7lAfxswPWqwuP-EVEg_Lfkvz4ABjwayr1O6HiKfLb_iyLRojHLhR7o-r4hVS735EFpkHej0V4Ahb149VRYklNZBY0e-dHLyoA1nnF31dZh1iYr0qvf59hT8bo0q9x2gZPzYVYIv0BDJnXi8FXr2QVEX1xSuE1UfVvRTh9aomhakO7UsczKqXB9XKiREZVmnidrxPQvtE0qsp4LRi6UR2menYgwfvAQTfOaFWHpqKFtdStV9STxs2rt-yLv-MxDg2dy6QCTGLj10EsIgBr6ZZPykLmVMmu0A99t8svxKUW4B7IanpQdF0dqrhzZfKxBOnudxbAOzPfsmaHe5njLIWvk-hFYidhpqj7M1KtWIbt2ugiE7rvyyr0Rr5jbtpnJ3SqTSCaFumnMCuD-P-uvZV-6TusMiDK3a_vTDvgArXf2xSDSSese__0XOWpKrTU9aJYPNGKV637uPQj8B9VHAofiibYk5HTn68we5k2cams2rhVo_dA4u1tee6f0QbZNZrKkuX48Bmyfiwy9FNYo2nnXYJnps7jPgX9UNOJnV4jB0aHpxPizTxdv6nmgYQuf5EjNlrr0Y9Gizmy8OA19ZhjhdRIl-r8lAI18B8JkuRHw0OLKeCyniFWjQ_JOPgsg==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "device_stop",
+ "input": {
+ "reason": "World reported episode ended during release wait; hold and inspect final measurements."
+ },
+ "call_id": "call_5daa5ef62b724ef2867e3c346d1a3544|fc_0e05b35c94578fcb016ae26cb37ab4819183bfd8faad8f7b3c"
+ }
+ ]
+ },
+ {
+ "id": "74adf0c9",
+ "role": "toolResult",
+ "tool": "device_stop",
+ "timestamp": "2026-10-28T21:44:21.914Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
+ ]
+ },
+ {
+ "id": "cd3634f3",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:44:25.100Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "devices",
+ "input": {
+ "calls": [
+ {
+ "deviceID": "head_camera",
+ "action": "image"
+ },
+ {
+ "deviceID": "left_gripper",
+ "action": "joint_state"
+ },
+ {
+ "deviceID": "right_gripper",
+ "action": "joint_state"
+ },
+ {
+ "deviceID": "world",
+ "action": "time"
+ }
+ ]
+ },
+ "call_id": "call_5a7dcfb565f84f16b427e00d4290db11|fc_0e05b35c94578fcb016ae26cb87d088191850ccbe07a34f9ff"
+ }
+ ]
+ },
+ {
+ "id": "20d111e0",
+ "role": "toolResult",
+ "tool": "devices",
+ "timestamp": "2026-10-28T21:44:25.261Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"head_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":13.48,\"frame_id\":\"head_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-hilw3rij.png\"},\n {\"deviceID\":\"left_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.9982522617686879],\"velocities\":[0.00007679601284590635],\"joint_names\":[\"left_gripper\"],\"timestamp\":13.48}},\n {\"deviceID\":\"right_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.9529129727320238],\"velocities\":[0.17699392681772058],\"joint_names\":[\"right_gripper\"],\"timestamp\":13.48}},\n {\"deviceID\":\"world\",\"action\":\"time\",\"ok\":true,\"data\":{\"clock\":{\"sec\":13,\"nanosec\":480000000}}}\n ]\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/20d111e0-1.png"
+ }
+ ]
+ },
+ {
+ "id": "f987cc8b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:45:05.154Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Refining resource memo estimates**\n\n**Recording gripper state**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0e05b35c94578fcb016ae26cbd1c0c81918256e2d03ca14b13\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Refining resource memo estimates**\"},{\"type\":\"summary_text\",\"text\":\"**Recording gripper state**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mzGEDbYxpU8BKU30oTljwjt9Jg6IHUKHRneZTLnx3NXh_sul-6hVagfMjPZ9Yx5g27iVxtmZgQFc54lqL-OkFMtUMBcM_Xkm8kecYAleHPhmyNNXjIVJV3q61GmjGkuq8S889FACTKljV6kOY6B3ve7ZVKeKYaW74kXuTLwMIRjMSkMKwg5ymo7knxB9lliRZ_13B4jDgOdp5CUl5pkoKx4Ag07szzW5FmyQjEsHpON1td9OBRvUFrfmy3HGZloW-Rpu2IZpsg6mRH1857MTdTzDI0-75Jg66y8kBBnTu64MGdQ8-tLtQQ2eyoVj5k3IFcsYKGOK4zc4upao-An_aTXLEoTpss-axp1FKSlbCaV9rlUEM30bOXX9_c-IakRkuaOtYe5SPOuFm5RuKyCtMUC3-V_xYKE3FIVP-xqQlq5SVYvlYdzN867XqfXKSr64RLZvzOuLlWsrlyydBrdkGokT8Erxe7R0JvW2uKaUIIuuhkcup4YSnTFnjSXrACWQFloXlwy0Pclc9zjI2-ixQxAlYtcebmZZB8gphpuS_IPQZoV5yQ03TvPLgLW4emswySC-8KYaW49qoGPTUO8A4XsoGADFjKqNJ1jVwUIeegoTQ1RhI64j5Pct-IYdhXd_V71uHxJz9Ej1vwrU-uuLhtmW_YTM8o9mZrUmX564rTBWUCKGaSKH75pUOX0xdKEqLOPjtOhgX57m73mHouuJ6wBio3ZKx1keE806JF_mEnKQVc3z1t6F9hAzwjFsVV0ZnGVBSmX2KUzLrS84ZaTBm9cSs9_nj3XkfGoKgyMLMHfushqrHv4ZM2AhCShtHc0pgoTO2qXi3x8mJ7chV86Ox_DXz9T1SXHHvD-FKRNKcKaIU25tYeDsSOI2y5kydRIU_r-u-o1I6cEuSVpZBfj042G1i00sViCT8jyHDFgJrw3SBR415W7bE1RfvF1jBeAnqHUin-PffgktWKdb_nN_O_X63MJlztfcPZCWzME4xJzs8E2Mu6F3Mx__oLaAewJHgK1QIaUOC5uk8w-TJZeW2qMz-cqRaVQlYIRwKgNqPjWYroAgpCvkBppzHtCG3Aocw_6SbmNDJbN8pH1yzd9agLF4MyzfaNrxf6iMq6SSxrHCDrsjDqNWKkQ-aIP_OrBYZLW9N3xZzGx4ftv2uloEganfEEX1Ytcr_9Z-gWb7Y9acGY_1-AUi3DmDcvBv3x7K_3KYgVtSbNc3TgVrs1oAb8O6Vr6t4B9MvxoAaJyRzBgpJavrWnquwCK3yyQOadU-3TPVhLpSjyZwVYSCS_3ZPLI-FtHPS8t6-42lkA332mBe3FeKILddxzPUkbOohYhIoL5rYPZNAShJ4hGk6yug34CcF1BBJ3dht2g2IXpblpdQLzafiBbOiM79epON_6qGmAsETLh9fVC16J_iU67lQ2S3rCKv3HKhGmoA44iGztqZfJnlFd_OxSFFGbeCD-yzPVcUVXCRRzBMmj1dwICZiB3oMo1uZANvFZWPGcpVAu1fCUcDlJ9zvCnAtzNTT5FWkygv1jERp9E9KV7c-DFC-d278lv5EGunQbBXy5uULSi6i45LypLMFzQ4HPKlSaHwtqFdiAqeBsIHKLhajHPNp4dd31BjJQyp0PkgWxbFiHEd2vYpVwjcW0phUNrmBabI36k-v9rrbWOtUMilXqxAb2RCGD3DzUjXOKahkC9E1zwHoWTmaPgyFIdAYOwVjeiPcVnra7ITs40dALeVnds8Pv3yE-aMyxbql7og8PkUxfK1oY40kos6ELkAax99eft4CoP-8KsNW-peSM-AQ1OT3VatOYj6juLrZHdRP-bKoLxnaTnzqXuCi2xpBRWTJF6Y5-aeKzbOVgn2gT7kTR2-uCJNA7kVwGboe-IQTy2UIvA42a0HSwfNOZvnRE95EGbxp8oJNMtwSRqfCzgMX4yFT72WjLNyL_nWqKc1qf2n7jUY9kMVC3EStWL90QLTNjSoQxbLARoSpshyFcKiI_PUXzS-Nc6JOLUe6mUY8K1ompw_rdiFPTW6-oYE8KqcC2CAil2XQvsdyH5Vf9xTcrF1SNJ1M4QvzmePc2PD8F-IBfzXoEmnYREq0qVzPPLp_CH84-W1f0MRjLWUi8fPUfKCU1zQDjM1XvZPtAm4AALan2f7LGtrhjwMA0US1Bgq17L2_BFe1qNcXdDTB1khPSUZUTLduV82MirNu-3mLEwFkM1-i7lxpUpuh8ziUms5R80ddYSNvzokR2f7D-Y109AKCh_9tjZw_KNC7yt5FkJkCpyJh3pbQjq8aAMPIx4xNRlvDJZFuGy1Dz16hQCrsbRSBi2blgMcMQSQ0P9vICD2GgADrDYUsb92OUG0vfSFS_-SXNZWVBskf1FUSDFxGqOwD02q0d3ScP10C6rAdWYzO8OdvNQlsCeIYHY276Iif1SfkJixAMS57ogoDCqLRkdhX4QPP0vwb9Gu1RvXLcwrEwJSKpRyyI-c069uZTtN7q5n-mKrM33hKY08QubHxozhuy3z4QPosctX91A0OcY1ZWq5xPS037RKAsJ78pBvLcWJ5B1ODdwiOkhsqe1Vq_KxxvdHTaK1jy8KyLoKoWUKQFbxnvQLF8w-X3qfb3P5H453TiV8ylL1TiVJ9-a2SGNh1Y_PEuIS6cekxR19u7K_iGUKH91exHb5-HOSViGpM-IZFIR4bHvlGFV-rHRxizFyVXlaCRhNZA9FQ7zPpAmGud7-T7NB3JVsu3fTx5LDERVNS2f6c4zHJE8UPRTrXom4luyLFM93sda0540_0-FaCb--mA94LIv4h5TeBdDS9DJThG-93X9f_zc10IjHQQbFGja9Vil71zNBRU93DJeqlrxtr6aSlLozOty7EJIIQ60JpBfcJ4fJ2AqD7yzuoLIm17wqTZ5h2qclOIlx86JO88OjVypjWm6NCXgI8ulJcGywS4C1t1aq-W7bD2Z7DmWF8gSH4iTr0wS5x0QBNqaib9ITqd1g0w966ms9E5pZyK0KscK6rQdIGhaKhojvKJvaqiW68JsTkExK4APcaG8hfWey7a18rHWpHuWiogyyEC9B-qtHx9ColM7M0S70FHUAKDji2L_f9kWBPTOPAXlTR2QU_K_z0b0R7iw7GFeJA4qzKY0g2ipI5ALrdDFsO7A9N7s842tjJjBptU1XXecTalQD2ZyYLXAP7C8pwOI0RiI3c29BELo5gt4nxg1dZUAEnaV0fOWb2Ri4Vfx5KLRXFi5ZeG19WPoh5NXPnlDvWL8Ng3NGFQxzx6QUJDZCuLFVL4d3k1ziJn-Y-8WQ7aO-WzQGjRtKLHyGs_M9xEwFoYq6ith0jilg6BxCYjMxiFFT08tBVYKkoWTUdXTtJcwE2Q0PiaKZFUqXoutit2Rnd7mIowyLyeq73bLDIIJTIzznsGDNRf8nTbzvITvuAKMU9TJQv9AYT38bfo5Eu_xq7ORK5eiCLoRyTu1NkJepIYITzMGhT_L1gLegrccGfSFI4JKk6qJHtgrBl_MIyUu6lVrJ_v3CZBTliratMkZhmBCu6fVaTWPSPEBlWisN7oXdoMl48P3VZleZcQFSEcruNh7zc7xqqL9jrLF1dQKWChDJLs8AIH-P3n1v5b18LUY38w5uTYbToiTw58SqBGvm8YI9jRVWow9SfR2sAcS6k0UuXVkYgRYMpe7QPB0MWbQczlSvvvc5O56K4Vn-TxDIKvxa1rrhk5b3fktHTfAigEXD1EK3gwK20kc_P2j5vlMvP3SUk1QQ-gHB780ZZDd536mWHTdonzin78zSC3zQly4ClCyBX20mROdEewpV9EfFfcQjWBomYMorkLWlZcfFVF_-mgV7CcwwmDcrxu4DB628RkdZL4GKmK9JhW9_BULxzYXay3VNw-8U2zL8o3EJ-QegCq_jxAc8x9BZfzKiLzx73DdIrkIn3kKLZURO2gBu8RgFl4UwGyvG20nCbldOzjUGTvYtLacB-L6VsRUZCukOAkxB-de_6P8uBgjYtYb_OX43VZXOY-atBj3K85O5P1PvJWaPxwl3Txum0wRGOjXFpXS2uJJ2cugePfFOPMR_gBVVO5zuAbA5dT1yylcnetFcljweQZDIVd_LTWlFOEtwS28Rb9zhuY1UsJB86Tik_cvN88xedxlZvi-MqriFMti2Rp0RYR0OxDMSXjLYCmg53lmb_-DFLj_m9IUBuvnKU5crhSCg8W251QlQr7LOFStxRTS9q4p5p-xlWVXMFiCXGhU4THriIQgVqFFNy3_5qFN-L4yXvdZg9FScoPsoX1RqyDa\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/memos/dual_shoes.md",
+ "content": "# RoboTwin dual shoes / ALOHA AgileX\n\nPublic interface: read harness.md and refreshed profiles each episode; load world, both arms/grippers, head_camera. Native period 0.04 s, stepped world.wait only. Use typed kinex.communication operations. Do not reset or inspect private simulator state.\n\nReusable tool: `.kinex/tools/dual_shoes.py` accepts world-frame TCP targets, duration/settle, normalized grip targets, and dry_run. Uses measured joint state, calibrated base transforms, 0.12 m flange-to-TCP translation, Cartesian interpolation/Slerp and continuous seeded IK. Publishes both trajectories before one sequential wait. Returns measured TCP/grips and camera. Read schemas before using. JointModel.fk/ik require list, not ROS array; camera_frame returns (image,depth).\n\nPerception: paired head depth mm -> optical coordinates using profile intrinsics -> world via camera mount. In observed scene table z=.640, box bottom .642, rim .740, inner x about [-.125,.130], y[-.215,-.045]. Shoes length ~.22 m, width .07 m. Re-measure positions each scene. Initial left shoe pointed roughly [-.435,.9005,0], right [.10,.995,0]. Grasp across width at center: downward TCP x axis; local z opposite shoe toe direction; local y=cross(z,x). Grasp TCP z=.695 worked, lift to .865. Both measured grips stalled ~.82-.84 and visual lift confirmed shoes attached (stall alone is not evidence).\n\nPlace tips world -X using quaternion xyzw [0,.70710678,0,.70710678]. Near row for initially left shoe: observed target TCP [.003,-.171,.795]. Far row: [.003,-.087,.795]. Grasp offsets kept soles roughly .055 below TCP. Release just above rim: gripper fingers cannot descend to floor in narrow box without contacting walls. Shoe falls flat into box. Place sequentially; keep other held shoe high/outside, then withdraw released arm up/outward while bringing other shoe above far row. Example left clearance [-.23,-.18,.94]. Waits .3-.4 s after trajectories reduce tracking error; verify actual state. Near shoe was visibly flat, toe left, before placing far shoe.\n\nWorld can terminate during a release wait before requested duration. A rejected/interrupted wait is NOT proof of success. Stop and inspect final images/state; do not keep advancing terminal world. Observed terminal at t=13.48 during second release (337 frames): image showed both shoes flat inside box with tips left and initially left shoe nearer robot. Open commands had been sent to both; final openings left .9983 and right .9529. Native verdict is owner-only; do not claim it. Tool currently surfaces rejected wait as error, so final observation requires separate device reads.\n"
+ },
+ "call_id": "call_ce2bbe8cfcac48fa9a6cbaea14bb18f6|fc_0e05b35c94578fcb016ae26cc583608191b8162570ad00b3ce"
+ }
+ ]
+ },
+ {
+ "id": "3184d722",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:45:05.157Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/memos/dual_shoes.md"
+ }
+ ]
+ },
+ {
+ "id": "6e5bebe3",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:45:09.896Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Both shoes appear flat in the box, tips pointing left, with the initially left shoe nearer the robot. Both grippers were commanded open. The episode ended during final release; the native verdict remains unconfirmed.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0e05b35c94578fcb016ae26ce4b7d48191859c9b4ca65ee66a\",\"phase\":\"final_answer\"}"
+ }
+ ]
+ }
+]
diff --git a/experiments/robotwin-native/kinex-2/usage.json b/experiments/robotwin-native/kinex-2/usage.json
new file mode 100644
index 0000000000000000000000000000000000000000..72bca3ed033bda3f225ed594493d352fff3e8cd6
--- /dev/null
+++ b/experiments/robotwin-native/kinex-2/usage.json
@@ -0,0 +1,281 @@
+{
+ "accounting": "reported-responses",
+ "audit_complete": true,
+ "audit_source": "Provider terminal response usage",
+ "cache_hit_rate": 0.9580669562982812,
+ "cache_read_input_tokens": 794112,
+ "cache_reported_input_tokens": 828869,
+ "cache_write_basis": "provider-reported",
+ "cache_write_input_tokens": 0,
+ "cache_write_reported_input_tokens": 828869,
+ "cached_input_tokens": 794112,
+ "cost_usd": null,
+ "fresh_input_tokens": 34757,
+ "harbor_mismatches": {},
+ "input_breakdown_complete": true,
+ "input_tokens": 828869,
+ "known_cache_write_input_tokens": 0,
+ "known_cached_input_tokens": 794112,
+ "known_fresh_input_tokens": 34757,
+ "known_input_tokens": 828869,
+ "known_output_tokens": 6737,
+ "known_reasoning_output_tokens": 1832,
+ "output_tokens": 6737,
+ "parser": "harbor/0.22.0",
+ "reasoning_output_tokens": 1832,
+ "reasoning_reported_output_tokens": 6737,
+ "rejected_attempts": 0,
+ "reported_responses": {
+ "cache_reported_input_tokens": 33,
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diff --git a/experiments/robotwin-native/kinex-2/vla-io.json b/experiments/robotwin-native/kinex-2/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..250d7787ec0f8bfa2091df6ed87e28970cb2b3d2
--- /dev/null
+++ b/experiments/robotwin-native/kinex-2/vla-io.json
@@ -0,0 +1,43 @@
+{
+ "calls": [],
+ "coverage": {
+ "recorded_inputs": 0,
+ "recorded_outputs": 0,
+ "kinex_calls_associated": 0,
+ "original_temporary_image_paths_recorded": false,
+ "normalized_action_tensor_recorded": false,
+ "processor_tensors_recorded": false
+ },
+ "contract": {
+ "request": "policy.infer(obs, task). obs contains three ordered RGB image files; no joint state or agent conversation is sent to the VLA.",
+ "image_preprocessing": "RGB conversion, then OpenCV INTER_AREA resize to 224 x 224. Model images shown here are reconstructed from retained input pixels with the executed preprocessing.",
+ "request_paths": "The logger replaced temporary input filenames with retained image-copy paths. Original temporary path strings were not retained.",
+ "service_response": "actions, inference_s and call_id are reconstructed exactly from the logged values and the executed handler return. raw_actions is internal diagnostic data and is not returned to Kinex.",
+ "agent_response": "Kinex helpers.run_policy consumes the action array and returns actions_submitted, duration_s and ik_failure. The language agent sees the exec tool result below, including feedback and images selected by its own code.",
+ "output_layout": [
+ "left_joint_1",
+ "left_joint_2",
+ "left_joint_3",
+ "left_joint_4",
+ "left_joint_5",
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+ "right_joint_2",
+ "right_joint_3",
+ "right_joint_4",
+ "right_joint_5",
+ "right_joint_6",
+ "right_gripper"
+ ],
+ "diagnostic_layout": "Left 6 joints, right 6 joints, left opening, right opening. Gripper conversion: 1 - 2 * clip(opening, 0, 1).",
+ "not_recorded": [
+ "normalized action tensor before denormalization",
+ "backbone processor tensors",
+ "exact original temporary filename strings"
+ ],
+ "backbone_prompt": "Reconstructed from the executed QwenOFT and QWen3 implementations; 16 action query markers are appended by the model, not by Kinex.",
+ "model_metadata": null,
+ "executed_sources": "policy-contract/sources.json"
+ }
+}
diff --git a/experiments/robotwin-native/kinex-3/analysis.json b/experiments/robotwin-native/kinex-3/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..c04896838656c3c18e722850290336c82dbe5f3a
--- /dev/null
+++ b/experiments/robotwin-native/kinex-3/analysis.json
@@ -0,0 +1,3 @@
+{
+ "observed": "Kinex wrote a measured Cartesian manipulation tool, picked and deposited the bottles sequentially, and reached native success at control frame 1,354."
+}
diff --git a/experiments/robotwin-native/kinex-3/artifact-index.json b/experiments/robotwin-native/kinex-3/artifact-index.json
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index 0000000000000000000000000000000000000000..d9cb80e57785d67d6c91b719e4da63e3c23a1c33
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diff --git a/experiments/robotwin-native/kinex-3/detail.json b/experiments/robotwin-native/kinex-3/detail.json
index 4ad41b5dec9814738de47de27181fd442e18ef66..6b5dedb58ab60dfedf8aa2f43c66774a4cec173f 100644
--- a/experiments/robotwin-native/kinex-3/detail.json
+++ b/experiments/robotwin-native/kinex-3/detail.json
@@ -404,8 +404,14 @@
"usage_source": "provider-raw"
},
"cost_note": "API equivalent sums the native Pi session cost estimates. Subscription billing is not reported.",
- "media_note": "All three native views and every frame retained. Frame timing is unchanged; playback starts at zero.",
+ "media_note": "Three 960 x 720 views side by side; every native sample once at 4x simulation speed.",
"artifacts": [
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+ "path": "experiments/robotwin-native/kinex-3/analysis.json",
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+ "sha256": "716ca9c2ae3c0c33f8bd9731cfb03f69e670f39b6aebd93340345cc569b221bb"
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{
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"path": "experiments/robotwin-native/kinex-3/artifacts.json",
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"sha256": "7cfa89f6915dd66f0aead3d4ef82e1a961f6ad52eca698ee744e3b2c88e618a9"
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+ "sha256": "6bd4f2708c7cc5acb8b2ff01e9ee0b80d30a4b59be18cf8332f071fdbf54fa29"
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"path": "experiments/robotwin-native/kinex-3/workspace/.kinex/devices/head_camera/profile.yaml",
diff --git a/experiments/robotwin-native/kinex-3/presentation/encode.log b/experiments/robotwin-native/kinex-3/presentation/encode.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/experiments/robotwin-native/kinex-3/presentation/frame-comparison.jsonl b/experiments/robotwin-native/kinex-3/presentation/frame-comparison.jsonl
new file mode 100644
index 0000000000000000000000000000000000000000..b8f899e732a2bd1f8b8be782e6972689bdabe99c
--- /dev/null
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diff --git a/experiments/robotwin-native/kinex-3/presentation/frame-mapping.json b/experiments/robotwin-native/kinex-3/presentation/frame-mapping.json
new file mode 100644
index 0000000000000000000000000000000000000000..aa7790db784ab9e1ed8264a1cddb1ab47aff18e7
--- /dev/null
+++ b/experiments/robotwin-native/kinex-3/presentation/frame-mapping.json
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diff --git a/experiments/robotwin-native/kinex-3/presentation/media-validation.json b/experiments/robotwin-native/kinex-3/presentation/media-validation.json
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index 0000000000000000000000000000000000000000..b06a8785237b6110411fd24947152e109db62e94
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+ "schema": "rlebench/native-camera-media/3",
+ "passed": true,
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+ "width": 2880,
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+ "minimum_frame_psnr_db": 42.00768830044577,
+ "maximum_frame_rgb_mae": 1.432692289352417,
+ "decode_ok": true,
+ "pts_verified": true,
+ "playback_kind": "simulation_time",
+ "resolution_kind": "independent_720_high",
+ "agent_observation_video": false,
+ "camera_views": [
+ {
+ "name": "third_person",
+ "width": 960,
+ "height": 720,
+ "channel": "spectator"
+ },
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+ "height": 720,
+ "channel": "spectator"
+ }
+ ],
+ "coverage_basis": "Every scheduled 10 Hz control-boundary sample, plus the terminal state.",
+ "frame_mapping": "Each captured sample exactly once; no appended or held frames.",
+ "sampling_note": "Samples follow the native simulation clock; model thinking adds no footage.",
+ "scope": "Live owner-only spectator views; no replay, rerender, upscaling or invented frames.",
+ "recording": {
+ "schema": "rosbridge/recording/1",
+ "run_id": "c3ff59536ab0",
+ "task": "robotwin/put-bottles-dustbin-aloha-agilex",
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+ ],
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+ "topics": [],
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+ }
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+ "run_id": "c3ff59536ab0",
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index 0000000000000000000000000000000000000000..0f1967104a5b94938248a6217096852e7eff7a42
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+{
+ "max_steps": 1700,
+ "seed": 0,
+ "episodes": 1,
+ "control_frequency_hz": 25,
+ "provider": "rosbridge",
+ "realtime": false,
+ "stop_on_success": true
+}
diff --git a/experiments/robotwin-native/kinex-3/transcript.json b/experiments/robotwin-native/kinex-3/transcript.json
new file mode 100644
index 0000000000000000000000000000000000000000..c7a570d937711a0755d5af779ea8dd07fbff97cb
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+++ b/experiments/robotwin-native/kinex-3/transcript.json
@@ -0,0 +1,2572 @@
+[
+ {
+ "id": "d86b90dc",
+ "role": "system",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:23.264Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ""
+ }
+ ]
+ },
+ {
+ "id": "baa72b9a",
+ "role": "user",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:23.264Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "# Task: robotwin/put-bottles-dustbin-aloha-agilex\n\nuse arms to grab the bottles and put them into the dustbin to the left of the table\n\n## Work to do\n\nSolve the task efficiently using the running rosbridge environment. Follow the\ntask instruction above, including its completion requirements. Read `harness.md`\nand the device profiles for public interfaces, units and calibrated frames.\nReuse your saved tools, skills, and memos.\n\n## Limits\n\nYou have 1700 native action frames. The execution mode is `stepped`: physics is\nfrozen while idle. Use `world.wait` with `duration_s` to advance the native clock.\nJoint targets are ROS JointTrajectory messages; gripper targets use the units\ndeclared in their profiles. Reads and command publication do not advance physics.\nWaits are sequential; concurrent waits are rejected. A command or elapsed time\ndoes not prove arrival; inspect measured feedback. Device stop holds the device\nwithout ending the episode. The safety timeout is 28800 seconds.\nDo not launch or reset a simulation.\n\n## Completion\n\nReturn when finished. The owner finalizes the episode and reads its native\nverdict. An interrupted or rejected wait does not establish task success. The\nnative step limit stops physics even if your requested wait is longer.\n\n## Saved resources\n\nMaintain reusable code in `.kinex/tools/`, skills in `.kinex/skills/`, and concise working notes\nin `.kinex/memos/`. Improve existing files in place as you learn, replacing outdated\ncontent. Create a new file only when no existing resource fits; do not create\nper-attempt reflections or numbered copies. These files persist across fresh\nconversations. Update them before finishing your response.\n\n## Robot and device access\n\nUse Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place."
+ }
+ ]
+ },
+ {
+ "id": "0398c2aa",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:25.910Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "ls",
+ "input": {
+ "path": "/workspace"
+ },
+ "call_id": "call_bc30fb8bf4f94fd8b419ada61ba9c495|fc_03880fcdb65294d8016ae26da951048192a45a47ab0d529d47"
+ }
+ ]
+ },
+ {
+ "id": "9ff17a7d",
+ "role": "toolResult",
+ "tool": "ls",
+ "timestamp": "2026-10-28T21:48:25.917Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ".kinex/\nharness.md\ninstruction.md"
+ }
+ ]
+ },
+ {
+ "id": "db44cfea",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:29.788Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/workspace/harness.md",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_878b9e39f63649cfb186f0f49feaca5d|fc_03880fcdb65294d8016ae26daced9881929db63b0c45ac2b84"
+ }
+ ]
+ },
+ {
+ "id": "3f4014f8",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:48:29.793Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Use Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place.\n"
+ }
+ ]
+ },
+ {
+ "id": "1a9ed4b1",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:32.349Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "find",
+ "input": {
+ "pattern": "**/*",
+ "path": "/workspace/.kinex",
+ "limit": 150
+ },
+ "call_id": "call_ed9eab7888164c59b45bb5130fd938dd|fc_03880fcdb65294d8016ae26dafe5288192b6bd79b67294c68a"
+ }
+ ]
+ },
+ {
+ "id": "113fa28a",
+ "role": "toolResult",
+ "tool": "find",
+ "timestamp": "2026-10-28T21:48:32.378Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": 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results limit reached. Use limit=300 for more, or refine pattern]"
+ }
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+ },
+ {
+ "id": "5c9b060a",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:48:36.946Z",
+ "error": false,
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+ "path": ".kinex/devices/left_gripper/profile.yaml",
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+ "path": ".kinex/devices/head_camera/profile.yaml",
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+ "timestamp": "2026-10-28T21:48:36.951Z",
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+ "text": "identity:\n id: robotwin-aloha-agilex\n name: RoboTwin ALOHA AgileX\n kind: arm\n model: ALOHA AgileX (dual ARX5)\n source: user\ndevices:\n source: user\nsafety:\n source: user\n max_joint_velocity: null\n max_cartesian_velocity: null\n keep_out_zones: []\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\n"
+ }
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+ "id": "d322cc9b",
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+ "tool": "read",
+ "timestamp": "2026-10-28T21:48:36.951Z",
+ "error": false,
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+ {
+ "type": "text",
+ "text": "name: world\nruntime:\n domain_id: 83\n observation: time\n nodes: []\n ready_timeout_s: 30\noperations:\n time:\n description: Authoritative world clock\n transport: topic\n direction: output\n endpoint: /clock\n type: rosgraph_msgs/msg/Clock\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n wait:\n description: Advance or await duration_s of world time (finite and nonnegative).\n Zero is an observation barrier. Waits are sequential; one requested while another\n is pending is rejected. A terminal episode rejects further progression without\n exposing benchmark results.\n transport: service\n direction: input\n endpoint: /world/wait\n type: kinex_interfaces/srv/Wait\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 120\n stop:\n description: Cancel the pending wait.\n transport: service\n direction: input\n endpoint: /world/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: world\ndescription: Scene reference and authoritative world clock of the RoboTwin 2.0 table.\n Kinex supplies frame transforms independently. This device exposes no task instructions\n or evaluator results.\nsource: default\ncalibrated_at: null\nmethod: unknown\nbounds: null\nsurfaces: []\nframes:\n base:\n parent: null\n translation_m: null\n rotation_xyzw: null\n"
+ }
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+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:48:36.951Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: left_arm\nruntime:\n domain_id: 83\n nodes:\n - entry: links.py\n factory: create\n ready_timeout_s: 30\noperations:\n joint_state:\n description: Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4,\n fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition\n stamp; do not infer motion completion from a sent command.\n transport: topic\n direction: output\n endpoint: /left_arm/joint_state\n type: sensor_msgs/msg/JointState\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n joint_target:\n description: Joint trajectory over all 6 arm joints in radians, timed from receipt\n by strictly increasing time_from_start and finishing within 120 seconds; velocities,\n accelerations and effort must be empty. A zero header stamp selects now; a nonzero\n stamp must not start in the past. Points are absolute native joint positions,\n linearly interpolated at the native control period. Replacement clears pending\n references; invalid trajectories are ignored, so verify measured joint_state.\n transport: topic\n direction: input\n endpoint: /left_arm/joint_target\n type: trajectory_msgs/msg/JointTrajectory\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n stop:\n description: Stop arm motion and hold the measured posture.\n transport: service\n direction: input\n endpoint: /left_arm/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: joint\ndescription: ARX5 six-joint left arm of the RoboTwin ALOHA AgileX. Geometry is the\n sibling arm.urdf with flange (fl_link6) as the tip link; measured links are on TF\n as left_arm//base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
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+ "id": "6306099c",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:49:09.222Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
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+ },
+ {
+ "id": "84a74e83",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:49:17.718Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure scene and inspect schemas",
+ "python": "import asyncio\nimport numpy as np\nfrom kinex import communication, helpers, runtime, finish\nasync def main():\n async with communication() as io:\n frame=await helpers.camera_frame(io,'head_camera')\n d=helpers.image_array(frame['depth'])\n pts=[]\n for u,v in [(70,80),(61,42),(78,107),(201,30),(263,48),(275,15),(160,170),(20,95),(10,65)]:\n z=float(d[v,u])*.001\n p=[(u-159.5)*z/358.6421814,(v-119.5)*z/358.6421814,z,0,0,0,1]\n w=await helpers.transform_pose(io,p,'head_camera:base','world:base')\n pts.append({'uv':[u,v],'world':w[:3],'depth':z})\n states={}\n for n in ['left_arm','right_arm']:\n async with io.subscribe(n+'.joint_state') as s: m=await s.next(timeout_s=10)\n states[n]={'q':list(m.position),'tcp':await helpers.transform_pose(io,[.12,0,0,0,0,0,1],n+':flange','world:base')}\n finish({'points':pts,'states':states,'schemas':{n:runtime.describe(n) for n in ['left_arm.joint_target','left_gripper.target','world.wait']}})\nasyncio.run(main())"
+ },
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+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:49:19.817Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224159.011935530] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"Traceback (most recent call last):\\n File \\\"\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 19, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 7, in main\\nTypeError: tuple indices must be integers or slices, not str\"\n}"
+ }
+ ]
+ },
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+ "role": "assistant",
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+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
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+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "d13b3f67",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:49:32.523Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure bottle positions",
+ "python": "import asyncio\nfrom kinex import communication, helpers, runtime, finish\nasync def main():\n async with communication() as io:\n image,depth=await helpers.camera_frame(io,'head_camera')\n d=helpers.image_array(depth)\n pts=[]\n for u,v in [(70,80),(61,42),(78,107),(201,30),(263,48),(275,15),(160,170),(20,95),(10,65)]:\n z=float(d[v,u])*.001\n p=[(u-159.5)*z/358.6421814,(v-119.5)*z/358.6421814,z,0,0,0,1]\n w=await helpers.transform_pose(io,p,'head_camera:base','world:base')\n pts.append({'uv':[u,v],'world':w[:3],'depth':z})\n states={}\n for n in ['left_arm','right_arm']:\n async with io.subscribe(n+'.joint_state') as s: m=await s.next(timeout_s=10)\n states[n]={'q':list(m.position),'tcp':await helpers.transform_pose(io,[.12,0,0,0,0,0,1],n+':flange','world:base')}\n finish({'points':pts,'states':states,'schemas':{n:runtime.describe(n) for n in ['left_arm.joint_target','left_gripper.target','world.wait']}})\nasyncio.run(main())"
+ },
+ "call_id": "call_e5ff0661f776449e803aa94caf102aa0|fc_03880fcdb65294d8016ae26de88d7c819296f7ed199064f5d2"
+ }
+ ]
+ },
+ {
+ "id": "17e9766e",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:49:34.430Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224173.802050693] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"points\": [{\"uv\":[70,80],\"world\":[-0.19695410638592586,0.004840793255465603,0.8648806102948801],\"depth\":0.661},{\"uv\":[61,42],\"world\":[-0.19843608488027142,0.01836181260217995,0.9437713751659849],\"depth\":0.606},{\"uv\":[78,107],\"world\":[-0.19720784117987777,0.00647091530623034,0.7836032015382537],\"depth\":0.727},{\"uv\":[201,30],\"world\":[0.05952994588289075,0.18251674300724796,0.8356375733823433],\"depth\":0.791},{\"uv\":[263,48],\"world\":[0.17520652312780038,0.09531415164087742,0.8614856295206998],\"depth\":0.718},{\"uv\":[275,15],\"world\":[0.1815178275905498,0.10234625219325044,0.9355097052456853],\"depth\":0.663},{\"uv\":[160,170],\"world\":[-0.03103803993853389,-0.11372648082994058,0.7397051536755269],\"depth\":0.6900000000000001},{\"uv\":[20,95],\"world\":[-0.4427492319227125,0.24131101888369177,0.5484832795119379],\"depth\":1.056},{\"uv\":[10,65],\"world\":[-0.43384341948444355,0.24559314590548487,0.6666948752399482],\"depth\":0.964}],\n \"states\": {\"left_arm\":{\"q\":[3.7421762044687057e-7,-0.000003416102799747023,0.000009044338185049128,-2.5705126915909204e-8,-0.0000020763914108101744,7.544119284830231e-7],\"tcp\":[-0.30032403719682815,-0.19382880994801913,0.9420051083628493,-5.304990567434886e-7,-0.000009308971204628978,0.7141433685930687,0.6999994635766562]},\"right_arm\":{\"q\":[3.727569151124044e-7,-0.0000034167196645285003,0.000009045151273312513,-2.5587102214785773e-8,-0.0000020741485968756024,7.532827339673531e-7],\"tcp\":[0.3052327434365579,-0.19280673228662837,0.9410048642737745,-6.068416298149924e-7,-0.000009277349876493806,0.7106343746258521,0.7035615008751448]}},\n \"schemas\": {\"left_arm.joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"joint_names\":\"sequence\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"left_gripper.target\":{\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\"world.wait\":{\"description\":\"Advance or await duration_s of world time (finite and nonnegative). Zero is an observation barrier. Waits are sequential; one requested while another is pending is rejected. A terminal episode rejects further progression without exposing benchmark results.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/world/wait\",\"type\":\"kinex_interfaces/srv/Wait\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"duration_s\":\"double\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"time_s\":\"double\",\"waited_s\":\"double\"},\"definitions\":{}}}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "e8af5c83",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:49:51.670Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Planning yellow bottle grasp**\n\n**Reading joint options**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26df0ba0481928f6c0ec056997090\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning yellow bottle grasp**\"},{\"type\":\"summary_text\",\"text\":\"**Reading joint options**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m3_4wgSvLhrMFhyO2QdbR12oA4-PBvBHH5LnSYf2QHKNDsrLeUQnvGy4MIFsTNlPrm8nmkw5mTISikR1_UMLujFNs-nsMWaXLO78mmazjg7S2vp2orbQxBeBlBdid8_medDyn9pNW6XQ22fvgJEmtuFsu8T4jKGESZb6kPWzuNz1bm9ExF_TTmxs50K3PKeRKhtKrHssBTsi9ziivT3FCWAkANllkl5RYVo_xn-WWoeOpEmGZopi-aTV5QYMQC2Y4YU-0IjSF7aAKLlfTV8XvZCMHb2X_Y2jv_ZVfaIK5oYbs8jI_XdMEgMtTc4trlrAnju0YUXNFsAfStyt5FHeZb7Bk56-SfjHS2l0yafZwbFkgn09rWwR24Oia6jHdawqO6yiHrhayCaQ_m-tVSRLn9uHvsdrlKFDHK91CBxvgWa3thUSsCqRv8lFcFyPkoX8B_m8lUsnDphXRTqF4bq2Nj7GNPqh3H0GXBbN940vN7FNmcDktTusHDT1otNDKr5jCunbiogT7V1KlrFto8sTyjQ7kzv22OGkiS6kgPyH5WSslk4RNEi4Jm-MSwcYAnWxqUFtAuaS9wuB-RL9Xk8_zw483UciXkre37G2FMQodx3yZEZUPkvnPvSqrPNQ5WwPH-U7NuJKlRyt6XYJCrj6UNqRaEcicmWTQr1CiyovbHtLVnXGI5TC976u4iD8NXYa4_Yd82u8IsORYxnHA71glr0kQo1sTNVeewQQns5N4ZCITX86peGMNIO0GDz6nckoPU_P2P9OHkFX7YGUNjesKs_wxyUFN9KJKNmgsHgiYyEcvfj3ZTXEvARqmRxJsJo2WDlG7Ye5BHD15D629187Ns_jEOI_nNJsm2jPN8BXCgepwOGfSuzDFVIw1kWsYe0b-MWTSCnirTeOw2HJedpBCvyFPn8pi5HQuP4r2EaCtIgPzZaWc6lce88uEp_3DWBNpdx7OLZtBOSPQTWhtop9nTPTBOcoELDZ64n6TW8lmnTBJWcMOq-mXtcC7Z-NpjNqWOAAfxyQ4fRKaIOlIsqxttQPNgpi7eYlTMJNQJhI9oYT9TkfRRBOVcpKx2HcNWINFX2r6yqewXy0BsyhYALKghomxibnE2yprn2h8pbrldpRCys3XBXtF4QLQiOlP4bKo21UpG-v9a9_flJotB-wFDiFG_SDxK8kDvb7y9BBbD4nvk70elWiiGPn6VdnvcBfV9LAvkGsqdXlkg3yyhvE4PY2ekSwWlKJm-s1qI2MKF-2dJ22qqA-OApPS6YFOBSoNsN-UQwLAwHWIUIxpsF3cungzVRawvnGWCamQFcvQB5ZWBUIbflJf9cHzI63_uRPRMz0qCIElfohLQbIlqYobtPuswy2xGpYCn8pZFvzspByjLRj04JPz9VqWvBQD-pTJs51jBfUAPDyuQVjSjWS6yBFSgI1p6Q-FBdN_HaEHfdl6CUet8uhcJWzIBIesXgXt1oAlzt7K8j95zBC2Zao2Wi7Bo-iZ45U9vb43qLZ6FYxPj2zrg_iDvRoIjETV4CstQJr1wRMX7Kpof328m7WUMMxalMLq-alZsmcX9msRdzp5_-tDAzjEAnVDR26IfE6pGBy9NbeF49DKDM4W0ZDRQIem4ygAXRxahv87DN-wt9nGa4uiS1t2OPZbCaVmFKbUs-VBA4d-f9gA3Anx5jFIrBNNiAXkM8z9or8RLSITVc1hlJNkkQiGETHRrfi-zbfoU-0QFMoxEnYcRAEUxpfL2U4WOBdq6GOW3VFtwIB6yyY3TTPaTHbbKozogVtqCSuVV1KKrzdb-fkymQLT1PcuOt7wrzfFsp_gszf0aTFvC1KvO-XfYRbw5CE1bSBJD3IynzDY8l9_e9injt8HOtvQT4JX98z8mZlaS-AkYL3OnhfCPfi4F2p9DH20YGZ6o7oxjRVbzx_1RcWqFuryWUk1R6KlzCZKOT5ftIbagsxOcWbPGdGQaaNzuhp-j-LOUFZ3haJGvRcYnpcMis003l-nww9mFLtsKHouP8Y9EGPYkMk2ImNDesuEl7Bt4ccIMEx-TLHf8CWEVJEsIuCa6Yzn0WXSOzcXBQDxhg51QNN_uSlNG0kbvVaeBuDrmUSWzy38g9bYyCl0ff1wf2wInQhv_ypx3fbLdp3ikhLXGJcO7k8JQo4AN171jGVjoAhsN_fyZi4u4QBdKhnaj0vpeGu7CrNk0J7n8XyWafsjILrrxP-tUxRvF1eyihvPS-uTrq9ytCYt1WrKc1MN0Phr_fSXPItogWl8DqYKDaSbKx0XNuUQioGAPmRZdMz4F4Q-6vcaxxtrSFHQ2gNz84qGLFT4d_Nt5261eyKB2fmlMOFDLSm_AvSktC4cbaw4vIwt8ZDg1uXJSq0xo4pkrlnqfmvRAQZ0_gmGLk_c0_zKMxNu3uQACN2VG3pjO20dX_YenZfA-f35zGgYoCJm-fb8g4eJiRvxr0YOSDX7KPgS0foJzBMqXj6p6J3Rm_Vi-APvbYpBN3Alhl8wo4e5FMiEtrooNv5wRP403E8Ht7C_fUlWrntmHwIr4auuMlrbCzxH877cThyl9OeFwrW_n7mF4j4evNjeKP0uxxeX5alADGfXOddc-2KzUwdksqZqiVILUns16vP_Ktmr0K1ft_gvGOsmtlsJB4dsVG69EvuWdn9Pf7D1VDcSmB5oQJ99y7-OY2d7YS5pD-kYCtVc_wUCm4n6ZRloW6kPsrIW34i8oP26SLla1wuIgMOPTL18po0llVqVwTAl7YfLEWV8-E_eyteu6xQxa5TIIy7ZBQS3RNZA8iLStSem-bHWuwSY8QXY9gILneQxm8CDwVhsFXw-I6HzsZ6Z69CLP0LwGpLkcuZ162eNH-uLVqHaxkou7Ic3cO_PgPHL11ukwJg_V26H7ZNJv61CylARr_eSp7C0UK6EsrDbtT_TMKtP5wgQjy2YVoRoBQd3XxpWLxr7FtebkezR0jKM6dK2BtdY5H3kEYXMcB7qwuz2LZDd-IdECoV-fap3qxdY6OE57A5wkCdwRlnPxXUuw5psR2t4UNzceSDVtWa9sQcZPA6a1CIaXd6IFirrPfB7xH_kRuJnNLe8ISnTCGeYSbedlTdYepUjYZnWBcnGBehFPIhduH6zUjF-TscDJ3KBEYxHq7oXG9lPdSST8p2Vz-UyWUq2DZOT8XI_2nRJbSQc7a8zQKN2bI5hGF6oQE7dDI5LOwYOgA5_WmP_2DmlDFkwfOTr9FYtcsMcf7bT5BpGcpCXBrujGi48vf0_B-OApdMAetm5dMuk_Lfmt8FRmwGDADNTkgKnten-1XeBOvUy-5BCvtAKR2tewPo9JOchVhi4ECx4FKjjg1dmzKbiDbVS7_iuapISArXlnlK8rXAKIVftDI6kAc-sWa2-RuVv5aUTYH5YnBtZK-IOk_v6chL8rM09SsP7P0Ayn7A7s3zZVeLO3di5NUnZ1yqrrR3gm-QFDj6ubGwSGpK0mpYws7uJ-T1LGtkAX_6aiGloELikLsCur4-GcJiN6-fzUudWOQPCJ4WnnNDpm7tzDLSDnmhhmuwlep7LkKA-jSgMikw1CiLgy1hIqKyRpMDerOLPAewDHlOOQ2t68EyU76wB6stIyGSl_C5r7aEbmiuazhJBhgEGVfMwxvrht4yflPaF714e_s4DQhUzk1OXG9PKkk4tbKvhTdLoQJM8p9SFTcEdCJOEUv9wh01VzYSg6ztsaeZQBSnLhlGHy83o3EtWg3pUxLCN-gWATRRWbhTTABIudyUB9dWDlTJx0vMF9Y9X7qbgj6RC_oaZnowBdW-eUMTmShuRzwAVUGf1Jn7DLaz825MxGAGfIwmSZS-DVhXMqV6l9tTT0_I_kTqrYgHsoOLgAHKkjt1zMhmobPXAkerKtzhZsjXkD2UmyIvKpVaJDDa9J_DVOaKMQWLYuYNYPD_dIrAPOWlq4ayfnmvNHGkgwIDngbbZR_dR66wWOfyb_7WGlnrRjDSx7rl6Htz_F_hwxy7ltyLGawMcGcMN5FhIp4CE8sflYHrsnHcEqu78hJ0gSZ3fuCE63nXTZbkyOjf6yUcxWnwdrQP8E-I49YjnGtoFuzl728gIt8gScd0BQprLwV4pHHjMJ0XCzvY2Wu22PQXpxfmThq1JFAsRO0Zvvmqe_hzP99WRKK-OgKyKVi90u67ahg9dmAP-3u3DCR0aYJacneB6mutpF1JvKdOc6IKfe8N-HYXtOjdHtfINZsuqUrCrxDFwAQbvcpX_nMxiguhpIIfKAcpCFp70_s5eLYgZi1JjZ1hNzHOSHvdKc0jIthWD4cm-XB6Mhc0hE67d4tlxqVN8Lvow5Rw8vd5VIaZa5F0r7qA4wfn3X3Yr9INGLVPMt-LmH_E90Xevwvonky7XdfSRTb7qIuljU=\"}"
+ },
+ {
+ "type": "text",
+ "text": "I’ll locate the bottles and bin, then grasp and transfer the bottles one at a time, checking each pickup and release.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_03880fcdb65294d8016ae26dfdfa788192924af801f222ea09\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/lib/joints.py",
+ "offset": 1,
+ "limit": 300
+ },
+ "call_id": "call_c9ef1243fa444c9f85a5355698087337|fc_03880fcdb65294d8016ae26dff555081929e10d71a55311cab"
+ }
+ ]
+ },
+ {
+ "id": "506bca54",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:49:51.673Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Joint devices: URDF command vector, limit policy and link kinematics in the device base.\"\"\"\n\nimport math\nfrom pathlib import Path\n\nfrom kinex.lib import urdf\nfrom kinex.lib.geometry import flat, pose, vector\nfrom kinex.lib.kinematics import DEFAULTS, Chain\nfrom kinex.lib.urdf import joint_target\n\nHOME_RECOVERY_TOLERANCE = math.radians(1)\n\n\nclass JointModel:\n \"\"\"A joint device's commanded joints, in URDF document order, and its link FK/IK.\n\n Poses are [x, y, z, qx, qy, qz, qw] of a URDF link in /base; link\n defaults to the model's tip_link.\n \"\"\"\n\n def __init__(self, profile, directory=None):\n if profile.get(\"type\") != \"joint\":\n raise ValueError(\"expected a joint device profile\")\n model, self.tree = profile[\"model\"], profile.get(\"resolved_model\")\n if self.tree is None:\n if directory is None or not isinstance(model, dict) or \"???\" in model.values():\n raise ValueError(f\"{profile.get('name', 'joint device')} has no resolved URDF model\")\n self.tree = urdf.read_tree(Path(directory) / model[\"path\"], model[\"base_link\"])\n self.joints = urdf.commanded(self.tree)\n self.names = [joint[\"name\"] for joint in self.joints]\n self.tip = model[\"tip_link\"]\n\n def chain(self, link):\n link = link or self.tip\n if not link:\n raise ValueError(\"name a link; the model declares no tip_link\")\n return Chain(self.tree, link)\n\n def fk(self, positions, link=None):\n \"\"\"Link pose at commanded joint positions; mimic joints follow their sources.\"\"\"\n q = joint_target(positions, self.joints, check_limits=False)\n return flat(self.chain(link).forward(urdf.positions(self.tree, dict(zip(self.names, q))))[0])\n\n def ik(self, target, seed, link=None, **options):\n \"\"\"Commanded positions placing link at target, nearest the seed projected into limits.\n\n Joints off the link's path keep their seed values. options override the\n solver tolerances, damping, max_iterations and search budget.\n \"\"\"\n unknown = options.keys() - {*DEFAULTS, \"budget\"}\n if unknown:\n raise ValueError(f\"unknown IK options: {', '.join(sorted(unknown))}\")\n values = dict(zip(self.names, project_seed(seed, self.joints)))\n values.update(self.chain(link).ik(pose(target), values, {**DEFAULTS, **options}))\n return [values[name] for name in self.names]\n\n\ndef home_start_tolerance(profile, joints, target):\n \"\"\"Strict devices may recover toward declared home within an angular margin.\"\"\"\n home = profile.get(\"home\")\n if not isinstance(home, dict) or any(j[\"name\"] not in home or abs(q - home[j[\"name\"]]) > 1e-9 for j, q in zip(joints, target)):\n return 0.0\n return HOME_RECOVERY_TOLERANCE\n\n\ndef recovery_targets(actions, joints, tolerance):\n \"\"\"Allow a bounded, inward-only prefix; the final target remains in limits.\"\"\"\n joint_target(actions[-1], joints)\n previous = None\n for target in actions:\n joint_target(target, joints, check_limits=False)\n for i, (q, joint) in enumerate(zip(target, joints)):\n limits = joint[\"limits\"]\n if limits is None:\n continue\n margin = tolerance if joint[\"type\"] == \"revolute\" else 0\n low, high = limits[\"min\"], limits[\"max\"]\n if not low - margin <= q <= high + margin:\n raise ValueError(\"target outside joint limits recovery tolerance\")\n if previous is not None and ((q < low and not previous[i] <= q) or (q > high and not previous[i] >= q)):\n raise ValueError(\"joint limits recovery must move inward\")\n previous = target\n\n\ndef command(profile, actions, joints):\n \"\"\"Validate a sequence of joint targets; strict limits reject targets outside the URDF limits.\"\"\"\n if not isinstance(actions, list) or not actions:\n raise ValueError(\"actions must be a nonempty sequence\")\n for target in actions:\n joint_target(target, joints, check_limits=False)\n if profile[\"limits\"] == \"strict\":\n recovery_targets(actions, joints, home_start_tolerance(profile, joints, actions[-1]))\n return actions\n\n\ndef project_seed(value, joints):\n \"\"\"Bound a solver seed without changing the measured configuration used for FK.\"\"\"\n values = vector(value, len(joints), \"IK seed\")\n return [max(j[\"limits\"][\"min\"], min(j[\"limits\"][\"max\"], v)) if j[\"limits\"] else v\n for j, v in zip(joints, values)]\n\n\ndef measured_positions(message, joints):\n \"\"\"Order a JointState without clamping or silently accepting duplicate names.\"\"\"\n if len(message.name) != len(message.position) or len(set(message.name)) != len(message.name):\n raise ValueError(\"joint state requires unique names and matching positions\")\n positions = dict(zip(message.name, message.position))\n names = [joint[\"name\"] for joint in joints]\n if any(name not in positions for name in names):\n raise ValueError(\"joint state is missing modeled joints\")\n return joint_target([positions[name] for name in names], joints, check_limits=False)\n"
+ }
+ ]
+ },
+ {
+ "id": "a487405a",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:50:14.970Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Writing action runner**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e0308c48192b6ea33c2ff852295\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Writing action runner**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m4GQDiBx5wuaBBn50w11s2WGkljmmJldS4sRYRotgOjiORqR8wkGlqRspjrqGGK-_9kGrs0X1h8E16Wc1RjLWnwzKcypDYwLefjbca0pO5jmqc28DJRPkmmZZhQD2FEDfX_KjGZN8jlOrTFJUnMhVFDdGsCt74r2VZi7zteXp3OzkiI0KEv_yEtGu032dbUoXZdnDQq5R3jCH0yFDQgwKReNcSMcOTXErzM08l9RdsQnQbMUXkI3BQ5eIXKM_H9ulge39BdiKPrLsF33Q3I8pXku9jWwbnZzFI50sGtuSVLC_qHGXF_Jpq6JDI8Vh77p05kJi39vcOBz2B2R7YMFaCAMCgyJK76V6y5fl1M1FoCMZly0socU1h4YcLaPmmWhGfLzEJQQ7NP6Uhqtg-zxM5Q8jHQlh_2oRRYciTxHBDg0QSbozKAPm1BfHUuRLOKsfZCp4WcwljE9Q4eZy_IvUv41pg4V_O-wxw5eeWelbkPUJBlSryPGgUfR__D9xRxhigNfHYEV6Vg3BXiikpf5sPZW66hHfBwq8HWatq-bM2wQPjpfGdLR4DBBXKtr7VHhtLhi8DSthsVQeZPdmf6TvTyWKwCyoXAB1k3b9QTQQXNaUgVJcj3tGhfyoojigA2KUE_9sSkicpmyuMzp_6rOwFpa_y_onn2ZF3GHTa3-JSUOk73rTWfr_nQdPNxKSIVNla4QWcHMK1BzBq4osrSO2WsiUHZ8eYPBjRh09x3b5XCAMlBlWaZEJmly8840PlSMdxlIJhwOa3_VW4qsLIValoSqe_JHMLkDvqUW2c5p4PNsK_gWUSKonCPHgjBdjeyZY5amup-8KlKV_WM6p_xUxAw4DZj8FKf0Aq5--PpxYa45SFtzOO4sfdkqwVX5hDnYaTgWSNasy_YQ_BG3N_D66BdcAB_Q2w7jqIqtT4UTWHb7UiRVSyTTrnsOMBsfiy49PNcARlRrSjlGKdyBq-yFMeROB8rkHzPE1GQFDrLXw1jK8ItPoHwP2aN0ndv7-U_R5O3v0CbJihvrMcF1_s1OKcUgpzEfnlD5XaxI4hUoQAVFw0JiwIyy26j_KlIoZKtLoBOdBA8nKoANVNA88gs_j8ccs7qEoUVwiyVr_lBi3BlaOEKrZ2-hd4AL1Phr6xyWYboXvfL_xXQG05yx_BHSR4dt8AiVxs99jyQM1_exmMdizcA9RvtTu6S0Diniq97RlehszTWw960nwJOXGi1wHslyo8lxrhtY6794B4dxfL4YqKEfdrNnO33hjEjf5jRA95Jbwvtmx_7lj8Ov4Z9WSbJKDLadq_pmdUijbQ5wVw3S8JWrqNa6FGhSF-6Db-dTiprymwMx-ZM8vAuynvxS78BGXwnWiZ1jQg7sdN0aBvQrsbXgN4jurHAwENWuTI_AU5GCakn_ag5ejfBGodgDInqZvwj5Ylzfn39z_ZBPOWZn1XmAiBDoDR8pD4EJRJwFO9tJTcOOMKvhZmQSaGnOy36u7lmj-mjC1-k-fjKxnzAhw_jBpzbqYhWwZ_H2lHZw2oPI58vmqCPqu515hJx5hnT0kFkOQx5lIqBVAsj-13v-oQ0tRQfbZVrBS5W0fwgGDqtLigvMXH5jc-mNX9gVEA11OOwUxpJ3Ct5XjTdMow3_Flj2dy79aQk1ZxFsDefUA-9VzPgJyFRPO0JzBdkNJ0DeUM-KI_lGr0_lDuhC1roj8rKXAonOLPL12XLhQJ8q5dvbPy8nw4jyCElJHGkV4CoGEanDEfNmGOKGHKqjozg0gitkHtVRTdlD6QgwNl0haU14qtuJWAVy4M3QG1zfuRo4HT2roqNgUJJMHS6m_d3ngJhtxLftLZQ3wRluNQnB_UM416bRZ50nBYORIFLTV3GtTwNVne0zmHgCArsBlrAsqzSIaK3JAnS9nX-RPljTuWKFqeBA2vE41bCrwTZ-WXbA7-viPtiWYAyM1tqNqNldl3GFyU-HPpDUrqC8Epxrj0VN61D8xh1c73pds0q1-oqCgsmbqiaWOgkEPKDZYp91_UTw5hD97ZHMkJHRbsx6m66qBhM2ZkmXfdK8vgnntARKIouMTKBfAObEEufnXwmOSDRR_roG0oLWA-lcqi1E9ebmvj3VsxhmnWYhMReR78cwkWgJun9qTGtj7enLXrLkvHL7deLC_Sl8OmQHySuqauIRDoOWcfASFHW-rPCXMSRLMqR_gPoUVxGdqnb9nyZaA-aOc7D8kk-OEsFyfX5Vq5_RuTbjrXl1kOCRtoS1woS4Q==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/manipulate.py",
+ "content": "\"\"\"Measured, stepped Cartesian moves for RoboTwin ARX5. Invoked with Kinex exec args.\nWaypoints are world TCP xyz and optional quaternion xyzw; duration per waypoint.\nNo motion inferred from publication. Uses declared FK/IK, camera and wait interfaces.\n\"\"\"\nimport asyncio\nimport numpy as np\nfrom scipy.spatial.transform import Rotation, Slerp\nfrom kinex import communication, helpers, args, finish\n\nasync def state(io, name):\n async with io.subscribe(name+'.joint_state') as s:\n return await s.next(timeout_s=10)\n\nasync def main():\n a=args(); side=a.get('side','left'); arm=side+'_arm'; grip=side+'_gripper'\n async with communication() as io:\n model=helpers.joint_model(arm)\n m=await state(io,arm); q=list(m.position)\n if 'grip' in a:\n await io.publish(grip+'.target',{'data':float(a['grip'])})\n points=[]; elapsed=0.; targets=[]\n # Default vertical approach, fingers close along world X.\n default=(Rotation.from_euler('z',np.pi/2)*Rotation.from_euler('y',np.pi/2)).as_quat()\n for wp in a.get('waypoints',[]):\n xyz=np.array(wp['xyz']); quat=np.array(wp.get('quat',default)); duration=wp.get('duration',2.)\n if wp.get('linear',False):\n current=await helpers.transform_pose(io,model.fk(q),arm+':base','world:base')\n cr=Rotation.from_quat(current[3:]); start=np.array(current[:3])+cr.apply([.12,0,0])\n rot=Slerp([0,1],Rotation.from_quat([current[3:],quat]))\n fractions=np.linspace(0,1,max(2,int(duration/.12))+1)[1:]\n else: fractions=[1.]\n start_t=elapsed\n for f in fractions:\n p=start+(xyz-start)*f if wp.get('linear',False) else xyz\n r=rot(f) if wp.get('linear',False) else Rotation.from_quat(quat)\n flange=np.r_[p-r.apply([.12,0,0]),r.as_quat()].tolist()\n local=await helpers.transform_pose(io,flange,'world:base',arm+':base')\n newq=model.ik(local,q)\n # choose equivalent nearby revolute solution\n newq=[v+2*np.pi*round((old-v)/(2*np.pi)) for v,old in zip(newq,q)]\n if max(abs(np.array(newq)-q))>3.2: raise ValueError('discontinuous IK')\n q=newq; t=start_t+duration*f\n sec=int(t); ns=round((t-sec)*1e9)\n points.append({'positions':q,'time_from_start':{'sec':sec,'nanosec':ns}})\n elapsed+=duration; targets.append(xyz.tolist())\n if points:\n await io.publish(arm+'.joint_target',{'joint_names':model.names,'points':points})\n wait=elapsed+a.get('settle',.4)\n if wait>0: result=await io.request('world.wait',duration_s=wait)\n m=await state(io,arm); g=await state(io,grip)\n flange=await helpers.transform_pose(io,model.fk(list(m.position)),arm+':base','world:base')\n tcp=np.array(flange[:3])+Rotation.from_quat(flange[3:]).apply([.12,0,0])\n files=[]\n for cam in a.get('cameras',['head_camera']):\n im,depth=await helpers.camera_frame(io,cam)\n files.append(helpers.save_image(im))\n if a.get('save_depth'): np.save('/tmp/'+cam+'_depth.npy',helpers.image_array(depth))\n finish({'tcp':tcp.tolist(),'quat':flange[3:],'q':list(m.position),'grip':list(g.position),'target_error':float(np.linalg.norm(tcp-targets[-1])) if targets else None,'time':result if wait>0 else None},file=files)\n\nasyncio.run(main())\n"
+ },
+ "call_id": "call_0dab35d986494f688df08ec008796574|fc_03880fcdb65294d8016ae26e06f8f481929dff7a1ab8dbc133"
+ }
+ ]
+ },
+ {
+ "id": "4df9f281",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:50:14.974Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/manipulate.py"
+ }
+ ]
+ },
+ {
+ "id": "7210e35c",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:50:20.195Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/manipulate.py",
+ "description": "approach clear bottle",
+ "args": {
+ "grip": 1,
+ "waypoints": [
+ {
+ "xyz": [
+ -0.198,
+ 0.04,
+ 1.11
+ ],
+ "duration": 2.5
+ }
+ ],
+ "cameras": [
+ "head_camera",
+ "left_camera"
+ ]
+ }
+ },
+ "call_id": "call_45ca89cab14d441c80d9b258f0df7f6a|fc_03880fcdb65294d8016ae26e1adbd48192aa2a6f636e4f6741"
+ }
+ ]
+ },
+ {
+ "id": "df02d221",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:50:22.923Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224222.313883542] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"Traceback (most recent call last):\\n File \\\"\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 40, in script\\n runpy.run_path(file, run_name=\\\"__main__\\\")\\n File \\\"\\\", line 287, in run_path\\n File \\\"\\\", line 98, in _run_module_code\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/workspace/.kinex/tools/manipulate.py\\\", line 60, in \\n asyncio.run(main())\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/tools/manipulate.py\\\", line 38, in main\\n newq=model.ik(local,q)\\n ^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/joints.py\\\", line 54, in ik\\n values.update(self.chain(link).ik(pose(target), values, {**DEFAULTS, **options}))\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/kinematics.py\\\", line 231, in ik\\n solved = search(self.joints, options, [target], [seed[joint[\\\"name\\\"]] for joint in self.joints],\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/kinematics.py\\\", line 156, in search\\n raise ValueError(\\nValueError: IK search exhausted (time budget); seeds_attempted=5, iterations=406, elapsed_ms=100.044, position_error_m=0.10653722123952583, rotation_error_rad=0.10622118351177572\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "8ad02130",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:50:30.833Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Testing top flange feasibility**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e21592c8192bd3909fa7c03be48\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Testing top flange feasibility**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m4lFi-BEzfKtWtRy0Wv395Sdz33QMjU--o_4cTk1SoKiQhIJbRFBl9_ssbwa6mEGx7JWS0RHl5u8hLtzPs6fFKqeH8iluBb0TFHF1S9nKeRbMcENPEcwIZ7A22G1oy9p5n0e9PaH60vCpedWILbiDH7nXKrre9-fBaTTa9-m3T-885hqW5Yu-emP34IX3oWBKujrgW8664RVj9JjXNObL9E0zI9V3n8l1j0gUBMdC-NFrgfl5bVqNFYh0Ti3ceCFXNZoCbnPXDE2vfTvkKPN1rzFfgi_Qmtmig3qiK1gF1uIRGPK1EC6w_ajWC1pcb3CCQsjosLmwtEuZoW3WTQAFg3gxCgkVHY3rSKeVDBsUQDulDbAjX8URW0EPk33F_vpywjqM0EPR7ygAmmonF_YQWO-k1-cslnXSvcNVSveQIy1NI8DtFaAlLxsCXZFRnAFkZ3FKm9GVeBKyqtllw6jL-ykYmU0ycvxuwpQWc8gZx4acxAEz7G-BOTBmLBZvpNeXhM4sHrB1OqadkBM8VHrJH7ZaUvbue8xDOImh_1G-pceiP6qTc99nzGDG6k3OhAlWxHfueWrbk5qq1D6_JOUPe8uY3_DAVo1TgIkqdoguOCb1W5R-tIO2PXnceBedl6uo6_ODDAsUrcDTaeZKviqyeUUw25nOeKkhGIjy0QeLAkthpy-qQXKfihU2xgkF72Cnux01hPe110nskgGomkoOSGQUSsEBSOulEVOdu0xGdfTSlm5Dz1HBKtXra0SzOSSV26e46ek5QzsfPHE2uqrqDEDH6Y_QK4u4hGYbHqZkK37CZCuMh3Skk29BXGExxZlU22OsOgzQlA0luUguvd5WLyJciAdmQEoZf2-uv8cpwqrm2UFn9zZ4m8dGD182CtP4AV-PMlL-roT9-xX3xpm_z7wn7cAO8ad10cnkF8a5wyEW2iSmmyvaGNcchnxpy2ZAvCp0xZLWZA76fQC4yNz9ifVBy1OSL3QJ_8-2nCXnrZKTVKDyiTg8FuOjteIHGy_AzIxeFCuKMTRG-P7W_FFPOU6ZP24L57vb7D5mY2UK3dHKHXFE62xUq7-4bVGbnWceXcsEWKDK1neBF_ZTOVynv3gkMwrFOYJQLQkea9ereVdxPJwxLvOs_ntpwjx2f24QqsbGbM0OkHMzVMZi9qqybB7L0cHslen9jidUQNClinXJsYiDyrQKGz6PQ58_C5KFKkKpf9myHBkfuwzC-0Qe3_8IMP8Bn-JsGWI4rYDs55w_PBZepjWvHPIZnJM7o_HYLFcRt4U0TZX1sz9vpHxn-8JZDZDhVutHXzpvUK8IlZv9oD4Bq9U4iRyM-_mgbs8MGUZxET1kW5x-zsyWMrc21iGNX2AepFmNJAk0DGsegowmOWIRxcYGze6kLRhVibHW4N4vZGCPgHjscxfTPiTI61zCkuD8Flv_Q0uQjGz7zwiEOm6R1_ifrYcF3wj9DPjMWrxppWi2PPLCGwwtNt2CDHrVfGQLTtSxxb_GTgjRFFlACPt2SsB9o_qpFS7crk5wUVks1cBucHopvsWo6GZaMuyHaaXKqOErFitqtRiQR0t7pjgX55af7lywKfsub40GrG3r5Z_XBbVXV4mItHYm6mEA0tpig6ygTtJmWLVTtyZTuAhXvztb4cpgXGBzYYffQkcVXTFBl4vCXA4oYMWqn-DV-abUAABH8Vgs8-j8hNzu6WQKIqmFb1QXn2bWfkS16ittt_BNjPXqRNc3jhJqgktLWg-OpOg63TW_KfG4UFQ0rfkdc4soq3cxnhptkS8HjafNIFy2CXJ_q2c00rFA1C9Hm6OXxp20bxyFwNCma752tUTLCGC8AD9cX4NGNPsWTZFHw-7itK_Hc8qAcrvoQPvFCDNGZXf1IUBB-3-q8Bo10dnF7wqt1-DCX0K4YsoikJWetsh9wdd7xVd_tyxUu0XA==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "check reachable grasp poses",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n out=[]; model=helpers.joint_model('left_arm')\n async with communication() as io:\n for z in [1.04,1.,.95,.91]:\n r=R.from_euler('z',np.pi/2)*R.from_euler('y',np.pi/2)\n p=np.r_[np.array([-.198,.04,z])-r.apply([.12,0,0]),r.as_quat()]\n p=await helpers.transform_pose(io,p.tolist(),'world:base','left_arm:base')\n try:q=model.ik(p,[0,-1,1,.5,0,0],budget=2);out.append([z,q])\n except ValueError as e:out.append([z,str(e)])\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_d766eb69ac6d4ec79410f9f2129fe45c|fc_03880fcdb65294d8016ae26e231ffc8192873929d00d4373ca"
+ }
+ ]
+ },
+ {
+ "id": "054b78b0",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:50:33.588Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224232.937157450] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n [1.04,\"IK budget requires max_attempts, attempt_time_s and max_time_s options only\"],\n [1,\"IK budget requires max_attempts, attempt_time_s and max_time_s options only\"],\n [0.95,\"IK budget requires max_attempts, attempt_time_s and max_time_s options only\"],\n [0.91,\"IK budget requires max_attempts, attempt_time_s and max_time_s options only\"]\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "23c00f42",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:50:39.106Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "check reachable grasp poses",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n out=[]; model=helpers.joint_model('left_arm')\n async with communication() as io:\n for z in [1.04,1.,.95,.91]:\n r=R.from_euler('z',np.pi/2)*R.from_euler('y',np.pi/2)\n p=np.r_[np.array([-.198,.04,z])-r.apply([.12,0,0]),r.as_quat()]\n p=await helpers.transform_pose(io,p.tolist(),'world:base','left_arm:base')\n try:q=model.ik(p,[0,-1,1,.5,0,0],budget={'max_attempts':40,'attempt_time_s':.1,'max_time_s':2});out.append([z,q])\n except ValueError as e:out.append([z,str(e)])\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_45460ad2e45c4f75af849f7a18986ecd|fc_03880fcdb65294d8016ae26e2bc4cc8192a79f14f7a6b63d6c"
+ }
+ ]
+ },
+ {
+ "id": "efe179cf",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:50:45.291Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224241.131440963] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n [1.04,[-0.2496410241379745,-3.8412895605530037,2.487698982425237,1.5250552017336654,-3.1154129244818,2.924150273604751]],\n [1,\"IK search exhausted (attempt budget); seeds_attempted=40, iterations=8000, elapsed_ms=1170.321, position_error_m=0.017156539321827088, rotation_error_rad=0.0005849824564675265\"],\n [0.95,\"IK search exhausted (attempt budget); seeds_attempted=40, iterations=8000, elapsed_ms=1184.417, position_error_m=0.0004092112180844326, rotation_error_rad=1.4402656672529403e-05\"],\n [0.91,[-0.24688493993230948,-3.825269561715616,2.5398416965020116,-1.6526536288735123,0.005872565741773644,-0.2145231983847298]]\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "96d5863b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:51:01.624Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking IK seed candidates**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e39c7ac8192a2c6d356e51a4fa8\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking IK seed candidates**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m5BuaC-Kno9AR3hmRIUBx2iU4SBsGwUqfHA5tfJvOW7KIH3P6jeICJ-Y8TyvPXZx0uWQZyQYbyCf5acFGIx1msHGcV81nf3gsqCMyTNfxrSUarJo7Z1knC2ej2o42maMxOXtht7kqdbFe5NaHRNehV5SXAsm_VRQ8mfy1dhFWYQ8a1HJETZbpLZjmMaf2HB4HuJ8AZeLD0eVvFaxRNBaUvg04OC9QAwIVy5vSNkQPc3nVBM7GtRan9LRswVRMYd4Msms7lUmMwBNBrYstrRLBN5r826C4j6Ohgv453JjQ8LHa79rYi5Z4Xsecrc-qtQX65_JDmTwAykE6y9Gxyw2S0k2E2rqT6Rcvz48bp0Sfp9UD6FFpYmMgtf4sy_zNYobkoV7Xq2HM2dyIHxdd6PmBNDEn6C05XWu4AjvS0l_tDhpFYW00fWUPBSljE0KpEEtFxrmihtdX0Cn-BcWzQ3Empec6t3EAOltyiqBF8J9llNItcsbrpLibIQaPtbKkexQ4w76C8leyHkjPFYKrO_VOSEKL1j2Iw3id-DVb0sHvwiRrIpxCvA47eOmP5lUkBiqvSODF4tgWRAeoOTOm8RIWlZOmE9y-nzEk_2eqUjC6VpL4Bz9WWE8DIcavhEpwXBVoMDJeAiQpzVy8FcIen37Hp7bCwJkDwLyJsO96jKyL0ZW_PNw_4xGgoCIiQDpQJnPTWCl-qN3dmLnV0410vOQWsZ98rx-MHjEF9wFdaoYfICB3GJ1H7Mb47-Ew4FnMtNqzAaKixEy2HQVggRPhA-tIMuV8HAZsSK-1TJtY1oM09f5NZ9lBrbLCXHHhTdH9GHuS63OC4mXWSOradHvcOkKioS-G7uZvKFeujM1zIw_R4JvPjZT4LU72S8WYZeMhDY5pUEWbzdvyGm5hugxA3nvI7Bu15L3J7UcK0uKMj2M0ECq08F35Z0kHw84PVBtX0PTQ-uFMxa5uO1zvNdwqpNfrzgmfqA1YYa9X_BNGv_tOFAwlLoqa1XojjY2NUZpjLpWYaSZsr086aUlvGgutCKX_a_wlbV0GmMlg-wVIwt-yNRI3xvNhXNia6jJh66CoyMFKArubvu8rhiooyP7zTzGMFHLf50S4l65a-OHDEiYY071DDLGtPXS3r2DbvM-tc-tyUWIo8x7WNhML1sfL1e9K82dLrRjFHE7U3hGfXEZjiQ62xIt6krmN44AOHxItfKllFNFOUusSjOUO3yaYP0wQ_eMTRwSACFYkK9Jh9NRI-7-5f8VOfmU_xUQPmgthARw4KP6-NGi7zWF2jhFeUPmJAQIIDPavZRhvEuSu_QzCdoFa1eU7EoG0QPIcX0mLFLdgmSIrt7PokUod0rXWRzuHeQD-NpZwyiv8O-BO8hCb178fNRD_WCKFXl6B5m9tL0jCCwKh0fs4XXiOoKxeJJyZBRWsN0sadWiqsgf1KIC10H1N6EQsLLLa8xhWJfa23dF2adcnOyFyM3YWe2aZ0vpxqzaWnSr-hJ6DdMRrtv2M0RKRrPlZNuOGTxErPVJ_ifrUKMb5c444rXik8aEDyiBBR8Cuy_SuEnHOf2klyTmhmUp9Zq62RGkZmESyGpE3qU8g_w92kSEBXah4ZROfNJ2zD-S3rzjc-sPNfimHZwMyLWjzjVRez66yC33oLXjeo6SXNYMDcK8HmWfm4T_oXus6ocWwNBy8F4Ai3DlYpZfEPdyvNeHxMEiykPCDLUsXOfhkUqxTdmhQExTVzXqhePtYtW2vYVrHn93f4Aqegsztz6-wWwACzDg5HcWO0pdI38JIrm2qgfTevoMA7b7u236OlytwkFKzEaXiEDkQaCEtim8BftMsWxl2o9gpfp7ffkG-rMPwB7i3t6T8VjkKlY0ymc06afYIcsp48ytnBtHx9dko2ILGs3ZrejGZwt5fl7ACBXXZLgYAko5josecrqu-afw6rsSDsP75TEfeoBcYuh0vv0O_lGPfehOYc_0py9xOfC66hKQOoHCMt7K5NYiv6m3dxtY2_oB1ZHRm7wTY_0pbcLDkkdGOUecqVieOuNg5J2UUeEvH0USxGA1CRlvG3n26MaXKQ3Ii1RBscfgOcIDuHq235uCCWDuMH9stMawk-gKkIP17XWAQMFp8pmJsRnvA4quYzk55a4m5kI4TdCT-sujcTiXafJu9MqSAZpX6pXOGqjPzdRD9aiSDD-1s4RQWbSAJmU4a0rjevUvFFQx1X632i4Nmd4MnT3bwggZiCQulcclEb8dXsx19ncfDyG-2J8YCxxf_fmpEqtz7jpOHEI0XyQLR6j1m37W0QUDk9N8de3sGvy6RNQBtxAs8Ytl_33yvknLMGqNW6BIi_ZD1t_y7nPhzq1R1r1xADIwW5xr_3UGNXRrMcPR3iPsjAwOmaowtA8XGnevDo9yAE1GIW_4No05GRgpCYd7UG661rc3Z7XWbWwhf1bVSvs1FmekCkf09AATBqAiMtks0OOB6hVsQNvNwNUKCYiNuEZshc-64mQU2arwv0Gvu6TW1tHoBYWSxi32FOS-UHVNtFn3-p-j9P7AeeMs9u5BunNA5DN_Ypmll_B63VQfkccTp8FXx0jYbaqTWgigdW6jmeELovwlPBsVmWxD2Q_dUJJ11PVvEhuMLYk2HQLTxLjDw4hj9CaYhPFwruw9oUBJ4ir3_Z4rp_7ylF5RmOxVwG9i_6isA38ksRgFrhrDN7w42VT6XY6seBB1MmHEu_5xAuXj6KIN0G-Tx9iF3D6I4p_xI8olkCmm1n71mN9YE-3pJN5XBQ9u_AUItk6YbpM5tAGA8ERFTkBDc15oVMD5xEfbVpgSpouZHdfIkzmRvINp44YNQ==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "solve approach configuration",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n out=[]; model=helpers.joint_model('left_arm')\n async with communication() as io:\n r=R.from_euler('z',np.pi/2)*R.from_euler('y',np.pi/2)\n p=np.r_[np.array([-.198,.04,1.04])-r.apply([.12,0,0]),r.as_quat()]\n p=await helpers.transform_pose(io,p.tolist(),'world:base','left_arm:base')\n for seed in [[0,1,1,0,0,0],[0,2,1,-1,0,0],[0,1,-1,0,0,0],[0,2,2,1,0,0]]:\n try:q=model.ik(p,seed,budget={'max_attempts':20,'attempt_time_s':.1,'max_time_s':1});out.append(q)\n except ValueError as e:out.append(str(e))\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_e80a33c48f3e491cba937585b6e9c711|fc_03880fcdb65294d8016ae26e3fa1288192b59901d15046922f"
+ }
+ ]
+ },
+ {
+ "id": "8b058fff",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:51:06.403Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224263.608290980] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n \"IK search exhausted (attempt budget); seeds_attempted=20, iterations=4000, elapsed_ms=594.872, position_error_m=0.06611405415402853, rotation_error_rad=0.0019896488433462475\",\n \"IK search exhausted (attempt budget); seeds_attempted=20, iterations=4000, elapsed_ms=590.202, position_error_m=0.06586970481906577, rotation_error_rad=0.001980616266574562\",\n \"IK search exhausted (attempt budget); seeds_attempted=20, iterations=4000, elapsed_ms=582.975, position_error_m=0.06614644516120394, rotation_error_rad=0.002008056238735402\",\n \"IK search exhausted (attempt budget); seeds_attempted=20, iterations=4000, elapsed_ms=579.950, position_error_m=0.05696908984691351, rotation_error_rad=0.1997905349017585\"\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "f0a68f76",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:51:14.411Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Positioning bottle for grasp**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e4d5eb08192959c6f3dc7816fb8\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Positioning bottle for grasp**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m5S7P9hp49CgIfquWEnPD-q-jHSv5ilgsseqWPcUWc5MCfkfRUO_qILsLJrQa9sBcg0btw7o4vTiG7AWhwBuO1hB5NUgzYcmgZOTnoUFWld6r3dQpHnCPPluwys-2LSUqmjcVrxEsxZJjduyhOfqIrw7M4AVghy6MdJBLRtyByvEJCdNSrf4Z09vHtv8as8KsnA7-FPdYsy_BD9BE0JKq2dpQphLa3bnCCW0jwoxp4l3g2hfST1oDSo2QttWMNtjZfEu6KQoqhBWAMRdbY_fPbxx95BpN0GY2Z-0T6yR07DZ-44bK6KzdUh0npFAi1qmUsxHuecP70CsyrlRcQGtsV9PVqK9ASnnS0wg5v-eBj2LbJkjIxVs9-lIhsZLhBL5M6nQGWCI2VxLyIcCRK7krlm98z_lwKAIZBVaOiPFYoE8XkgyLQ9wfg_wF4NpqvSgF0hqozJynJvmFNo9z7NgOLHVybCzfWnEyB2A5ITL1fCEF4Un1AWACtM66EDfILEx742Jskx0zEYsguRCYl63x9GshgqrtgihnZZQ7Aw2bfYvf_NguBgmYp4-g6D_NduS7MJ7k13Ko_Db8W8y7Fyn6LOA7YJ8ALvM3OE8hwo6DXD97-Y8iQJ19wJ5L8-zKKeY66hyW-CLioY61G2p6t91nlquPfqYDHMT6zRpPFZv4ERpCw0PJ5BoulEQAty8L4Afg5OeHRfCQ8v5MePK06HPVgBV3b8LGhxdnU1TiVLVNYzXaobC7cd3eaTFf9tIbnYdUmIWkPhczIyzNF7_XgR-JCFzKA6sdV40N6N-FTC_ffrIrPdR2E5K8VgkUW37D3wLTzpW-VQ89RG-F0NVWERzVu_6zHfyuTPXkNo88mlDlwhuqQe0oUBI5yT0Y2R8WaYi-Uitpzxi9eDWjmwRQ8NnsEK0t_YLdA9NnL_0chH52qCA6s8Waxa79evfzKaz4rns0kiZDBZUSVt3oItYunAqTABHqwzwUkhOoHVvZPrQXljbu36kbKira7iMd6hYaEl_1FA8cMZj4W3sA53XqFxN8vpZXsvVsYd8VByMOTUs2P5F4HK9upK1aWGYxWeIvbgfydP-47xzvJuHivy7Z2Ibis4d8JVHqBzIIsi4YYCzY32SaUR0uxgOjBzM_0gb0VWgLWLi1UNDiC2PgqSJDwlDEFVvaj-i_SPuTteq4PuhijuWpAS7u7WtH5E_QYC1je3g3EURvncSTZiLQ8954M1uKE-zyFgGeJ57Uxdc4GcSfRcLczE7HRibff7p3CdxmF_ufTOt8XhwzgD3TWcfI_6x8YrzGeyay2QroZgeCtHOd0srY84PtuGHA5uexdJQhuMeaFsnWCmrnuBnAKliAjhB8CBBd57bmE3PFra3BYnqTUEaalMtXt4cE25U_QVOHkJZdJIaop-k6oeDpFETAmxvjV0FZ4-utX-tiN9sxpO4DxDKGn16GtcO_uUeyiSaWRLrKg3lIlS1mi11P1KyOtz4i8dw8ES5lthY3gryFb1QnRJZZCZRgY4G-lrQWBQaZhnIWkrI_r9yvqFXIpwV5RZOuYm9D0AqdTuH-B5Y7Nq1HdLPdjGzssiLSKNmWXAvbXLcAFj4KesdvmPo76eFTw7awWzA5NOSwBuxYPWdI3fV4XM8TtAQRODYeEXg6mA47FvKPFtsICsrUbTJKxlstA1cI50c4A-EKrpXSQkZjGpYI4CBRK2puy7tnISmx-7zPVX1EijNOt0bYkBuMn6ZKGzIvHn0T4l0mXtQotbaauyPbEvsNMRXwolQCl5oejP-wRJ6nbUYCf-GhqLXULeOZosTiiv8rcoILaNAFUhNy9Ulzn_ytr0VMV6hNx6PvNxDEX1CQ7pNGWiSX1KWq4UKIzXfaHNt_LCGAYfVIZsENUnQXzsjJJmq_QF5p2m7KvCHBXkRL1xpw2zwckWeh47xGbKq91YpoF4gMiTBYBXTYX78tFTGxqv1puEgHn4R_diFt1mlAaEwBd68YgNGAGno91-oznHQJ5600MCQLnRMgjFc8xaGvw3aqQDZCSuoMiQdraCPZd4oOCtfC9P8NnuTfNDyBn1g1nYc-1cGcCvaNYMM2XrRgjINHMAnM8UjlA1Ur2RjLMacagaxYznavT0AVV9Nzn2VUCxjYH9gVJ78lyjc8mhDpHyepfEoAWS-Dz-AnrgMWaxTVv8gAA96_YXFZ-HuAuEV1okFElk-iDgycoOjsqLbTBjW1MvK9jcU40TbieNiMD_b1xaz_jvoYgZvWVqMBfF4weP-aSLLS6jf8KQwUJG22sXc23X1S-WH4g4sLi3lkLF7ZyufKQQTSX7EDRgBPpMMSN82gTZU0VBJAiC-S9NF4u4rmCoMAZhTTkRFcIK0heE-0V3QaGWxtfF8YzVpyL2Jd0U3H5aEV-ZIhfedv7oxO7uK0sM8YxfmSp-sgJWJQe4OTty4x8qTvp7mF_KKh_QxH6BXO7N-L4Kd16q44fvE2gMG_16pg_KPddVpdPa9Pw03bH39w36YHpXGp3U74GftPv5g2LKFw7uPqQZQLB4SK4kBG-aVZ8_20VO9J-EEvDI\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/manipulate.py",
+ "description": "approach bottle from front",
+ "args": {
+ "grip": 1,
+ "waypoints": [
+ {
+ "xyz": [
+ -0.198,
+ -0.1,
+ 0.87
+ ],
+ "quat": [
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ],
+ "duration": 2.5
+ }
+ ],
+ "cameras": [
+ "head_camera",
+ "left_camera"
+ ]
+ }
+ },
+ "call_id": "call_a1252c09618b4174985aa43b46b91af8|fc_03880fcdb65294d8016ae26e5239188192b89199dd881dd9e3"
+ }
+ ]
+ },
+ {
+ "id": "eda38a00",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:51:34.228Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224276.413911057] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"tcp\": [-0.34149891422440415,-0.2565050430306144,0.8897903932734834],\n \"quat\": [-0.09308770694337504,0.19088826103653672,0.7954797807205011,0.5675458299374028],\n \"q\": [-0.20009401440620422,-0.2250864952802658,0.1718592345714569,-0.8337344527244568,-0.5068660974502563,-0.01791577972471714],\n \"grip\": [0.9960487864234231],\n \"target_error\": 0.2132543705144551,\n \"time\": {\"success\":true,\"message\":\"ok\",\"time_s\":2.92,\"waited_s\":2.92},\n \"file\": [\"/tmp/kinex-observation-_g33q8jf.png\",\"/tmp/kinex-observation-g6aa97sf.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/eda38a00-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/eda38a00-2.png"
+ }
+ ]
+ },
+ {
+ "id": "201e1934",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:51:38.540Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Stopping after motion error**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e689ea48192b6a45f7f44aad089\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Stopping after motion error**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m5qtb_bV8Jnc9j_qat8z-aUK1DPEqs8dNwp8Z_1vIgp-YyRngT9bgbMYRd0VgVna-WB2b0cfyNDHT5hmlC7LdH8MrSTa7JkDGowgVJjINGq-87G2gXJ_sgM4YP-t6Xivc7xTQGSKzkVSaziLN5ZTAJxFgL5g_EKMUqiGwjRX8BdDRGX9F_QX71_XfwiVsvIZxrO75O8g_5UsNUtLwduAt0H8r3TIGUGFKmu4pWgWW2yG-JLWGxKFXB9jKsl21c7DQ0pto9UpZkyYz-kUwBsY7qBhi6i2etMYLEztVeZ79Y_hVZvXaO85HJV1NvZ1FjDcxPcr-wFdpQzGhAwaALDIhYZ5N2fqzH7HocEjlWyPbPzgEaxmy7RDlKLapmug1K6YSrJ78k6BgQblvr15Y6KaVHspphYb4In7LW-t2HL7zY69xaEgEBMr2hmP12ewMbKpq7dkx9mJsMRVVCSFKuQGUdpOCkWjzDjRmnH6L_qrLkCGGTRVeVgihIJ--diVRjghEgOWhBKnpT1P2Xv6akezn1ayPV2za-u-4MZKPTJx3qt4AizeBtteDULbwdgABYTb5-IwBi8GkjRylaPMkwFa1BnGmTGc7ejOlfh2R8yDUFd_RA0DtQvgj2ow8vyJuV5MZj-Ht95pGssDtdszA7fXrCNRIuy-hy8u3a_d-4KHrryz6RvaoSGXJjES0HSabhoaciBCi84Fml_1wcRKn291u5s8uxlBK2RsVoncdXWsJcja8TR2stnFqigCd-LJkRHnYwX6Ywi0jYFdtFqb1sDqVZYSOPNU44Aqu-iMkIC24AfQFMvm5B2ZlZriDLxjSO6g6OlFyqmpv4_VyULAym_3WN-UGlyZ4443spdQ6DSuxy6ZkUvvAWDauZZR-NJ8vi4kOBINHaoHBZWt6yLoRbslf9GIuyAsJHyCZursx3Hsb93Paw_P7Q4k-_yC46UiuyjkiRLIrjG9TVL1MWFsgNHoUdlKmYFQnRdNzoHo4U949eRjG4YpwBYwCu1mMwUZuAhh8eQtWIlUnyP9qmpM18FcoYzI78SxkSQVYB4AAGPSp7gvdyjyGPsGRi41_u8IgOUJlK-6N-P1xjm_3ugvR5DOb9JL3cl82LZdcDi4-eIY_fhHhaYSncCm-6C22XJlTQ5HeF6yiQayaQqnpyu0SABGhyogrd3R_11Rf83wMZLxoswPQz4O-2qcZnK9hmuul7o6ksqWUblZh2BMrEFa4R1_jdFZ8hv0-42nvBj0qPkj5F3AKES1NJUMSqalgvW8UmLD-bHXpVzTuxluaMs1BdKU6BcJehChwBfqZHnl57eeWQsz4PGN9_ILb58WH9J3qTt2nnqh-nMKOulD-X09rP8mITtdeg6pGn-XUKLDNNf1CSCV5ePADxOax6IAZH3BMEc0lQy8wliC9pC26G9bfcfEDRSVNNmvJQAFl6Tbn-1tckkdtOgiHWrtIiK66EJzoU7lBBCVaxC4J7ZYSJYpwPsJ76zTDSSBXXvP8k1N9DvShw4uBp5FLVAUvELynSYcLDcekVXXlOXzMyp22JwzILs0pg9Ok5mM6zFAQdixOwjLuFoUR0l-BLiCgYvQLlGqlnMF5oGYI7Nc7oML7eh-9A7TMCxh2YqI3fk9v2bhPEa2VWv6uw=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "device_stop",
+ "input": {
+ "deviceID": "left_arm",
+ "reason": "Measured TCP differs from commanded pose; inspect joint mapping and tracking before continuing."
+ },
+ "call_id": "call_84fa2d515dd348759ebb78e7d4a8474b|fc_03880fcdb65294d8016ae26e6a665081928c3d06c44e287f05"
+ }
+ ]
+ },
+ {
+ "id": "bde0e469",
+ "role": "toolResult",
+ "tool": "device_stop",
+ "timestamp": "2026-10-28T21:51:38.631Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)"
+ }
+ ]
+ },
+ {
+ "id": "ee431b60",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:51:46.090Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Printing FK transforms**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e6d09188192adf0cad418956442\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Printing FK transforms**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m5xe6gje79me6oduAamugooli3s1QjIrOTBvCO4VPwyYqYu4WdApg7WH5Qi2gelXf3OfqdSaZKmf8X9di-OHYYoQPIGuu3XB3OgMwvvwr1_8YoMMaKEVRerrLpOGJqXoRg3EzzmApwxXeN9myjP16OwjWGJ-Z1a5apA48L_SqE8gE6bXYU4ima0jEngacCtA0367ntdeNBnJdDVddOQ8XuiYGguFEf4YFlm1GTGLcNp6RFml-aZZ45a4lXUh5uVyWq02zmv58RmosNqHWqcUKuyQ32nu6rntmdPE5_aNdY79-O6_gq6l8mxxRISwAAHl3C6nz-QIoJer_y1xvWISQNZiqTUlSvbydpPaIzdl_kQfJ62u0OCh7ojscW7aKrDYO_IzqIxrqRpMchFCPoFu8qDY4q-abNLupmfVoLxY8hWv-nseb_pUWARaO-zKoMHtxP00OIW89be-HUVQ-HhjzSIh9hXcnVyHKQGdtfiNAUovmZdiyN9UV3Oi9cKWq1jf3OevH92zG4sBZt9xAIlpRf5pem_3JOe0EsZyji5YWeuirppRqqtLaA3HkyTiX71mY8kDLVsI8KmhMQfRWi1F0kLYbWO8ZGxq4huecYxZUYY87Goj4Nd7bGg-IlFD-hCQMBl6EGFSUeG7xYSGp4966nMYpfEATerdsZ5WL1jnrdm5yYqz4Tyiq2As1DZvOEiuno0ju0AfGUhCU-8KvC3TKf7BFVIBeYPCH-EpRmmjOMoS1JHTQ6UzFour_ALFDH8SRhmYT7Kj4U2GrGcn30NUgd92NLOiFhkih5mr6QDkYg_mapafSDUjtFXNHwjFh0S6E02n80DJZTjkVDkt5YoRgdD3Bs44FT3h28bLNgv9SBMpQryAUddFLGa0XSApvYfSJJYPogzuhBePV4sYq_Lq8hG4NgBEJ93sPW-AjwAs1yqM8Y9UeCnrxNbQKZI1rqylfVII7DJXpch3sA4EbdpimwvJXsuHrplknZbXqABBwjmKMLXODzgai_7kNX2wxuaVFmh-0DBlGJ2csEOYCa75Z5q5ABIpjNEtSq9McW20Hp4WofKjrdzcxuDb_nZTihIce9KH1vic4so4Gdc7ESps3zvTYBR5gR4MJvc9bEkl49jB4Siey9pj6q88HdbzHq2w9ehWH8MyKX3I1bwZJAXYF_zAMCci0Ux-xYQ11Blx6iiZTJfFNg2UG1JSRAoyuLJDeEz7gQdbfsKmg-BL6EaLXed8s1T-h4bfyZ3I8fQAGG8aPDVQj5gS84L3ePFkqYhcCCuLNM2cD5jsocIEExUAiz6t2d3M52rna3m8R9Ssd6X-xq3OFhPDXzhm_YHekQQAJWkf7aILiuZV2a4_lwR9YnHv0ddWi-Kz76mM1p2h3XBEKKL2e29Q4i6Ts-uymL-uaARGxxeX9_l3NcT6zIPKWtgFck2MmkBEeopsWFuagUFNqEhs6g8k95GJVisGWJwN8BRLng0r2GOaAxj6dCMil-fzbNbNF-Uxv_wpixAQdInQzHFBldQ4aVqs5d0YWpn36RSjq6GyvEzJgzgT70xooPw0Xx__Y_a0n6UrxqQpmaub00BpaX-PGHaX9hkfZ2ycQrNXR2MVj4m9LVk2tFGIKBIt-3zBT86gAjjzNb60eTJ0rSwsJYrwBgFDYy439wRjVzBOAvZSGXwhsYkNZ1dPpMdRuFcIFlV2rvilFjWnRhyVDHuO0WTzPCw1oSzRerk-K1sTQskiprKdWgyHqvq6nrK7YsffRk4Q71fC7gk1QV3wQxIzkend31LPaMajmHBhPyAVYIWsyvIZE4hQitEe7pzZD7Hg01y9rw_Vla5A7XmX8cDdC8NgyIbxFiLtsbFQyG9JzzVk3o-_fy458zSjkvP7ouDluR8Kk2vnGU7Fg2BBUFvh2ZAUio9vknyWBxHkDRUjR7m2ggpjyCtv_TfTfS0P6-OSUSLLh_5YKnXoZcPpd-u7DM6k7TIjDPx0XoUTJCHvgxVGRLHGVdas7ezr8RviUDIcJubFlnKRi-uOhIRNztw3IBultLVwdbHQIiAlZbm5gQJH6TqkzO_QuqNSKl0saH1zBLyT_GaPqy-wRNt6F41B2a3RCYpR-pwbnJflaUK\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "diagnose measured arm tracking",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n model=helpers.joint_model('left_arm')\n async with io.subscribe('left_arm.joint_state') as s:m=await s.next(timeout_s=10)\n p=await helpers.transform_pose(io,[-.198,-.22,.87,0,0,.70710678,.70710678],'world:base','left_arm:base')\n q=model.ik(p,list(m.position))\n finish({'names':model.names,'measured_names':list(m.name),'target_local':p,'target_q':q,'fk_target':model.fk(q),'fk_measured':model.fk(list(m.position)),'tf':await helpers.transform_pose(io,[.12,0,0,0,0,0,1],'left_arm:flange','world:base')})\nasyncio.run(main())"
+ },
+ "call_id": "call_654cccc60e4f4bc1a854d57c04897250|fc_03880fcdb65294d8016ae26e6fe8c48192ba1d390ee0a59203"
+ }
+ ]
+ },
+ {
+ "id": "f361f966",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:51:48.098Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224307.591027112] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"names\": [\"fl_joint1\",\"fl_joint2\",\"fl_joint3\",\"fl_joint4\",\"fl_joint5\",\"fl_joint6\"],\n \"measured_names\": [\"fl_joint1\",\"fl_joint2\",\"fl_joint3\",\"fl_joint4\",\"fl_joint5\",\"fl_joint6\"],\n \"target_local\": [0.19748021568092256,-0.10296987920505801,0.08799976895842088,-2.1073194747276565e-8,-2.1073194744748758e-8,-0.010000025916871026,0.9999499984907548],\n \"target_q\": [-0.5538732839669482,1.995022269064291,0.16137099170018213,1.8421592169091363,-0.5113192953777548,0.016807289704789778],\n \"fk_target\": [0.1974588856049695,-0.10295700740880999,0.08803969389974405,5.656337319998357e-7,-0.00000421306646243146,-0.010000411984881847,0.9999499946207624],\n \"fk_measured\": [0.058972431162814636,0.00270585894917854,0.1515630860129737,0.07115997195073531,0.2000997192265956,0.15152750906073412,0.9653682068284917],\n \"tf\": [-0.34149891422440415,-0.2565050430306144,0.8897903932734834,-0.09308770694337509,0.19088826103653644,0.7954797807205009,0.5675458299374023]\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "d5761dfc",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:52:01.148Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Solving initial q0**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26e75fb6c8192bb4087a11f6da4fe\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Solving initial q0**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m5_74fuF27d3jGXNT6WvKuigsCve-sVROsJ9zt9PHD8PABLHzbUOK9THNyS1NU4_IVPXztmpYvGHv4llTLMuh5tqJXe-nKh5I3WXKfJ1VBv6aLYFaQNqpinPLho--WLpyLTkkUUiHJQUK0eklqekIoVsDf-uDro86BTFoM6cMhAo56OvYlmiagUETCgJlEFy7IjrQBekK7r3CyWwLwVd8TPOkm0QaAvAazN410Gujz_DBmiq43FG1BW9NTIWa-ZCFa49UM2yE4FZM2jgDAgAumTUD_BvRBxZ56JKRoaBRoy_YUul8l2k5EkHt_L544hRzr0CYFZ7XwV8I1y6wehyQVb5dHtTtZ3bInhWc8FNBsi9eLgZQNQQsCJsNqQFQAV1iE2z3PG4LuM9Orh3ofJoG-6ptyQQtjD46V_KRiZE-nV_2qQCVty2GKI9j600kKbwYj2-oLGiu13IUNBKR8hp9E4lpvmUse0lhV0OJQKBa9gb0Ghnr_z1nWjWqpWk4px94uafZAbS5Xa7BTut9y5jPBtNvV6rv_6TgHEbOILaIxUg2pfkAu-vxQ4xqxj9Wkc9air1IJLCPBkE8JuXHYgsgRAZuYFui34m22Z-5ixKgOZB1mG-yCME3f0VwQm6s0oXlfrT2p2mkp-vFQOBYtQIBM9-SoFCIZvR2dNY9EwAn25HA4W0p6SS7XchfzbzY2tdTc9dgSl5H_gLL01cE60FXm0HCqq2HGW5K0O013L4HF_nnIqEg6A93W1Y-v_rkoYLHtW-hgSr0vL_SLUNWsQtIlUc49yBQ6W5cVTfOrH11_cGB2hdfSx5U-Ry-QexRlwkZG4obxtBC9czM650vvkGOTeelXjsttpwVBEH-bis417P_Hgg1aWyj4w-p4ON_9eTTOVS_aiENEQShyyZRsIfqHolBmHK9sKESBUt93fmjdKyvdgW-6L1A71rwV_u2vqH6VIkGvXuPn1NQKyFGHWQbe-tLO5wHaCHuwLiSpBeH2rxH5e6TKETOvCh0rouvbcXi8MghnH189BfX71vx0OaOM_L4leu0SQwTjmwCzvnCBTVSS0L7oJOaN3u2sHCm8_X6J0U3q-ddC_h1bfLT0MII83TeYCFSvN4hgUNfIuI85DL6185sq5bYWsi5qggk49pL3FSPWieMeSogKh1ysK3F0lTjwld7tnPFLNHj3oPSGDkydbTMr7_9EWv1ZU39QitymsI4fkK79ee29kGgO9eSnh-VtHEGskfUZl1Qs_Jv0btwNYYkc06pVvpfqkODxYz-002o2OfXBz8VpTBUcL4oWQRTlUBXSVe6Qq9GTKkk0kdasE-omq4_2kEMPjLiRS9eQYioIcMaV1vj3fTi1UV7UAUGTSsZGxt4YtJ01I0OvZsxNj6FkcBuYYXNwNk7lXsa413Se13vjsK2NSEgGGn6IwkwsMG875zoL7HhM37LYUCNysw49cXMjRU58DM7cPLeZj5ZnzaDsKki8OI-MqKXy_c-R4Ixx0MY7s7CyzQVQVuj26ONZAYvWa_J3CPVwtvSm2kCEuE4C_YaIWMpu3953sjFFOhOhKusxiF5eq2xEy8SQ3Xox8UrDi2Y1_e85vtka6oC8v32eFWQ4DCoPOwwcq205OyAVHVJi0GeH1DSlsa04m0Qoyqc_hXy1KrXAvMvI1crpvyD0URbx-xkQwU__eo1ghtBcFpaPXOcRzzP48n56WERtVcIYe0eNPYwh0bKALzk0l6bJk5YYDDELtn6EHCxAXYsFXACjG75xB8wWyBDFe7BrJwWfx6yHjSatu7ogmO86ATJ5NjwGMvjd9CF4Lwrd-MXWxYm85z1qBddtAtIj6icNjnrUzymdYPUb5fByRoGBJtbG-NdB2GyJGt251klpBX69M8ZsNZEN2d8BwSn1B7wR19_mk9KjNKG0Tc3kbwza99a7Q5QqBZEWduGSAW24jb-fd1iY6z0ZP6vHMCPaup1zhh_NnGw2-uFF9jK4hg0ZGNoHqoJax1bmlRbGYQf7cPL1ZUnxrjKRggjYHpijBTytFtjTsRHTmS1X9ODEJraNg1KTbBMrx-hJMmIwneFboe2rtJszzMKzWYB8qtbf2TGVMzUNrayaDHAZGcM680RcckDTI1sC3CmFAfndIwN8cFZwtCMwoz9JmyP-EEj5YBct3NBgf-eATyuOw03czHzusE4V1I6khBwaRKfg4LaJS58FtK_FuKESujG1hQ8xa4oQ3-y5PGcPogqBR1NpF7hs119v460bQH4CN8OLkQ0_uMKgDmf0QnQdY2x5nEGh-slyb-Woe6zeVMRgtM01OuVFXnHxBCfu0d_Rd9nb1hv9nDzGVePMohZEu-XzCokVYcU9jLH_WzcyXdrp9SfH7JSABD4Rzqe9NBrq2QjXUzBzyQGziJG36gAiE1WKo8iW0F08wdHmazX6SyNmJZ72Ohqp7YY4R226BQBVRnOeAeJ3jkzAeQ5gJdZXIlIAcCURgf-TuJIgkei6acVgWtGymVwABZZ9lVgY56S03RhHosNlgfTJblR_2k5jXrlQkGziRQH9G9tI_wPewumL30H4DrrJp_rgIIMjr3FLqUfYTj7jKl0u8cMigX0bt4fQFgB2rL9P6eJCdnBK1xbTpDlesfC4Dm43c73LpHM2cKYBhHwSddRBIKwZolKVgbp2twcR1Y4FO6iolKgpSCdALpXhgMx8GzYrAtl2Na8KP7YwihnR8QGXHianNWn8Fen2ZpEtL06ojralK8HO8XKShClgJtZQT_nOcX0eNMWGLGQw6bdwaDSaKPbLjt4fhvt7foB16snCSJJHHOp4gKv5vigEt5DbevdaQlaHVmeA5MHCegt_4R5VcY-KG4-nbleaor17OIn52sr-7r9AevqTOwkQRFGWEj8gxhOaQ9QlVw0qKAfhePN-h-c-Y_yefTHy6rM6hIQCZb-MqDOjD0lhGE8mcXew81imet0oriUi19SoQKIA64lyXlLgDVV3Kob66dh44BiFzAcw7Obux1GZ10Cvaki5UqWHcwNtoV0UyjJzLeA==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "inspect inverse kinematics branches",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n model=helpers.joint_model('left_arm'); p=await helpers.transform_pose(io,[-.198,-.22,.87,0,0,.70710678,.70710678],'world:base','left_arm:base')\n out=[]\n for seed in [[0]*6,[0,1,1,0,0,0],[0,.5,1,.5,0,0]]:\n try:out.append(model.ik(p,seed,budget={'max_attempts':30,'attempt_time_s':.1,'max_time_s':2}))\n except Exception as e:out.append(str(e))\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_ddb8d3f7aa744130902ea9827c5a15e5|fc_03880fcdb65294d8016ae26e7fb7348192949bf1a9101eaff4"
+ }
+ ]
+ },
+ {
+ "id": "b444ccfd",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:52:03.306Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224322.596944567] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n [-0.5526204907538345,-1.7623647377941796,-0.6392799169876033,-1.1322713387442476,-0.513594805751331,-0.018117428053433485],\n [-0.553866303587819,1.9944921125413446,0.16136065569054742,1.8416406163084864,-0.5113207015289282,0.016809955678195713],\n [-0.5538701711987519,1.9950389022424122,0.16140448051613965,1.842137792565355,-0.5113167030912799,0.016803814033760394]\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "3e92b677",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:52:16.178Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Preparing the positive seed**",
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+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26f3e24488192826df4f01c8b3350\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking coke reach**\"},{\"type\":\"summary_text\",\"text\":\"**Testing left coke reach**\"},{\"type\":\"summary_text\",\"text\":\"**Testing bottle reach**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m9aCKzlX5VQ07qAimVMvKSy_C6SDmXNFGI2T6uEJRmyBYJU8-a64NUntkL8IC0qiV1iO4JQzenrwbWcK_qGClyTFxXEPr1bTwZoIl9f8v1P91h-QMvz96ZIR480dMDXHqw3TxAaYPWiMZy4DVEZSnbJYgxZezP1YDKkzK4Dpfot4POMiKr369S9E6gdpP7B0C6SIdG2shR5Xeto56Y-1SOn9NOC7PU2gnC8-Sbirhl6NrEk3DdYg3i12gKI5pR_6xwaUkRAzwZKlMMtpZoET3RkkxmAoBDd_k7CMQsjTkgM94PgRUIrXBot5uO6ry4O2nQ6xPVrd6J-HUjumOsSMx-rFOlswLoezTAc4aKH2uJwqhYoe9BX0MGNXseyKHiCg97n9fmcGsfJZH-DRvikE_46omGOWt4MB9Zc9bxyd2Cr0MUXzHpz4G67JK9aGn33trPI-hcXAo9Z3odIhDcup-SPDxG9_h3zGZQbfkTrwxCqW153UeInbRHivZZDtzXJdv10N763xebTrmTJ37AWhQRO6Hl6MMfizT5YNLOQW1ziLxH722cVF4wrhItPmvvHz8SE4qTEoC0Cqf5YFkDsPDE9XAs1U1MVpPxs2bOAtGmn3WHK8GrQiwE44s8SwRM2KZzTGVl9Yj7yvDki4WKwqcy9fVR5uU13Opy1eD_ZpBZqmE4oQ6WhvgvEOhD4ULLik6Ei99LLEWrHBpbi7NDVlPzyo2eu9l19tQN0BzaxiIjykZepr3h_Jz9fsfOONEMWFhdUYkCy0PXY7RJbafY3yjArkRB8IzanD0fx5_cfw9VbdvvxyFPKNpVPGn6lHtRVhwG_DDO_bZ443crhTjNIQ5R0DO-HSDEHuJ04FBldUftsvqzW-P78Co2Khf1eEsh8jsjipvh5pWIvRjfSvNNMLV0VhlWsMiXBX9d_tX8AzXR1RIWGSPifR6e0T9GrnXwzfVQLDDGqxhz6p8VaMhGFs7Z6JfTSxk1ow3wP6mONVcTepytxcsClLApssRvc1-n5U8HvW68HEnZmzbp2yrKVlgw9YHHmDRWq2b8gpueeQJ67FW0BHg3BqcvZhwyYtuGDsOoOzkBsfPiz-hI9u6OedeEnrKIBkjBvzHciGsniUqtdsRQbk85mykxWru-Uuho7J24LbwnxoGle1ldbVIarybW0w2P0vG7GvKXwNUjj60Cta5eZgOGr__XzrMayXU3rFg8PqvfSEdCKJYOozpXUJYsG-WH0RZ44b2HYYJVpnG9WlWZST3-8P6egf_DsJwgD2Rn9SRurzKItGzH1nbJOoYnOOZ4Pk-2uAKCW_fF-mwwAXYNw-AOtGmEPfJLBR8sGkQ7ojXNirj_O6HU3o45fl41TGUd6bF16kFHtj81K6fQOJRzafhS-K4MTP5GCrZoKMbvrzAP4MaetF7O4un8bYoutpniRO4OvpjZrLQVgOLHEcN_OA4YPBlAMJHvV7KzhgaRFrH3OoVzs7e4zfvxvgynpXGbE70SjnfH2SusUTO3Lht2QrvqvZY-K8r7Mn7YoETWheOXFgSozYGA7CqcBBvpNfjoiAMSEXuN8uQ93W_vRcMC7b-h89dKghOmcIW572lU9Y8fzmpoTUh3v2nyGy57NfYPTydN0K6bs1TLUUhPwBFd3JwED91rfDKuzspb0JT4K-q9-gB7z4vL3IRFBTIdpGh3duz7erKr2YDkCBGwMlXeyeYEFhPwAfmBijN6ET60BjIc2U2C5CsnC9BpHV3ysdYlVXne3jEbtjQY-HrybdPomqhSdWMHa-c6fXE7lHxEdhArUUOmX7XFDyXlg9JkeZxg9A6_l0AzFVZ6BOY-EvsEUHLhvUFN3ia47hkh9fRKiwMH4_ZEhvMQTJCo_94Ntkl2L4U-l_lxt-HxV7La2cLrDrAsOkemMDrAzCjYnEm-lyFwbeq8EWLgxs_J6O0pEjD_nVOgBHj6OXAgzqmeIhnm3fIEJo71pEsF4zROvpuOgSxb1T9iAR2-pbKNheXOTJBYua3TfuchQaxTsv8I-jF9hftnbeg5GHjEEFctO-Yvph3dPUprRi5pQ1wlNNpMLQhSbYyQZ1UKVo1JBqzHtrLta6-PkxKYUT-phD-gf46q-K27qfQj_gj7p4Tj4RXx0kNFFTzbWYVWb-KuRU-45pP7MiQKPX4DsVHroLOlHq_6tv9qndLkhZgpfkzrndo4GLSFvDKhYZlHe1uH-mpRA0lGj3OP6sKMRcBC_YSP98PXSE8hkFXrbklBtsBwF-lyhGxIeXLUnBwJLowMi2DwJeIQgaE9O5K6DidJ7eBjOMFHdxsSG_JawG1DS7GGX6RdEYH129ZnoLdjvoiDL_2Ne4zSA6D_hGJA5KOvrBjxG2cCUB1K6wvI1pSGUXiY7SPKj1kzLMA3FhcPaDnKhUtyDoA6as2K1inqpbnOAy-BFDzefOROrV2c79Sxrj0MyUx_hOMnGkBcuPGoSJwU5-1czW6atgVN4Pxe5yTIE5au90j-ITKYioCZqjaikw2jhm0CV6-SST2QCu0e9rPQ5YzE5yGOrjJha6lZ8qPAa4LdayubvjypZjmK1aFXo2oeCd5nNt0q5vLi9o1xypEE7J7q9n4-BE4spXkhSwcX4bKZh75CvkRIP532UYgKa7qZtF0XlQDDT0Pt6hO3e_cQzdu8ksI5kPB_EcBB6M56zf5Xl440iCNGneFIJdC-gHyaz5TjcTz_ex1kt1_l-TCSXvgoleXfEegQz668nauIYcw9Vswi6tyCS7a4_PcK-7KwOM1C9geeMY8UafNG1p8vHa8cvyotQ1hP98EfUOiOlHodZDcn1Ldbt2c2QWw7nGm6LD61Pb2T-K01RYUCvfo98YUb9OI2LpPmaYLSV9Kt8bAJ1koL1g71MBGwRnN2gufsPuOlyo5tEwvX2fMudMt1FS_zhHTaS-FdEPUDKVJxCt2YXTcvj5iogM2AZM9GbDHyBIIQv5YxOlufpqViAmzJS19RfF3kNpKmrUf-J1nIwoo6z9wWtCMubnbXIRWvHJkZnJhAw4YfjqPVv50PGWY5K0qTfqwbVJhzPeto5Jk7_p9AEJb14mgHU-9WnahY77FSSeOo4cVCOnQtS4UfPph_fvvSe9mu1JvkhFg36SPcbzoiS1SsyicD1LNOoYjipyif41BlmGtBscQ7v4SeeMOrzVq3lgi5iFmxSLx76Jr8mjqJfZ4KOHuBiAUZKQ6Z9wfMqqyhX8u2BlOaF9d7T0G0wq35xHiH28K6FR_I8er8dE7ooFgV-DLtmemfAVwokgFi_sJ_PsrgU959dQ03ghsY1MNCuR4sWOsEd5DWT6diT7f28ID2wk3w2C7DqYr0KBmWb-EonOudncRQZKBa1jjHfmKzEtJ0YdMw7bt9iojKrSHCFj_exNoLjA84UVyTXgWdpXyt2xvarfijgyTcTQRBDqcS7jeL2Xoa17pl97yryZxSPaXdSbMPBAVt6OlzGWGK1hpF1sCPvc1dtTSA_pzpYHYlH3xESM_5p-QNs4xgigbXUpB_CexKrLlkDg3eIcOAguxoJ_USZx5sj24IzpXHXCVA9SC50g5-8c2QyX0RRKXgeYwMx5n5-HufpGsIHA0L-cMXr_PKudyqcMAm084gMwWw-NXCYfV54bR5vk5X16oY2sTh3gelV9FgTqxcguGE0vvM4CxA0A8jd9sLogyph7-48bF34QUsz7F2xpHdItMMmUPNFpAdSPaV4NfHMDQL-hWooMyZvNpaExG3tdzdlOld4Pu930n3BlvMXhKVi2fZfxfPKBZlD8GrbPjpMyfdjPaL-1bxc2reEAc1zjKhF5HYOgnAllwRivlKdruMzCuDCyKNLU3pEk5j7mwLSzGWx1jA3A3aRyDfwzCDYoWAEVXCR4lF7Ro8l5qiCny4huCgLvF_nlGVpxFNF33Q3Us8ardwxDF4IwPv8tLxA945zOTa4z4_cckghM7vYrDF_LR_wP0C5wBaoemvqjfak3h176XC7sqwo2Etw-lvtitMrL4PosqpGNr4jTRfwD33R-IB18daSsuL2ShgyYRNSNiFFuNTIeCmQlVy_vQlGmCID2vOd6kozrvAQt5cJqGmWGKivm6h45IzzvksSFyPPGM0ZO1dt2AppW47myeIOjtAqfc8bKEzrVK0CjT3Dwg_VyiGglcdV98D5BfiW5lLi2ZFMs_Y4gUggwDppr14DMExgSv1sFrYaq_-kkHhrTnQ4Pk4Rr-AFKZMOJeQSnU5ANO-s5iutANhLkWOD4zHQKsa9xi5SM3ShCS-Y89kw1qxK03y5LWNTapv8XZxl-G4us1op2KKQxhQ9GBKQyzwk-2nMPveOaIfHmX7jgdzneKuGmpyL6v-5_tw5tGkfmV2vEbicafjegDneTIVMKxJQwHd2IMLet0SikrBqIHFbCgMQaZthhe-NYgpGpfRlq1Cj1h6SVeTEEQY_6fF5xbZtGdFCHmtksbSbU3V9HhbOuiFv8LpiOfNIX6yHRYJ1TMgY8wh2kb_cRQD4LcrYMpSESbv8xF1DN57bUpdvoLPBHDscr2EiMsmB9yDIz4oSXx1T7fwWnSH7SwqUHqEQHhI8iaQsKugNO-kP8oTMJsI8lu2kjCS_OjPZemTvSWp5ujJRoYftwLcHafVs0T0NO4t0apJTAOJyD8yS_avkFx_sAl-JJDZ9bhQDVRy43xLs12g3v6a6t2m32TlgVAx5_waTVR0HQXZgVPY5-TzdmdMOPk0LUC-Zi9kuup50zxja0cbipwcya2G2ci7MKGwhEZOujb0xAolxEznu9Z_fA1rzGv94ivqKnEwBOR_g_wrdJR6jnYpY0Hjs8mo-UQKIqH5t4UmHd1niGBBaOWZXpS85h6ZAHsCRRBYIc_iRX6qRHs2i9d_oL-sXO-PJxqM32yKKQegpZrtCZwN5PauUSyrlERD9tkSXF61O0v033SKDpwz9RSvtm5gcc-BNzsa91yCt1BpzmZFWn3L4Etp0XIm3uUpYoRj_Ui3UEh17O6dyVqSy_xkpyx6uYCtXQR2uKwF5pIvVC1u41AgNJzOmj-m_SEaoO4DacUbYonE8M8Ix32xOE0qpF8puZkeXy1pDwPbUx48qybkPqVsIjIjJzKMjVA2sRv1sLmfO3Xwkijcv770FFBHT2Z67XyZ4BwvYX-2dWUygL8aJi4dNLqkH4MqQNVMa_yCkaSHHI5-DJ6xi3nyr0qqdIIlry78khOTboSoxggZc8BKdRS0Ii_u0p6HRP0TiqDozabxrShvNkkVY8EWKmDuVgZlb5n_s9yklSpqZPcpUbWuFoe0O7sZMITXFuhwkrWmSgb2XnLM9IV_B-SZdRspqiNF_9l2J23hE4pSeB11YbUHsYOzlcfJWKIXCycNsfIWYBjQAxTonGzq-S0AEUJPF64KbDMmcmdq-0ZwNopRmYkiTJtKknZ6JPUWN3XM_T0FcDvZVGPoWXpO8QWGQ9hg2Xigx4Ma5_kg8EtjrVBAZUIjcmcKLe7ougT8_m1AD8DGuzmG8n1foGQyjRuAro2UMF48jimYjh69YC3fFqxA5JjCIRr5xMaO1wMFRN__40Pp3LheEHCdX9DVl7itakdgWwCnnLYpuOfjkoik6RABsgFn4gKSoYIMP_yI5aQTKb61mxWZG3dVSDbvAqn17JR-2L9Cm3zDjNf9A2mN-T2DCPub829qAOhdSfA8ADnC0YwOTGxvNBYnXb2KEwZbsIYRqNVxEJmgGhZPmBm4OB0xZMgGrSO6f8P6VEoL-lspnMgbWj6shgqrgL7e71I0T8N_d4sUqpOo9A2KmjTbyX5dhrJ_kefxDaqe4sJ-EID1jx2dIl7c2-boUp4dgUo_qSzjIV2M3gvaBrDGmD7P7ghTx23IFhid29LkMn7ItyzXyFT54TGWysAsGh9kZiu4qlYw0VPU6J7SXvBjdmjN4PENrH_9B3Ht9i1fP88B9KauzdExsMBe41jcn0EKcEq3e2-aO4QO9uxoYctQdXOjDg47uMgsnY1XX_dTWIKtdAsmxM1YGBJXxcNebERMyhkgQMNM_F9cni32zZgDS99jZskqmsUx_bUOzDmJ2WYD5-qzLGMfPnGIqnwRZF1Cg5py0NSZF_sKZBoEDu5PSOPzsFwp6himqvBO-TmPo9tjRdI34XMuKyC4zdK2_FwsZrm7J4jojoMBAF43nbc9tTbFtB-awwu7m567WdTaH_cpkNFNLTjbYdzEDo4kvLZblSvSEPwISKCjs8B9L_KwUj5zJgc1clCz_ehtWjTx7-V4VUP262aq4s3Y8lHWrY9HH9n9OUtC58FZF6r1LcIPV-28MQ809bcVhVmlnL-XAt2_2rbxVLmr8o3RB2ac_uiVjhCZwDLxuRt1qwn3YRaTD94anom5Us06yCOBZqSM-8zB6SPpVkAzuz19GjlmnxIRytjGjMUcMjrQ024jcOodpwKM3AzqmlQ8iA479WUDrHQOVidU_Uue0rwL63plH1lJ773PRYZgTFPEzztNb3_Lwa4-iFUWBA8fMBbFNsgCpdRoHlJEensFGHQsIuD4Rz-B0XVFkt7IFjViGI-o9u-VBsT0o4DsZVdBeKi5LlbA7jDqqYhksZDl31GYAIAmE_aWYV9uAkfaA5_LpxLwoeDoMnrpu7jfPMNJ5HZ6yPRmWL_LK7PjCp6hXzNPEXR2382z6zAelS08tF1qUs7ThCmXaPwtYVlrTRIelrGIsfK0Gckm3ogG7eKYc8ajR5vU8Haec-d2kShOGzWPztMAillnIvuFKKavew4HLN3YorQdiz4aZnEc22Lc3gUDyfdfRIJXEOcrlQ0Uzu4ePEHh35tp112eUTFYm_3nglshM9M1H9Tptqf2XQ1G6SLIl3tERs2xEaiPMm0TrH_4BbSYHPZEC03A92eLatylGVEpfgBZIt-YwbINdCBIoGwtodTNB5SOa7ANEfqKf87SKcxKRu2iXK4HoLDAnkdetBXNP-C4GUMfNOn3iNReVREt2I5qxtFQE1V9cQ7V-A8jgrXhTwXYSzq1DKBbwEJREogX86VKEA7yXXlbyngFS8UlUzSeZcurQRy0GkaujyCGjXiRRe15Rd11qQH7Nni-nuZq0rEG8lyZdJ2S9_VlbWKixhh9vdHtlW10cOf493h7-bKt_feS3BW1iZaa85yzooiW_KsXOvZ54yKjGr3TZjB1u\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "plan remaining bottle reach",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n out=[]; model=helpers.joint_model('left_arm')\n async with communication() as io:\n for name,xyz,yaw in [('coke',[.19,.12,.865],48),('yellow',[.06,.21,.87],61),('coke_lift',[.12,.03,1.03],48),('yellow_lift',[.02,.12,1.03],61)]:\n r=R.from_euler('z',yaw,degrees=True);p=np.r_[np.array(xyz)-r.apply([.12,0,0]),r.as_quat()]\n p=await helpers.transform_pose(io,p.tolist(),'world:base','left_arm:base')\n try:q=model.ik(p,[0,2,1,1,0,0],budget={'max_attempts':40,'attempt_time_s':.08,'max_time_s':2});out.append({'name':name,'q':q,'quat':r.as_quat().tolist()})\n except ValueError as e:out.append({'name':name,'error':str(e)})\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_c70a91f8fac24a9990a8ce9d010eab94|fc_03880fcdb65294d8016ae26f58edcc8192a2d5104c71efa528"
+ }
+ ]
+ },
+ {
+ "id": "0c11832c",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:55:44.476Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224543.725672103] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n {\"name\":\"coke\",\"q\":[-0.7682474838893932,2.8205441857806255,2.174066940855675,0.6465166651221519,0.015836629018606843,0.005026753078927928],\"quat\":[0,0,0.4067366430758002,0.9135454576426009]},\n {\"name\":\"yellow\",\"q\":[-0.5519639959914996,2.793350612445425,2.1392099935800983,0.6542416277664851,0.005085650161614391,0.005436249092634174],\"quat\":[0,0,0.5075383629607041,0.8616291604415258]},\n {\"name\":\"coke_lift\",\"q\":[-0.7837596704018495,2.0847705295916814,1.5159528392357002,0.5691906155097223,-0.006951084853310415,0.013880856415633741],\"quat\":[0,0,0.4067366430758002,0.9135454576426009]},\n {\"name\":\"yellow_lift\",\"q\":[-0.5705797685571973,2.131406981991661,1.5887848123532708,0.5431653775860207,-0.02002556223756075,0.013504624618480239],\"quat\":[0,0,0.5075383629607041,0.8616291604415258]}\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "66040d17",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:56:01.407Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Preparing yellow pickup**\n\n**Measuring yellow bottle**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26f6402c0819291e0ee682ba30910\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Preparing yellow pickup**\"},{\"type\":\"summary_text\",\"text\":\"**Measuring yellow bottle**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m9vZhPvnX0R8euDbMDkgi7xlFzTNq4vVnzjNJ186tasHThyhEO-htaQDwYzeF1L5DkYc8bcy79hWY-GtBAFvEQABpy6sc0GzNE0x-UiXYK9gWJw8AbUP0H1MCQiNn0k4ZzdsYlSOA4op2K5XbriHTTsuEPJP6-sVcXLDwFMrt7lHT9dGbs5LSuUEpU0h8VAW6fQzM3braoJhojoT_t3ic4mFfQJCU2ai2aotSKPMfQWxx5U-W_oe_bjWHork5m1QxzjtoiDTOhEw5z4KpB9QGyS59G-mbRNj1NrVB8wcdhc9kSTq5k9W-2Ym140TbMWtZy4NZEOsVgI8xCLHqlfUJefj38DwwgebG6VcDjpOoYkPlqcT1zWpidFV4LM1ooHuXlWWd2TJP127PY4d6lFMio9sWl2OxGKPZ1W8_hVdWdfocGW8iQ0DtVu0gBXB1IchFbpcw54VXB98Z45yiqYAUoanawYcK6ISklEpkEL-O3UeDj9JyZLDgASxshWtXGUMfPzECFeoRsaQ0roq4-owfUQPvMpiZUT8fQpWML2BqwyPqaVnfKoAe4KtIC0JY-BPbXMsmeneYd4ivpvKcQorIP6QXDMI9k-E3f7MBVHsVg-LWeRalBFWlr2Y350rVKpg8PNa7vfP1rminieGRP-qY4f4qk1Nun7CW054SBfUMc0xXTw64kFunQS7510nHcMH3qvlHnbVsnIKW5_aOi7jB3yVXDuwoHX1jUDqd1fLJ3EK1ZrixBd-vvNwXw7il6cqBd-beIDGyQvVbP8fHUy95h03WYG8_VvKcTJ7-cJFLpsRpChxFoi4JLMVQI-Lho0keeNVZfUgql8g3dY1_wU8g32dO7uJ3quaB7kazdSfOmKKuRbpLxlerVr0On_kJUVpnpriLIycVvuguPvkn-OSLUZTa8Tqu-SvjlLjd4m4PbdHz7m_BK6lT7Cv8usq8a7x2QeRbHFEHHq6swmi6K7bBDQ76MNQrTi9RudcrtLjhMebjRGv-agjT4p-0j8ldrwA3rhmtqbLEvvJIdMSegSmHr8H1-9MK2ESxG1C6aa4uUpGMBOe_v01bbHuhU65_ALbL1zv5OpwETAXlwkbvBRG6PyZsLhz02BnswaZD2X-inmn1E7yYFwbsR4WmysKzE6L-U3OYcvV5Vcah4Jl98eohUsxuq7U31CeO8nCl29LfhF-ffco-NmOAr16f2GiRWnJB1RK7VBGOEOpzwmSK7c6Ly0BX__6VVQ8FXg6AkXk_hZTadaPGOaAckoTFR3mPbgSw0dMnf8FYvtcO5OgQXlLK7A8lgzl5fEwBwHwFJZBrfj0DiJKIaU8O78h2ai7eMKW3lzHCwUs2abJvfiBoPCXCMDSk51LKTO05jbJ1vggv57a6ljM4zNZtUSxMLfAetZ8kSyB4APms1K7UeENOc0T4XID2QZdCeo0AhJenyf2y99SjIK0SxkaSSrYs2BFAile2Z5XDVYoJfG57GlwWE9v8RnHZiaUINmrVbVKhKohUPh2pYhmIrXQjw336S5lnnwqIxG-6vHGG1h0o_5JEZkLi-ikI0SE8jDKboRibBk8OBlzfcPtTzqY7NzEvWjxotNSgZ_k6UsZQ5-rils7xa0dekMf6H4sodPiUNbT_UDmYuouqaE4y3tfgMycndHhI7_YQMz-tHGUQ7O3lxxaCo9PA-5P1iigyGz9CY_4FbhvU7-DVTRKBqBlg13n2yBgP7C2voxVnyQRf87oe7CSy8wr1hgO6mhbAJzJ5R1DMu1XqfgYvHV2KtzBjIWfr7B74fco0DnoNZJjWV-uxbn-ur5b4_2fIhPVTIQpretSY1OEmApBdtzkpmOm0CL3DNVKacqY-222jKWbiUw0jV9mEWYWqW1_AbK36PhQGeQ3-68Yv1XKNALRnEoKgHpyWJ4ylSx6dOKsPYNf3Iz0GoL7h0wGX3Ujjp38OJcpJQw2as25DG4qYZ4I2KvPseNKkoI5RzDMBv7g74qheF81-B7z55k9Dv6knIpiPprdbG5_1Vl521a8mKYF2n3MR7S4eZqYPrbzXojmxe2ExXB58bJP67MLlDIStRpP2XFhZGWmCLCtb2bVApmhgdzQ3JqdF0IJW22dUjNEqVp4wdObBQTuPrPQteouj9ZfWGsIxYy5jNDsUCjhWs8ye4QZ2rXaZaKjFdcdeU4NkhjqzuDzRxf3dOChwZ6G3VPZVm4dOzTI_QUlvaXjOiKvq_dpgMAv_gGf9Jial9AaisbU_uelyLQVkQoQuoJYYTEXnN0kNBzo59YWf81yHuaaGwTd-xHz-ycsgL9UqCmUGYFJq6w1UAF8mHEZeS9zRqkGg4RCBF3tGxK2PfUCp85jzdO4zSsboQ39U_Zhy9HXQpylXDLlYqLju-Ojj_JkNAXS9avS6YaUQzJ8aGTfp9zFxgUDzIzqpOMOp9SvXgAkGd4jsi_DWfaiWBYVcZ9LJCWAZnf2n6htKB-_olFro5cz64uCEddEICgwa2VNYDootGjt057KmF46xp_PBT1Z_IlZSA3NpuWQqAiD9nAdWLdYKci49ERdbjjEf7IA44STE7PAJqbC68I1ZtdcpN1l395VWROQ6p_tC12cGsOaxfXB8lAVNqt3TscVCjtoA02ue8KtyWLyai6ZJi3sDuMyXXXGSt4lD1FAEUbMtnUEGrCZDpjfGAZBq5_zZbvuwoRsuKlc9IWrRpj1AAGxb44rxePUvwOS4URNeRknH3lJtXX72YNIN-gRrD6lt2aAKfZ1-BzhVSiIeLVdd-i3vVK8sj-_2EjHVfTt1iGYfX6IyjbIRKPoBkZvyJMzqfGQW7z4ua-gZJIsNQWSPwFY4B1tzym2qAL9JHLb5aMxcLiACoUU2c0jK2Q7Ftjye_2UKtzI5raLP9nz_JNvxL30fkMaQZXI1CUzeTQuIVMxaVeR4yY1pL39cxMDgjc7OXxC-cxus0FGdXQJQ2y02OU_SKAyBQxEpWR4ZWbOC-sf7zfz1vjYLs61EOqgyfIUm7JDAvHN5w1yDz1AJFCu3CR2Y1aHbR8IAkd18M96Q2RHgM1mO2gsBvLvsFBqm3pRJoSZlQSMWjsUfqfbKdnscUIgYL5Wo2BJVGliruyVE4E0xfklZPIfLO3uv--Twa26mLM2i1eSVH7Q4OXiaR1xxrjVlCAYOiabSunvlDnwSgZmLn21OfVdXnRm6UVdh1nSzPMHyJOD8M3fXTnK9x3p6u0zMAiXMX-DAgDm6FaItyqg5km7bb_cE5KamAPezmCyDFwX0Nfk9t7EtU_fWPD2LmdAtFMYiHqr4CHIc1GNkUzm-Ejtcp8QXskNU0efP9Gql_o2BgVs8wBSAeyKdEwe_aRBBlyD28lIueZpck7VbHubGwYzA6MrwzbT8Gk8Hwd9koLHWSvHcDUnKH2C8wmWTgMDvRuOVKN8L_Ds1Ijg96HfxATtnXdBNVkcX_VUEGFNIHvytacn3dlaT6WUZ0HpkOE0oGx00JU4vlzMLZ0tD4hNwMekOvgfGHz_xJQx27L7GnJ4A8v_CrgqCLoE-y6rEoLtz2MAMFm-GRZUx70PpYaDr1fR7NXMgej4d3wE8tXNvEOPzM6xcMZDaqZ7Rpbu3J07F5kVw7ztmvfjhtcZAIGFlR2IuAnmyrqsnMG15LEhb_RQMBZdVuNAWyLBT4ZLbLQ7eH_KJOMWnRwhoVNArLaJ79HQOAxWS_pBpMYW6yDgPyQ_w4sqQLQlywAICjVTxMecLRIzUB_G7ZVzliUzXALpcJOnILso7_DcDHJKuGRPreJt0tD6NTKGboulfVfDSor2Z_Yq_EGZ3dAqHgFskWHhD-x1a6SyPZhD8PqGpXTypzXF1E4Q0KlSeNjVR4mkqFmlFuPx5OlV-ewTJsmvYgisVLze7kmuiIBuiw6Q3kOc7CSosxV\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure remaining bottle surfaces",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,dep=await helpers.camera_frame(io,'head_camera');d=helpers.image_array(dep);out=[]\n for u,v in [(197,45),(203,15),(195,5),(270,35),(260,65),(264,48)]:\n z=float(d[v,u])*.001;p=[(u-159.5)*z/358.6421814,(v-119.5)*z/358.6421814,z,0,0,0,1]\n out.append([u,v,(await helpers.transform_pose(io,p,'head_camera:base','world:base'))[:3]])\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_2c4bd3b629dc45048425661fbfddf8d2|fc_03880fcdb65294d8016ae26f6e63cc819295374267ef4f87f4"
+ }
+ ]
+ },
+ {
+ "id": "5e3b2fbd",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:56:03.819Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224563.007108510] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n [197,45,[0.05447197977048632,0.18363281695971267,0.7914746286877076]],\n [203,15,[0.06005972182630685,0.18232398834126862,0.875493007530382]],\n [195,5,[0.04204036901406122,0.18984502660198344,0.8948837863355172]],\n [270,35,[0.18028540144849753,0.09326873128529545,0.8962015643731865]],\n [260,65,[0.18068970414215718,0.09767136948762245,0.8120035427331231]],\n [264,48,[0.1769171417661466,0.0945546611955852,0.8621660116854928]]\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "6460a19c",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:56:10.787Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Approaching the yellow left**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae26f764f788192adb3130555dc26ea\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Approaching the yellow left**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m94yiM08QV4UfNk4Z0-u-OJld7z3Vs43pNhX8P0roN8AhOv5ZhbDWd-hfOX_fkcHeWB_TTan8OPE8GHSMehG-YkHE5DmVEbkojDX9DJznHTGq8lMnKarV6PCSp-mYxH8pRaJBgZwrgBlk-HqVEGItxE4XlmiezZRI5b_UV4-zNCcoYXYc2gJnyp9j33Ei_AWfA_-vn8baWtfuexYD82du1wVJ0QJQK935XDTdg7FZngqWL1feYYG9oVmZGJ6aBjvi6EU_3m2oOF5jwDe7M5i-8Q--5ks7YyIYvT749OyyZz7uekk7Pf2wS9yvhxchNZAhZkfTtb9U9Bu-Ddw3__Iyhkx6Kehud86pLm1-m4aLD6ttJLztbMxA8lkrHTh7lQt3sUqrF1FylVikZETZcnR1F4qaPwpLzvNMtysFR7TkmdviYVqOm0yHPg7xSRh5bzMKiHP_WOymIXNsjILiq7F9UK0_9JINsgd8gHgICjdkFGX9Ouh3FAo5v0Li64W5sGTsVtkWVHsvZ5wGqqwgbu6BS8jPfiNug0xP9Ta-dUB_cBHXoRKyrW5AdjdnqHwkUidY86LHlFd2oeoGz2FlB3m06CT7rpsJZAVavTX940WIJ-dSXWI0gIMTXrMIXkpedZtnQBkBlhzF7KYJFpQmd5h7t4sEsRxQMNsjaLkU3Cvz-fByD_HVe2XOmK31EB_QGHUUFLImc8A_H2Al1VUfUwc0exXu66vgirgwTsLtJRVLMMspBorOt4nzUD5uCVBa219XzRAIUbocJxWaWfXYe88KRRKkDKnFT-L-Uimwno728TaIR7Dupu-0qi2_bTEnMBn8koyYc_x5DEVJUraZ6emDWnunUXcPGYll93pTWQb0856hShtOQWZ-17PebYd7SKOsNECyhBE-_4nOsrrrdvGd_kzejPdX9qZi7TvLhYxmlxAxQVQxYsJUHyaFw3UOFpymBl-gUx2w0fA9BEiPZvO4WN5q54rEaQktzOPWZW43xEIddhexVY44DAXsTZ9jd2DSy3yvboL2P10851ZaJpjU0EM_SM5cj1Ddwq1Ef-wZViYO7Av_DRkSYwOoVkRDUj1WKjx-ehm97Y1fAZzoTArTvofyPEnx9tP7daoEQ8qNY-FkdJNcrsdQhZfw_zcmHJrAj0Bz1i5qwtHfOzFtWNC3gs4W4CMgLvovU4G7DixxUZ7NlP9Ntvu4z0SmG0hIf7kUEYzw0mhnHb2Izzhk7_OTd-IrouC5V-p01SGWEkWBvYQzJMjYLss_kMvb9QhzcqET3Oqj4A4mkC3t7I7Qh5-jJPL_cZOQBDB1d9sCnVsY5xOBGPauuF_PhBqsZOtDU6yeIq61hYIHFC6BeAk8ranRuX-uLpgcep7dg8vn48DC4HwKeTtauC-RuWKHK11O-uEBAf4PYAq94HsZU-PsscWI7LFzbHJd6IS0lIXSR3R6w2KL9KYvJhDgGNeLLDybcMTBRsrIerPQw7OqSUZpnKOY6CDEDNFJrUjNQJaK04uSripD1gXqaCFNqgIz7FTZk1TF4fq8tBMm0N7Xaf9oBQhy_1q6h7-I-MP7LIZr51-3CE054H0WwXQ85_f-olfGsibLOEaW5by3_Bq9W8nB8hGsjyyJp86CyzP9sj4BC1L2iezFmNapRWaxAumygY_7gk8g7XxuAOnEGgXtQ8cu2s_vkSVo6p-VSOndZ6eDkNZF91cKibTGPgh0V2XUzMLquHM1zY0DrZfgeJAcwT0K8WUStJRf35DteLGJUHhO4Cp4jPRNEN8n26KLrtfK_IEatACBKGHut3ia4Y8yGZckj6ArJMY7OSqsKmYtBIh9vKr5MAYlg=\"}"
+ },
+ {
+ "type": "text",
+ "text": "The clear bottle is in the bin, confirmed by the wrist camera. I’m moving the remaining two bottles next.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_03880fcdb65294d8016ae26f7877ac8192a7bcc4ff06c6e2b4\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/manipulate.py",
+ "description": "approach yellow bottle",
+ "args": {
+ "waypoints": [
+ {
+ "xyz": [
+ -0.18,
+ -0.08,
+ 1.06
+ ],
+ "quat": [
+ 0,
+ 0,
+ 0.50753836,
+ 0.86162916
+ ],
+ "duration": 2
+ },
+ {
+ "xyz": [
+ -0.006,
+ 0.093,
+ 0.86
+ ],
+ "quat": [
+ 0,
+ 0,
+ 0.50753836,
+ 0.86162916
+ ],
+ "linear": true,
+ "duration": 2
+ },
+ {
+ "xyz": [
+ 0.055,
+ 0.205,
+ 0.86
+ ],
+ "quat": [
+ 0,
+ 0,
+ 0.50753836,
+ 0.86162916
+ ],
+ "linear": true,
+ "duration": 1.5
+ }
+ ],
+ "cameras": [
+ "head_camera",
+ "left_camera"
+ ]
+ }
+ },
+ "call_id": "call_9505612e357f41e0b601181c0afd3dc9|fc_03880fcdb65294d8016ae26f78a58081929076c7f634d33d64"
+ }
+ ]
+ },
+ {
+ "id": "ed3b0775",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:56:37.608Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224572.865750018] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"tcp\": [0.05147708742033642,0.2045278187007235,0.8629828751979567],\n \"quat\": [0.0012442963942044286,-0.0021552669022041654,0.5092927264227239,0.8605897543917034],\n \"q\": [-0.5445034503936768,2.769740104675293,2.054563522338867,0.720240592956543,0.008363209664821625,0.00577180739492178],\n \"grip\": [0.9996614374897697],\n \"target_q\": [-0.5484997194158352,2.7834866635540485,2.0749658177550847,0.7086049164412447,0.00849461950524203,0.005581543401104956],\n \"target_error\": 0.004640195326699464,\n \"time\": {\"success\":true,\"message\":\"ok\",\"time_s\":28.560000000000002,\"waited_s\":5.920000000000002},\n \"file\": [\"/tmp/kinex-observation-jhdi9t_a.png\",\"/tmp/kinex-observation-zkmskjon.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/ed3b0775-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/ed3b0775-2.png"
+ }
+ ]
+ },
+ {
+ "id": "10bf7ac6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:56:41.700Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/manipulate.py",
+ "description": "grasp yellow bottle",
+ "args": {
+ "grip": 0,
+ "settle": 0.6,
+ "cameras": [
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_668fe7f6cc314dbdaa6658b2da33540c|fc_03880fcdb65294d8016ae26f990f948192bd3357fc047329c9"
+ }
+ ]
+ },
+ {
+ "id": "82847509",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:56:46.905Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224603.816933881] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"tcp\": [0.052825427222747336,0.20584596398041766,0.8627488049225395],\n \"quat\": [0.0014806761308315045,-0.0011401104489938575,0.5090236070610991,0.8607505301775115],\n \"q\": [-0.5453270673751831,2.7777156829833984,2.0716705322265625,0.7096014022827148,0.008205556310713291,0.007084341254085302],\n \"grip\": [0.7739523974331943],\n \"target_q\": null,\n \"target_error\": null,\n \"time\": {\"success\":true,\"message\":\"ok\",\"time_s\":29.16,\"waited_s\":0.5999999999999979},\n \"file\": [\"/tmp/kinex-observation-7uqteqro.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/82847509-1.png"
+ }
+ ]
+ },
+ {
+ "id": "b26612cf",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:56:50.222Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/manipulate.py",
+ "description": "lift yellow bottle clear",
+ "args": {
+ "waypoints": [
+ {
+ "xyz": [
+ 0.015,
+ 0.12,
+ 1.035
+ ],
+ "quat": [
+ 0,
+ 0,
+ 0.50753836,
+ 0.86162916
+ ],
+ "linear": true,
+ "duration": 2
+ }
+ ],
+ "cameras": [
+ "head_camera",
+ "left_camera"
+ ]
+ }
+ },
+ "call_id": "call_c3bbeb94b3df4b7ba3f237205beefb8e|fc_03880fcdb65294d8016ae26fa112ec8192ad6730590b8c8396"
+ }
+ ]
+ },
+ {
+ "id": "4a031853",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:57:02.594Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224612.139791819] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"tcp\": [0.012475983380957172,0.12415535121015182,1.0325882299616729],\n \"quat\": [0.0013523926468964947,-0.00044605020363605173,0.5105743815543966,0.8598324098181513],\n \"q\": [-0.5547859072685242,2.128363847732544,1.5929771661758423,0.5379608273506165,-0.01129952073097229,0.01545263547450304],\n \"grip\": [0.7797582962296226],\n \"target_q\": [-0.5614852376589563,2.1161047986303942,1.5853120475938565,0.5314918774258239,-0.011183534532282036,0.0136917382097596],\n \"target_error\": 0.005427175903790725,\n \"time\": {\"success\":true,\"message\":\"ok\",\"time_s\":31.560000000000002,\"waited_s\":2.400000000000002},\n \"file\": [\"/tmp/kinex-observation-dsx7lnz4.png\",\"/tmp/kinex-observation-wfdkz__a.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/4a031853-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/4a031853-2.png"
+ }
+ ]
+ },
+ {
+ "id": "ceac11f4",
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+ }
+ ]
+ },
+ {
+ "id": "2d42d2fe",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:59:50.835Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Reading head and wrist**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae270521bd88192885f2cdc5f51b0ca\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Reading head and wrist**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nBWCu25WyrAaraNVsSHTC8PzCAOgKxuFifQDEiQRGnkEdNlNCVGdDYm1OVxBnCoQyudlsuV1nP6UT4juYSEEZII4zbmvarQIXZL3veTaWeXMzDS4Jv2NvIL8ZL05DRMY9AKZ5cD5xP7g8y0bde5gmH_YFOeDyJ4mCGFcM8FdPDIIALWMod5Z4C2ftqXG6jyXzwCHDdawd91qbfBWPorQU3V78cKCpLLskkvbmZyLC7Bc_8AYvdXLNjvCEdQfe2PpKHX1rbKkuYxc9IjXyKellxKV_5dXRa3INjzGck2yVdBp7p-5tfQVDmmAszY-JKv8h904GXLPazWADnkdW9G115g9j14eg79cFhPMssRNxDQ90AaVbq7haIQvMs19Abff6pzwcM71PpgSUteWvv1ETrkMWI4rwRZ-5dP2SEr6itEfCh0fWT2rdJmlrkp9ZZuhBk2PSp4rEwkiQDAkhGsm2yI1T8QQ6QbvFJNIRa1_KqT1eWHC2xlo-RoBfzKfH6MJtnF1rNb9V-c9jV_35KC7zMU5B-SZPyFt0_iCo3SOvOQNCGx19Q1RbaLaO1lhs0oeS3XGe53U6u5ph5v36T99nJoX9foRIXqqGnyii2yVmixWXiUYn_KfrZitO-GJozLDU6T7eKlP5Q1BUH_lRn1EZLFQ3w1miwZnoqy2Hx7ofkRytnAtiJHhK_PgcG53zqVuqUlwK59WGPHKeL1k9XNx_xQIxWh9XH6jbLlAM5btWoTWx352d4UAR2yNYX-doWjzvETl9D0senfD8FIWY2m88zg0Qq32FJNxR30esZJuwnMAkvKbIoWQOCgmO4aQyrx8ULY5_aPOI8DSXsXCa54YpVUU_kwoEzj6rGfAgF8IrVl9BDQTuqZzFUUp5R7Q-qsAFFPpTumCiR_rXBaul1PLpN5B6U6i_AGYa8T0_wbmQQYGemRlRcV-Kn6_v11xIFws43QgyLYNTYFbOO5wWIles0Yf2D9KvoXT8djWEtT_lGHUTJDRYr2L3oo3qS2ugaBnOMaLCYVpvFmbNU4OnXOhH0SzBJ-xELrJ36hProoSi5rsbs9d9t4S36G6ntxaH4IbLfNZjVe1D-Jo72VTvQvsUUdpum2A5u3NeIOlRa-DvsTjf779g3NgpVAebqJGp2XzodzsKzr_bOmfhXejiS9f0qDnYrn3H_kIOq_7jh7hB7TVJQBUnWOM5Jxy4S8spJ7hPgZDWukCox5l6ftCVEHSpUfgPEpQKIzQkHKFaBGxKPyFSAz4RTRvR991ejlTkCv3qFLy-Q8rD5ljc2Wn0lWff0ZKGKXsPcErzfaEBgOuSdV6jfIuq6wrHWYLLjKrlGPiP1Wg7_UHMkSVscXoRByAdb6bcnlRY_DSqKSw2vDebFCq_gOIh-TGNlVlhcVqIiaPmuZK2gdXqNGB_8qUhwD0Y_xGliYZh3p8cRENk_WZ8MljNyf0ReJ6qMcq9b3B2v-PHEDsTIqUE9oMfqrRWiEbOshfKFIA_FEX4bxFGzthpQDegbO9CzVPtMvlXiD7lodWNBRCJjhj3YKi3zteNPzF0V9gASx1mDSvKWCcvA2L861XXW83uLOPjp5zHLT0tvKVpEvWDHyTcDSCkdFASGzlh9CwkvU3-dHHgyPuKBjP5oVlzN1XxLux25UP5Mc6ymb-52Ym5PhWDlKZbXpPU7PP4-3YtgAdWoX1qRTBg7jH3DCpgkEToZqARk2hJiM36GrY1-As2IPh9r1FbDzz1aKowlgcryD5LcGxzv1xtax9_9lU28irxbP2anDBnN-Bx2LqRg9YVlYri5EDfA0adOsrCU59G0bi9icutAUsOgd2AfUflSYMvUVSSphkDH1w4OoY9N5rzk8WCSDbte3U2fRK2ywiV3KayZ1JTUbeR5dQ-21AbZCP8UqwYUfPSrhTIF13M1Nl1HsAGE8tiuLLLhruJxy9XmC-Klxy_aCDearQndDrFO1FsI8OsYDbOdpvHyTJAoT__L8xewymyiMmyLi_IPYHjlVHnpmk67fehrY5plulwOrab4bZPkAqc7qmDrOmcT26y0DUNrBK-4vyNpcKbkR6PrcLt27p-1d3dsYrwoKbwQ=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "devices",
+ "input": {
+ "calls": [
+ {
+ "deviceID": "head_camera",
+ "action": "image"
+ },
+ {
+ "deviceID": "left_camera",
+ "action": "image"
+ },
+ {
+ "deviceID": "left_gripper",
+ "action": "joint_state"
+ }
+ ]
+ },
+ "call_id": "call_99772b019ce54637a450fa554edd019f|fc_03880fcdb65294d8016ae2705681248192885c5ae7385d9fc1"
+ }
+ ]
+ },
+ {
+ "id": "5306339c",
+ "role": "toolResult",
+ "tool": "devices",
+ "timestamp": "2026-10-28T21:59:51.121Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"head_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":54.16,\"frame_id\":\"head_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-_7ve1dm1.png\"},\n {\"deviceID\":\"left_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":54.16,\"frame_id\":\"left_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-dh4luhs9.png\"},\n {\"deviceID\":\"left_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.8859383490952579],\"velocities\":[0.5435731939294122],\"joint_names\":[\"left_gripper\"],\"timestamp\":54.16}}\n ]\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/5306339c-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/5306339c-2.png"
+ }
+ ]
+ },
+ {
+ "id": "04875e3d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:00:13.590Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Updating defaults and checks**\n\n**Adding an error guard**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_03880fcdb65294d8016ae2705a3d348192947c34536594c223\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Updating defaults and checks**\"},{\"type\":\"summary_text\",\"text\":\"**Adding an error guard**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nBmpe_sJ-uLduHia21dpJYQclBwioQI_vQrm6BtWHfDjdeSkxmdjNKeMX2Zl6k3PrXMbYClBvr2eJLPxvlTLsBUXD-YPW39UW5wzFH3Lz4TqGgUOh_RRJ0ckj4X7anJoikoDNABLqv6VyI8b4rQVC-R9vmoa38Zo36ec1i7fagbxhvH7HGZOADq2JluhojO1FxKmnofyv1nD3KLy1SSInxxJjivW6Av76Gc7NWfCC-7b5y9IT1oAxG4Mp1F9cTt4hFMe-E8xvtqGJDe9BLIddw1CXrPGH8Agpoakb1cbvBOAS-AICHEdzz1mxcmKA0oKK-wQzuc2ucI5844z83DQzJ2lsm-wl2p6jSAwBOcbxV91dzyszCJ6IqWwunSBJ7YFQCMUt3m5sRyhaJDAwN7OZgjQtCDZyr-AGhckarQtzsXVIljNKi31eSW27nzRhatjLKU5gsiOPJfTAEcWODpu2mh3zwFv1wFfNjswE6zCLr8tGEMJXiIRsfhFaNOz2D-vp2Drr6Rgco1gwEBV-ZylsEs733sSJxgszU0GZNM5N3oEQ592tw_MivWxtj0sk7jciYUEhsWgR6F7cYpWKYVLHnXp3AOoM4SqZyL65-gV1oAs97cBY3nhylfYw_PDjlQwtatPcNObTBI2oGzQOmrvZRsGgV3z3mCSicd2C8StsdTB_6EWtLa_yJDXE2bxrktFx9_YsAGsdRQ04k56zddeK5ElBRKCz8uNR3nGQb0n8v2rj7eVMmouang4K3xCQ4DNuF9ePgy4fO2MbB14aYzuq7dVOP-FWoSrbC6Q5Wqmq75lvJybemGGrJOO5VfwK6APwAaSHUD0dKK_qqpbM5i031JzoBPc4tqgEKrPhbc6BLSPzKSDboS6t7O15CQzyHxCZ1pzqivhumCt2GTv8Lnz9n2oo-4v4Fq40oO6XpUI4_QaomYf_9tqO_TWMCy9LO2I5lDl2ZDenCIYAqTixXMnzSfYl2v-2fh2IxBtaEUZq4mnhzgmgGJryyqdvqvNrclRrDiFdOjSrBT9_zAooKYBVnq_a83y1RA3CCOJTgVooEyYYnUiFIXhvwSHQO2cZxE_NfW03NfjJKqOPAGMmnqneHFDPAh2LHiLNvPFmo5yYjFXjta-HQW68EGDRVDAtTCRzpC-GJQJhUj0IC4vUpDyN_dH9b27PngiQuHEzP9JIKnhjIMmKB0xQmfXYXoscc0swGmM2y0abxFqeN0XTUBpHOD8pqjQRyiiBDUi0co9F23mOy7sElOMXy4tj6GvLQMuAPdevpK3lRKXj7A_MS51jWZ4AZItePTqRarwzzpXd5N5Zhne5hgsFEva868MeokpekjG4RmDxW-z3eBMmUX6-TzG5irCmvG1QuS0l3pB6d8PMpBW48SVzzOW0rqTGI2u9niAVxmVVtyLbC-eq2fy47G7rZTHc6S3M2HcK86TeUXHsJ-Lb9MwypfOJ3wYZqw34N7q7F0Nak-GYjvpd97YuWbj0PRtdRTDrd7cB9hck1mppcq-jhRU8rRh6h8nX1Z0IO9NTfn5PNFC-Bp6o9-HzxbZP5ZAjs_cQxs0P99ysBc5NXmtgBES5M8acizTcGedIyesEuQFMWL942oSRg7bqQfq4AjioEyYi0SBNG4c7wDSj6dVLg8-9_YgW4g3h7DSt5cBfZ8P2pbe4mgnx950PngKUH6dH_vyYpYRx--3YyoBRA1N-HEjwqsy8tNmZAnJZdyrXhuBLVceJr9ScVTgBGjpEL9pKSmzdEhpo_J6Ty5QNcA8xEhmXOVi1WRBb9NaLYomKN2iJeiXsPZ3fOCsx86uXJDPuVTPPfU4OeYAqw6AZt7t--O-evoxdAGackXmcvY0VQtDPX_S3uvggJS-ykVcISGFwYuf3pttv4hlgU9u8nj0qgfVpB3M1rIkNGAeB6ETVlfVdkjNXqqTQM08eJHLAZSiEwiJGf4_dFF56vD12l9EDkZODBXvS62APwy3B-r6GH9pu_E4zoDKcmIQjiFQvZ-wo_k8lWjrsShgjHUI_nmU5wB8pba_q9dGgTXmNFNj7lacf_kE_zBZPuiHfkqmV_rPGTd3VEnwEKTuwJUgTfWFwpqcMQv7tWnhVnncyXaDjKbNR4juMVV3z_ASge-WLMgR5EligAPoMVhDuzlnQQyQ2-iny0EV7QyR2bRhc4HBaYjsiDv4P9zs5cmqoa7JdJOD4a9XH40cp5U3Mzbh17awH3o7eJr5z74HQjCiXCuQRtLKlzVZtCu1WTiXRlm6EucZeEt0FvqpVo2Wv7ekzagVzFiOc41qNW1aqVEWRM8cXV9ptUbHY5sweDWvtkIzAuzQ0XF_g8sxt5VwDNNB5O6NU7lywoE2q7CqnReYkrxlCGUZbHoFUho5M14-WoLGw-EaXWqTzncxwRHKCtlgY1SPYAWXTir5_4QAW-rEKSzi3l0BEoFNCJKthaF1FwDJ3C_kpjwhVPAtGUf2ieX5Ac4O1qxfsL6jtCIuCLKlu0j9FOKI14sHGN5hI6SR5P59hpJghDRI1WYNK4d4Mm-1qnZy5mQYhgC-xUOsAgNML8cUZ6dN_iRwpZ5zffVXdxC0YaiNtR3rMDee3ld_-HZvI_pDsYBZ6inMr94tyNQ39JKKv6g0ctLwzasJ2i6RZHSD9I-6xjc-rdYh6qsws8Nw0uxDoiaTOGChSTD1gjP7Xnlev5tfzcvtwtc6LgWbjB_0CMM7DELO5MMLGr52UcKtV1wi7uB0UBjA_HPGJ0kQXgbNUFuswUFTxwmAnHW77K1QeKA1_3tgpYdWwjJHd3TcMpkRr-3EowPAEtBSB9Br7bPyWa3s-DldDhcRmXESwaZZNS00Z2x-wmW-RMomuxmJ9QPK5X4T2kSbARxymVGv_LCoNrq2r-Hhtipg0C2kV_R_CUg6wkj_ivOM1jBHCZL5J61ODmrhbW0nDkHUKW5dXoYfS7s_nTAFvFJci4Jocw2CPoFDZb0k02-Jcl2u8E1JS1ZaAUE2FxffY3RDWLYIXSUL-YNfdKxJABcRATd7kghInx7llik3CwxVArAmGR_x7dbj6j3wnpLZ8PBYUKsfoZ4KnYMqo9EkvO-xtPTUvPfcptkcUVVhBj4h3_IYSDGLsPS2WUZ2diECZm84YWYi2ZuHvp62kdTsqYlJmUN9BYZAL2hsUUCLmgjIze0jtBfyUcD_ZLE0R0IToleWKDAmHStbKz3j54zvM6SFpq_3ScnAP_yMeimSLHBwqGYUkkJIddj7N5yA4o3LgIUTEdv0bZnKcVnge3nAHzRSThyD7qWNG5vQOX2wxzl3Ano2uwDxqIgPTmeJh963_CcngWt1Pg1uaS2l3padXiBudtjTBCkLs5gWBkMWHJmsUIAAzg_kjnKKde6rbdiUimHilRpUZmBjnmzAc_-WHKQYk4FyxhE9ChnMRzaPd6XR1h8zHumRKX1DjZKHJxsl6Rcv82iKjKLLZ2R8EhWH5EjtRp5gj8FHH9cIgYLGiSB1gG7E8qYdmfRrqsJ7P-E9XO7A4h29hFjqdtejBDCe1UDqYaankVgWW7abkxJSsQImv902U5HatRw-4ZVr1hccyWk13tAw5eJsrdGZwLmChq7lFwDdI39ajEI3PqziVXXFygQCg6m0vNJWislqtUe4BRNfaya9qjQObqbPD-mfXxQK78mln45piqBOC1nA57PRl-e6BJvaodBr3fAyMWLI3ZbohISt4lm3uFgD_GFToSnsxXUKp-Si0Tbe1zoPHE6O95bJUHPmEITITriFYTdh44r3krQmI4Xtq2kCFz57Tak5w7vHK9JtL-EKJOdmdzYExIfPCk-SMRUcBpaaoLPXdCjq19vJQkAblbO41btXMNwMe3Qc-AGbydVDTj0_MG49E5s0_LZ1zg1l-PmtT08Ain7zfZib23RSQUHv494pwvram7bAC7_7IVH5oaOf2DX92Xoear6nOeq_lqQgrqk8q6Vx4Bhw4ByHKftOHPvzXrdBGi31NB_Qeaq7jiUg5L57GXe6rx1-I9_sObP2XxfRbdXR4J6cc0OvBBk38SBrMA1Dmrj1iVMxyczWwno1LdQW9cnOj_ZLb4c0BN_eS0-WHGExpOpnfWWEBL-iEuvyCzdfnmdx5frW4_OPHi27PAT3TS5xHGMT3lVs4NnvzcIX7_C7GaRo2L2tYC2IT9qEi-sPj-FHkFcsLH6ePrsaePhwUpvp7PXczokdVlFEeCtWpoqZoZAqBJd-3WpE60li9X7LNFUgb6NDrXXx4rBMk4Kl_ROc2wpPR-_2ZZQ8dIqXdXbM90H4sTc46AW8D4NnuM_IAZhQHklqOf8wQaeB3bl5poBnlmj3QV89ie_DxE11Ha0v0flxopn6wdBDVLCksBk6Lt8QqvvBlb7jMFEcJBrPXt4qefg39vuhoe8qE-qd_m2ua0z0aymBzfj-ePSKRx-fgggDMpTT87YVh07qO5Wt7o0_x8IeJslkMStex6aUKatBkmJp7uyuNkEzXTVR9_YaroIoGSLvMfFEPlMU5Cq_rTsh8qcoOdhl1j9deIiBpx1iBMSy9MB\"}"
+ },
+ {
+ "type": "tool",
+ "name": "edit",
+ "input": {
+ "path": ".kinex/tools/manipulate.py",
+ "edits": [
+ {
+ "oldText": " if 'grip' in a:\n await io.publish(grip+'.target',{'data':float(a['grip'])})\n points=[]; elapsed=0.; targets=[]\n # Default vertical approach, fingers close along world X.\n default=(Rotation.from_euler('z',np.pi/2)*Rotation.from_euler('y',np.pi/2)).as_quat()",
+ "newText": " points=[]; elapsed=0.; targets=[]\n # Default horizontal approach along world +Y, fingers close along world X.\n # High top-down poses can exceed ARX5 reach; provide explicit quaternions.\n default=Rotation.from_euler('z',np.pi/2).as_quat()"
+ },
+ {
+ "oldText": " seed=wp.get('seed',q)",
+ "newText": " # Avoid the below-table IK branch when starting near home.\n seed=wp.get('seed',q if q[1]>.2 else [q[0],1.,1.,0.,q[4],q[5]])"
+ },
+ {
+ "oldText": " if points:\n await io.publish(arm+'.joint_target',{'joint_names':model.names,'points':points})",
+ "newText": " # Do not change a grip until all requested waypoints solve successfully.\n if 'grip' in a:\n await io.publish(grip+'.target',{'data':float(a['grip'])})\n if points:\n await io.publish(arm+'.joint_target',{'joint_names':model.names,'points':points})"
+ },
+ {
+ "oldText": " files=[]\n for cam",
+ "newText": " error=float(np.linalg.norm(tcp-targets[-1])) if targets else None\n if error is not None and error>a.get('max_error',.025):\n await io.request(arm+'.stop')\n raise RuntimeError(f'Measured TCP tracking error {error:.4f} m; arm held')\n files=[]\n for cam"
+ }
+ ]
+ },
+ "call_id": "call_d572734da4e64fccb8c44ec8b9491c16|fc_03880fcdb65294d8016ae27066f82c819291b7d71c53e842f9"
+ }
+ ]
+ },
+ {
+ "id": "3ca82f9c",
+ "role": "toolResult",
+ "tool": "edit",
+ "timestamp": "2026-10-28T22:00:13.595Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 4 block(s) in .kinex/tools/manipulate.py."
+ }
+ ]
+ },
+ {
+ "id": "fbcfd4cc",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:00:44.520Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/memos/put-bottles-dustbin.md",
+ "content": "# RoboTwin put-bottles-dustbin / ALOHA AgileX\n\nUse public profiles and cameras every episode; positions below are observed examples, not immutable scene facts. No simulator reset or private state. ROS wait advances 0.04 s native frames, reads do not. Load devices first; inspect schemas.\n\nReusable `.kinex/tools/manipulate.py` runs with `exec(file=..., args=...)`. Args: side (default left), grip (0 closed,1 open), waypoints [{xyz world TCP, quat xyzw optional, duration seconds, linear bool, seed optional}], settle (default .4), cameras. It solves flange IK with TCP offset +.12 local X, publishes typed JointTrajectory, waits once, checks measured FK and returns images. Defaults horizontal +Y approach. It stops on >.025 m final position error. Caller must choose collision-free waypoints; IK is not collision checking.\n\nARX5 home-seeded IK can select a negative shoulder branch that drives through the table. Use positive shoulder seed [0,1,1,0,0,0] and first move to raised safe horizontal pose, e.g. [-.28,-.15,1.13], yaw90. A failed early command had 21 cm measured tracking error; stopped and recovered raised. High top-down grasp approach at y=.04,z=1.11 was unreachable. Horizontal side grasps work well.\n\nHead camera paired RGBD: world points from K and calibrated frame transform. Bottle surface depths are front surfaces, not centers; add radius ~.025 m farther from camera in world Y. Table observed z=.74. Left arm can reach all three upright bottles using yaw roughly radial from its base, avoiding need for handoff.\n\nObserved successful grasp/transfer sequence:\n- Clear: center [-.198,.035,.875], horizontal yaw90 q=[0,0,.70710678,.70710678]. Approach y=-.095, straight advance, close .8s. Lift to z1.12 in 2s; verify bottle moves with gripper.\n- Yellow: [.055,.205,.86], horizontal yaw61 q=[0,0,.50753836,.86162916]. Approach [-.006,.093,.86], straight advance 1.5s. Close .6s. Retract/lift to [.015,.12,1.035] in 2s (pure vertical lift at far reach may fail).\n- Coke: [.185,.12,.865], horizontal yaw48 q=[0,0,.40673664,.91354546]. Approach [.093,.014,.865]. Close .6s; retract/lift to [.11,.03,1.04] in 2s.\n- Carry each at z~1.06 to [-.5,.015,1.06], yaw90, with 3–3.5s Cartesian path. Lower to [-.52,.03,.9] in1.5s. Open above bin. Silver-lined bin is left of table, mostly outside head view.\n- Inspect deposits with left wrist camera by moving empty TCP to [-.5,-.06,1.02], quaternion [-.35355339,.35355339,.61237244,.61237244], 1.5–2s linear motion. First two bottles were clearly visible inside bin.\n\nEpisode ended during final opening wait at t=54.16s (~1354/1700 frames), after .16s of requested .8s. No further waits or motion attempted. Final head image showed empty table; wrist image showed coke leaving gripper, opening measured .886. Native verdict is owner-only; terminal/rejected wait alone is not success evidence. First two deposits visually confirmed, last grasp/lift/transfer measured before release.\n"
+ },
+ "call_id": "call_f208824e230143d3868ae42789834c29|fc_03880fcdb65294d8016ae270701e808192978ccd6e1a97c916"
+ }
+ ]
+ },
+ {
+ "id": "fe55dd86",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T22:00:44.524Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/memos/put-bottles-dustbin.md"
+ }
+ ]
+ },
+ {
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+ "timestamp": "2026-10-28T22:00:51.307Z",
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+ "parts": [
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+ "type": "text",
+ "text": "Transferred all three bottles over the left dustbin and released them. The episode ended during the final release; the native verdict remains with the owner.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_03880fcdb65294d8016ae270921be48192a4860fe4b01c6b96\",\"phase\":\"final_answer\"}"
+ }
+ ]
+ }
+]
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new file mode 100644
index 0000000000000000000000000000000000000000..c21d31355fe0e1e05b39707024c8d62e44f4cc1a
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diff --git a/experiments/robotwin-native/kinex-3/vla-io.json b/experiments/robotwin-native/kinex-3/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..250d7787ec0f8bfa2091df6ed87e28970cb2b3d2
--- /dev/null
+++ b/experiments/robotwin-native/kinex-3/vla-io.json
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+{
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+ "original_temporary_image_paths_recorded": false,
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+ },
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+ "image_preprocessing": "RGB conversion, then OpenCV INTER_AREA resize to 224 x 224. Model images shown here are reconstructed from retained input pixels with the executed preprocessing.",
+ "request_paths": "The logger replaced temporary input filenames with retained image-copy paths. Original temporary path strings were not retained.",
+ "service_response": "actions, inference_s and call_id are reconstructed exactly from the logged values and the executed handler return. raw_actions is internal diagnostic data and is not returned to Kinex.",
+ "agent_response": "Kinex helpers.run_policy consumes the action array and returns actions_submitted, duration_s and ik_failure. The language agent sees the exec tool result below, including feedback and images selected by its own code.",
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+ "executed_sources": "policy-contract/sources.json"
+ }
+}
diff --git a/experiments/robotwin-native/kinex_policy-1/analysis.json b/experiments/robotwin-native/kinex_policy-1/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..fefa2213c13aae7d3aefcabdc0ab1cc0a50501d3
--- /dev/null
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+{
+ "observed": "Kinex wrote its own one-chunk policy tool with fresh feedback. Five 16-action inferences used the complete original instruction, without subtask rewriting. It then switched to agent-written geometric control and succeeded at native frame 523. This episode shows autonomous switching; it does not establish a planning benefit from VLA."
+}
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diff --git a/experiments/robotwin-native/kinex_policy-1/detail.json b/experiments/robotwin-native/kinex_policy-1/detail.json
index 7e137b9c42ae4a6aa271efb9b822e2766ed4be40..370e1619d96e0c6b50f25c0a75e3e82e1dcbc99d 100644
--- a/experiments/robotwin-native/kinex_policy-1/detail.json
+++ b/experiments/robotwin-native/kinex_policy-1/detail.json
@@ -397,8 +397,14 @@
"usage_source": "provider-raw"
},
"cost_note": "API equivalent sums the native Pi session cost estimates. Subscription billing is not reported.",
- "media_note": "All three native views and every frame retained. Frame timing is unchanged; playback starts at zero.",
+ "media_note": "Three 960 x 720 views side by side; every native sample once at 4x simulation speed.",
"artifacts": [
+ {
+ "name": "analysis.json",
+ "path": "experiments/robotwin-native/kinex_policy-1/analysis.json",
+ "bytes": 355,
+ "sha256": "7139f27f993fd42fa065c8f9e2c50245f3473e732e3e1cd7321dc72c35dbd61e"
+ },
{
"name": "artifacts.json",
"path": "experiments/robotwin-native/kinex_policy-1/artifacts.json",
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{
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"path": "experiments/robotwin-native/kinex_policy-1/observations/0a0c9ded-1.png",
@@ -705,6 +801,60 @@
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+ "bytes": 17331,
+ "sha256": "c2bc187a7483e275c7ca8749539289f68352db16c90ff366fa1ac90ecf282d73"
+ },
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+ "path": "experiments/robotwin-native/kinex_policy-1/presentation/frame-mapping.json",
+ "bytes": 3504,
+ "sha256": "0d42a08bc2256ee874719dfd4ca65f950fc25be439ebeeeefd98937b150f502d"
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+ "path": "experiments/robotwin-native/kinex_policy-1/presentation/media-validation.json",
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+ "sha256": "0bcb415c305d3ede35793c0f4bd4789f8dc8b1c9ffc3a15f36fbf73597d00700"
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+ "sha256": "ac15e983e0afbe68b6c357a9563df0beae4c8eef2128af0ed33e76bd302a474d"
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{
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@@ -741,12 +891,30 @@
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+ "bytes": 10108,
+ "sha256": "4be2cecd21f48d2f0655ba32d367d83345a5415510b0730ab436fbe69c10f8cb"
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+ "sha256": "44fc4582fc1d9613b7d6236bc6b66d2809831937ed6c09fe5ef69997159c463a"
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@@ -0,0 +1,9 @@
+{
+ "max_steps": 800,
+ "seed": 0,
+ "episodes": 1,
+ "control_frequency_hz": 25,
+ "provider": "rosbridge",
+ "realtime": false,
+ "stop_on_success": true
+}
diff --git a/experiments/robotwin-native/kinex_policy-1/transcript.json b/experiments/robotwin-native/kinex_policy-1/transcript.json
new file mode 100644
index 0000000000000000000000000000000000000000..5229f07000d78f9c251567c164f1e93eeb413c07
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-1/transcript.json
@@ -0,0 +1,2244 @@
+[
+ {
+ "id": "3add3304",
+ "role": "system",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:05.503Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ""
+ }
+ ]
+ },
+ {
+ "id": "3e107627",
+ "role": "user",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:05.503Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "# Task: robotwin/handover-block-aloha-agilex\n\nuse the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open\n\n## Work to do\n\nSolve the task efficiently using the running rosbridge environment. Follow the\ntask instruction above, including its completion requirements. Read `harness.md`\nand the device profiles for public interfaces, units and calibrated frames.\nReuse your saved tools, skills, and memos.\n\n## Limits\n\nYou have 800 native action frames. The execution mode is `stepped`: physics is\nfrozen while idle. Use `world.wait` with `duration_s` to advance the native clock.\nJoint targets are ROS JointTrajectory messages; gripper targets use the units\ndeclared in their profiles. Reads and command publication do not advance physics.\nWaits are sequential; concurrent waits are rejected. A command or elapsed time\ndoes not prove arrival; inspect measured feedback. Device stop holds the device\nwithout ending the episode. The safety timeout is 28800 seconds.\nDo not launch or reset a simulation.\n\n## Completion\n\nReturn when finished. The owner finalizes the episode and reads its native\nverdict. An interrupted or rejected wait does not establish task success. The\nnative step limit stops physics even if your requested wait is longer.\n\n## Saved resources\n\nMaintain reusable code in `.kinex/tools/`, skills in `.kinex/skills/`, and concise working notes\nin `.kinex/memos/`. Improve existing files in place as you learn, replacing outdated\ncontent. Create a new file only when no existing resource fits; do not create\nper-attempt reflections or numbered copies. These files persist across fresh\nconversations. Update them before finishing your response.\n\n## Robot and device access\n\nUse Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place."
+ }
+ ]
+ },
+ {
+ "id": "1d9a472f",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:08.068Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "ls",
+ "input": {
+ "path": "/workspace"
+ },
+ "call_id": "call_b93e1b1d30bb49cb930b357edb6cfa08|fc_08ccae8539651651016ae26ac7a39081a2a97abc8fe896e84b"
+ }
+ ]
+ },
+ {
+ "id": "cc628236",
+ "role": "toolResult",
+ "tool": "ls",
+ "timestamp": "2026-10-28T21:36:08.076Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ".kinex/\nharness.md\ninstruction.md"
+ }
+ ]
+ },
+ {
+ "id": "2af5f111",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:12.659Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/workspace/harness.md",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_130da6a804ab47dd804cdd0d8f9c2d35|fc_08ccae8539651651016ae26acc024881a2b27bf65eb04ae0af"
+ }
+ ]
+ },
+ {
+ "id": "c1aea678",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:36:12.669Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Use Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place.\n"
+ }
+ ]
+ },
+ {
+ "id": "75216b29",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:36:14.751Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "find",
+ "input": {
+ "pattern": "**/*",
+ "path": "/workspace/.kinex",
+ "limit": 200
+ },
+ "call_id": "call_bf1481b3f06b424eb980c7bdd2b27d72|fc_08ccae8539651651016ae26ace7a3481a2b997a3d225505793"
+ }
+ ]
+ },
+ {
+ "id": "d0ba1d2e",
+ "role": "toolResult",
+ "tool": "find",
+ "timestamp": "2026-10-28T21:36:14.775Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": 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ex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/PKG-INFO\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/SOURCES.txt\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/dependency_links.txt\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/top_level.txt\npython/ros/install/kinex_interfaces/share/\npython/ros/install/kinex_interfaces/share/ament_index/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/package_run_dependencies/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/package_run_dependencies/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/packages/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/packages/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/parent_prefix_path/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/parent_prefix_path/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/rosidl_interfaces/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/rosidl_interfaces/kinex_interfaces\npython/ros/install/kinex_interfaces/share/colcon-core/\npython/ros/install/kinex_interfaces/share/colcon-core/packages/\npython/ros/install/kinex_interfaces/share/colcon-core/packages/kinex_interfaces\npython/ros/install/kinex_interfaces/share/kinex_interfaces/\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/ament_cmake_export_dependencies-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/ament_cmake_export_include_directories-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/ament_cmake_export_libraries-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/ament_cmake_export_targets-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_generator_cExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_generator_cExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_generator_cppExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_generator_pyExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_generator_pyExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_typesupport_fastrtps_cExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_typesupport_fastrtps_cExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_typesupport_fastrtps_cppExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/export_kinex_interfaces__rosidl_typesupport_fastrtps_cppExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfacesConfig-version.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfacesConfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_generator_py-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_cExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_cExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_cppExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_cppExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_introspection_cExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_introspection_cExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_introspection_cppExport-noconfig.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/kinex_interfaces__rosidl_typesupport_introspection_cppExport.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/rosidl_cmake-extras.cmake\npython/ros/install/kinex_interfaces/share/kinex_interfaces/cmake/rosidl_cmake_aggregate_targe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results limit reached. Use limit=400 for more, or refine pattern]"
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+ "id": "5674107c",
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+ "timestamp": "2026-10-28T21:36:18.258Z",
+ "error": false,
+ "parts": [
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+ "name": "bash",
+ "input": {
+ "command": "ls .kinex/tools .kinex/skills .kinex/memos .kinex/devices; find .kinex/devices -name profile.yaml",
+ "timeout": null
+ },
+ "call_id": "call_816b5ca02a114a64b4420799465afe07|fc_08ccae8539651651016ae26ad1758c81a2b2b68b8ff51795ee"
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+ "tool": "bash",
+ "timestamp": "2026-10-28T21:36:18.278Z",
+ "error": false,
+ "parts": [
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+ "type": "text",
+ "text": ".kinex/devices:\nhead_camera\nleft_arm\nleft_camera\nleft_gripper\npolicy\nright_arm\nright_camera\nright_gripper\nworld\n\n.kinex/memos:\n\n.kinex/skills:\n\n.kinex/tools:\n.kinex/devices/left_arm/profile.yaml\n.kinex/devices/right_camera/profile.yaml\n.kinex/devices/left_gripper/profile.yaml\n.kinex/devices/right_arm/profile.yaml\n.kinex/devices/left_camera/profile.yaml\n.kinex/devices/head_camera/profile.yaml\n.kinex/devices/right_gripper/profile.yaml\n.kinex/devices/policy/profile.yaml\n.kinex/devices/world/profile.yaml\n"
+ }
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+ },
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+ "tool": null,
+ "timestamp": "2026-10-28T21:36:22.892Z",
+ "error": false,
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+ "input": {
+ "path": ".kinex/workspace.yaml",
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+ "limit": null
+ },
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+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/policy/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_073226633db3436eaa004fd1b7f47bda|fc_08ccae8539651651016ae26ad6cd4481a294e04aa528646fdf"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/head_camera/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_5de315338fcb4ddc86f68b19eec4c4d4|fc_08ccae8539651651016ae26ad6cd4481a29faa31a2d212e054"
+ }
+ ]
+ },
+ {
+ "id": "fd0e8b70",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:36:22.899Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "identity:\n id: robotwin-aloha-agilex\n name: RoboTwin ALOHA AgileX\n kind: arm\n model: ALOHA AgileX (dual ARX5)\n source: user\ndevices:\n source: user\nsafety:\n source: user\n max_joint_velocity: null\n max_cartesian_velocity: null\n keep_out_zones: []\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\n"
+ }
+ ]
+ },
+ {
+ "id": "b7e881af",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:36:22.899Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: world\nruntime:\n domain_id: 83\n observation: time\n nodes: []\n ready_timeout_s: 30\noperations:\n time:\n description: Authoritative world clock\n transport: topic\n direction: output\n endpoint: /clock\n type: rosgraph_msgs/msg/Clock\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n wait:\n description: Advance or await duration_s of world time (finite and nonnegative).\n Zero is an observation barrier. Waits are sequential; one requested while another\n is pending is rejected. A terminal episode rejects further progression without\n exposing benchmark results.\n transport: service\n direction: input\n endpoint: /world/wait\n type: kinex_interfaces/srv/Wait\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 120\n stop:\n description: Cancel the pending wait.\n transport: service\n direction: input\n endpoint: /world/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: world\ndescription: Scene reference and authoritative world clock of the RoboTwin 2.0 table.\n Kinex supplies frame transforms independently. This device exposes no task instructions\n or evaluator results.\nsource: default\ncalibrated_at: null\nmethod: unknown\nbounds: null\nsurfaces: []\nframes:\n base:\n parent: null\n translation_m: null\n rotation_xyzw: null\n"
+ }
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+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:36:22.899Z",
+ "error": false,
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+ {
+ "type": "text",
+ "text": "name: left_arm\nruntime:\n domain_id: 83\n nodes:\n - entry: links.py\n factory: create\n ready_timeout_s: 30\noperations:\n joint_state:\n description: Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4,\n fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition\n stamp; do not infer motion completion from a sent command.\n transport: topic\n direction: output\n endpoint: /left_arm/joint_state\n type: sensor_msgs/msg/JointState\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n joint_target:\n description: Joint trajectory over all 6 arm joints in radians, timed from receipt\n by strictly increasing time_from_start and finishing within 120 seconds; velocities,\n accelerations and effort must be empty. A zero header stamp selects now; a nonzero\n stamp must not start in the past. Points are absolute native joint positions,\n linearly interpolated at the native control period. Replacement clears pending\n references; invalid trajectories are ignored, so verify measured joint_state.\n transport: topic\n direction: input\n endpoint: /left_arm/joint_target\n type: trajectory_msgs/msg/JointTrajectory\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n stop:\n description: Stop arm motion and hold the measured posture.\n transport: service\n direction: input\n endpoint: /left_arm/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: joint\ndescription: ARX5 six-joint left arm of the RoboTwin ALOHA AgileX. Geometry is the\n sibling arm.urdf with flange (fl_link6) as the tip link; measured links are on TF\n as left_arm/\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\n \"left_gripper.target\": {\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\n \"world.wait\": {\"description\":\"Advance or await duration_s of world time (finite and nonnegative). Zero is an observation barrier. Waits are sequential; one requested while another is pending is rejected. A terminal episode rejects further progression without exposing benchmark results.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/world/wait\",\"type\":\"kinex_interfaces/srv/Wait\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"duration_s\":\"double\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"time_s\":\"double\",\"waited_s\":\"double\"},\"definitions\":{}},\n \"head_camera.image\": {\"description\":\"RGB image measurements with encoding, dimensions, row stride and acquisition timestamp in the Image header. The frame_id identifies the calibrated optical frame; use its stamp for tf2 lookup. A new subscriber receives the current frame at once, also while the world is paused, then one per camera sample; reading never advances world time.\",\"transport\":\"topic\",\"direction\":\"output\",\"endpoint\":\"/head_camera/image\",\"type\":\"sensor_msgs/msg/Image\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"height\":\"uint32\",\"width\":\"uint32\",\"encoding\":\"string\",\"is_bigendian\":\"uint8\",\"step\":\"uint32\",\"data\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "d795cfed",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:37:26.674Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Planning reusable script**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_08ccae8539651651016ae26b146e2881a28c56cec1184d1eaa\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning reusable script**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4msWfgHyhZuijYJuvnK7w_zDFl-e-TZBFJZUFnguIG721OjI_0I5V21NEEQt2BR6bSva6CjdrTAqQ5E0GoR-BRlrP27j167uthHjrYt-ix3_4XfqazNA2VdVixz6reVrxRrPH7k0W4eCHgH6veA-7AxvCROZ2bYUL1qSr0fuaaThR26H9VxR3aoOdr9FejnSPJ20NOKVrgKE-V4CuD8XIlw9f04Tx-4OkSu_UaITpVEwhdl3SsgV1hN6Ze1yKW3rZTq6Diu1Wr-tjkwxYKnUeSHAY4o2Y0akMmP2SAKlluMHUAvaaQTaogE5aePoKQIgVgG8InS5w6OdehSgIEcyCmWBPaVHRS61kH4jvBKzMnrvUAzK8svHfJZkUwkxGCynzk3mPOEILFQ-d4MbkFucyr2-inktogQlX5w1LvLNLKzTm_4c4R-KpCU8FGouQChqQ37aQnKs4gIXj9pvPV-p-JSk8JGtAP6PEeGwgIR8Z_BgqSXBFRaFiyy8JZv9FFQi7lkRJhzYBXw0CmfU2g_j7MNJjetbja_JW0I7JXAfckBzyEnM84byLpQYNIy7ija-pHLg-ip-BQf3ghQPuO9M1pEn6SBYg_te2mMjgUnz90LTFhNhpSvwb6ewmkdvUXK5vsVWM9rJEuYqhY2xxc4y5rsVGUtZ8bQvnhQxoKd3oioQwjdeAJf9K0d7CNbpGuwm_RjLeaYfJLY2JXApnd88EFAptpw1zryLSEfXEltwiKu2U9h7UTSdA_hxQYBB3OkFFdtkiSP4zOHnMwHfp_llYUY9uLwmQ-NDT4GN6iykC2uU-kak6bpwszNi1ie41q4EorNlX3rNVv-ZfQl4G1rJqfFpiHKvmOt5cebfm_AyYMu_3qiKi36MtRvRDJQNvlrwAq2wxniiGMiIGRjxT84Sd__CXy-k4PnXbS2GXFGAtXkLB_JekO0bqJHhMTt7cupC5A9wEW4F1mvJAN_c6fatiT27RKXYrr4_rc8fpVvnbaMS8AMQ4dnRoGJO5BWIEl42X1Z8rwU0jGq2czlris3j6QpdwBnF_a6VcN48pNxNB30petTI7ByzsTJC27c2LgaLcs-4qRyrRh87lvPIamPAWcfjSUiJ8t5KBpyB2CM-UKaLLqJIed1w8G4e1FU3DQpHzKUSG0xz0t6PSJ-6v-w5EsFL8nIjjPXIOKqnWjZ3CmaLPzIMYlD9G9-hAQ6GGWLqPyk0rt2XHR39FSl7nD8NPcDKtRVFvu7XDb1eEDrXd3OA4Hao8eVL-oOr9OhpBd7vpLkqKHpQqNjzxoqunlTpVIkkwk98iSI4YZcfwByFbDicneb2JJL6h09-8lS5-2EuEE4d49VYPMu3uwKFwikX4c7iVX0HiOUcvpVzFtN41VGz0VBUiZ971txogGd0altyCa6EuRgCesZ5irvQVJj10P_-BeUXIAq2-LUn4hsc_Kh1MoInRi5i74SEIstlgnQO4gO_DK2YLi-hg01m0uSxdEKRyvRVVRjod4j9WofS7gYt_PKAHF9_xpPg_cWkCOumAoZIvx7XOHDXx6CtRPp5HedOOdfh1a6W4q63Qp0WvnIt9ytEFXylEoWgj1KN2HTNI0G7fQq7ZsKSXai0wEloZcFHc_BRV6G9xnHOhKq1IyXj1lbBbzWZpGziBDv4DKZ0266vhyjdOR6hwD8CPB7k01OoNJPwzQKHJHDllyOfH7cii4YcCQ5IjMXDCCcV2Z_WFGD2MKm2KbU8r0kjeUzenBRLIBp5ZqZzTGUE_vgs_ykwZIlX2KdPXBDgsURwRY_Jz_c2\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/policy.py",
+ "offset": 1,
+ "limit": 240
+ },
+ "call_id": "call_aafa6eda56b0431db5445c532842c4aa|fc_08ccae8539651651016ae26b15215881a2bad7cde781ccdd84"
+ }
+ ]
+ },
+ {
+ "id": "63212478",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:37:26.679Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Policy execution: one inference turned into validated device commands.\"\"\"\n\nimport math\n\nfrom kinex import profile\nfrom kinex.lib.geometry import compose_rt, number, vector, xyzq_to_rt\nfrom kinex.lib.joints import JointModel, command as joint_command, measured_positions\n\nEND_EFFECTORS = {\"gripper\", \"suction\"}\n\n\nasync def run_policy(io, model, observation, command, task=None, world=\"world\", action_hz=10,\n max_actions=None, inference_args=None):\n \"\"\"Infer once and submit the valid action prefix to every commanded device.\n\n model serves a Json \"infer\" operation taking obs (and task) and returning\n actions or action. command lists {\"device\", \"space\", \"frame\", \"target_frame\"}\n entries in flat-vector split order; named action maps use device names.\n space \"device\" takes absolute joint values in URDF order, or end-effector\n values in [-1, 1] that release at -1 and grip at +1; \"pose\" (xyz + xyzw) and\n \"pose_delta\" (xyz + axis-angle) solve URDF IK for joint devices with a\n tip_link, frozen at the observation stamp. max_actions caps the horizon and\n action_hz paces actions on the world clock. Joint trajectories submit\n asynchronously; end-effector targets are paced by world waits before\n returning. Returns actions_submitted, duration_s and ik_failure\n (device, action_index, error) or None.\n\n Example: await helpers.run_policy(io, \"policy\", obs, [{\"device\": \"arm\"}, {\"device\": \"gripper\"}])\n \"\"\"\n import asyncio\n from kinex.communication import duration\n from kinex.helpers.frames import IDENTITY, transform_pose\n from kinex.lib.geometry import invert_rt, rt_to_pose\n plans = [_commanded(entry) for entry in command]\n if len({entry[\"name\"] for entry in plans}) != len(plans):\n raise ValueError(\"command must name each device once\")\n wait = f\"{world}.wait\"\n if any(entry[\"model\"] is None for entry in plans) and wait not in io.catalog:\n raise ValueError(\"end-effector policy sequences require a loaded world wait operation\")\n options = inference_args or {}\n if set(options) & {\"obs\", \"task\"}:\n raise ValueError(\"inference_args cannot override obs or task\")\n data = await io.request(f\"{model}.infer\", **options, obs=observation, **({\"task\": task} if task else {}))\n actions = data.get(\"actions\", [data[\"action\"]] if \"action\" in data else None)\n if not actions:\n raise ValueError(\"infer must return nonempty actions\")\n actions = actions[:max_actions or len(actions)]\n split = [_share(action, plans) for action in actions]\n count, failure, sequences = len(split), None, {}\n for entry in plans:\n name, spec = entry[\"name\"], entry[\"spec\"]\n samples = [item[name] for item in split[:count]]\n if spec.get(\"space\", \"device\") != \"device\":\n stream = io.subscribe(f\"{name}.joint_state\", depth=1)\n try:\n state = await stream.next(timeout_s=10)\n finally:\n stream.close()\n joints = entry[\"model\"]\n seed = measured_positions(state, joints.joints)\n base = f\"{name}/base\"\n ik_frame = f\"{name}/{joints.tip}\"\n target_frame = spec.get(\"target_frame\", ik_frame)\n reference = spec.get(\"frame\", base)\n # target_frame is an attached tool frame. Freeze its offset at the\n # observation stamp while resolving the policy's Cartesian chunk;\n # URDF FK of the measured joints places the tip.\n offset = await transform_pose(io, IDENTITY, ik_frame, target_frame, state.header.stamp)\n tool = rt_to_pose(compose_rt(xyzq_to_rt(joints.fk(seed)), invert_rt(xyzq_to_rt(offset))))\n current = await transform_pose(io, tool[\"translation\"] + tool[\"rotation\"], base, reference, state.header.stamp)\n converted = []\n for sample in samples:\n if spec[\"space\"] == \"pose_delta\":\n value = rt_to_pose(_delta_pose(xyzq_to_rt(current), sample))\n current = value[\"translation\"] + value[\"rotation\"]\n else:\n current = sample\n ik = rt_to_pose(compose_rt(xyzq_to_rt(current), xyzq_to_rt(offset)))\n goal = await transform_pose(io, ik[\"translation\"] + ik[\"rotation\"], reference, base, state.header.stamp)\n try:\n seed = joints.ik(goal, seed)\n except ValueError as error:\n failure = {\"device\": name, \"action_index\": len(converted), \"error\": str(error)}\n break\n converted.append(seed)\n samples = converted\n count = min(count, len(samples))\n sequences[name] = samples\n if count == 0:\n return {\"actions_submitted\": 0, \"duration_s\": 0, \"ik_failure\": failure}\n seconds = count / number(action_hz, \"action_hz\")\n prepared, scalars = [], []\n for entry in plans:\n name, prof = entry[\"name\"], entry[\"profile\"]\n samples = sequences[name][:count]\n if entry[\"model\"]:\n joint_command(prof, samples, entry[\"model\"].joints)\n fields = {\"joint_names\": entry[\"model\"].names,\n \"points\": [{\"positions\": value, \"time_from_start\": duration((index + 1) * seconds / count)}\n for index, value in enumerate(samples)]}\n operation = f\"{name}.joint_target\"\n else:\n target = _grip if prof[\"type\"] == \"gripper\" else _vacuum\n targets = [target(prof, value[0]) for value in samples]\n fields, operation = {\"data\": targets[0]}, f\"{name}.target\"\n scalars.append((operation, targets))\n prepared.append((operation, fields))\n\n await asyncio.gather(*(io.publish(operation, fields) for operation, fields in prepared))\n # End-effector targets persist. Timing belongs to this workflow and the world,\n # never a device-side duration or a background worker.\n if scalars:\n for index in range(count):\n if index:\n await asyncio.gather(*(io.publish(operation, {\"data\": values[index]})\n for operation, values in scalars))\n await io.request(wait, duration_s=seconds / count)\n return {\"actions_submitted\": count, \"duration_s\": seconds, \"ik_failure\": failure}\n\n\ndef _commanded(entry):\n \"\"\"One commanded device: its profile, joint model and share of an action vector.\"\"\"\n name = entry[\"device\"]\n prof = profile(name)\n kind = prof.get(\"type\")\n if kind not in END_EFFECTORS | {\"joint\"}:\n raise ValueError(f\"{name} is {kind}; run_policy commands joint, gripper or suction devices\")\n model = None if kind in END_EFFECTORS else JointModel(prof)\n # A gripper or suction tool takes one command value whatever it reports back.\n width = _cartesian_width(entry, prof)\n return {\"name\": name, \"profile\": prof, \"model\": model, \"spec\": entry,\n \"width\": width or (1 if kind in END_EFFECTORS else len(model.joints))}\n\n\ndef _share(action, plan):\n \"\"\"One action, split across the commanded devices in order.\"\"\"\n if isinstance(action, dict):\n missing = [e[\"name\"] for e in plan if e[\"name\"] not in action]\n if missing:\n raise ValueError(f\"action names no value for {', '.join(missing)}\")\n return {e[\"name\"]: vector(action[e[\"name\"]], e[\"width\"], f\"action for {e['name']}\") for e in plan}\n vector(action, sum(e[\"width\"] for e in plan), \"policy action\")\n shares, cursor = {}, 0\n for entry in plan:\n shares[entry[\"name\"]] = list(action[cursor:cursor + entry[\"width\"]])\n cursor += entry[\"width\"]\n return shares\n\n\ndef _cartesian_width(entry, prof):\n space = entry.get(\"space\", \"device\")\n if space not in {\"device\", \"pose\", \"pose_delta\"}:\n raise ValueError(f\"unknown policy space: {space}\")\n if space == \"device\":\n if \"frame\" in entry or \"target_frame\" in entry:\n raise ValueError(\"frame and target_frame require Cartesian policy actions\")\n return None\n if prof[\"type\"] != \"joint\" or not prof[\"model\"][\"tip_link\"]:\n raise ValueError(\"Cartesian policy actions require a joint device with a model tip_link\")\n return 7 if space == \"pose\" else 6\n\n\ndef _delta_pose(current, action):\n \"\"\"Translation and rotation increments use fixed reference-frame axes.\"\"\"\n action = vector(action, 6, \"pose_delta\")\n angle = math.hypot(*action[3:])\n scale = math.sin(angle / 2) / angle if angle else 0.5\n rotation = xyzq_to_rt([0, 0, 0, *[v * scale for v in action[3:]], math.cos(angle / 2)])\n return compose_rt(rotation, (current[0], [0, 0, 0]))[0], [a + b for a, b in zip(current[1], action[:3])]\n\n\ndef _action(value):\n value = number(value, \"action\")\n if not -1 <= value <= 1:\n raise ValueError(\"end-effector actions must be in [-1, 1]: -1 releases, +1 grips\")\n return value\n\n\ndef _grip(profile, value):\n \"\"\"Interpolate the grip joint from open to closed.\"\"\"\n grip = profile[\"grip\"]\n if not isinstance(grip, dict):\n raise ValueError(\"the gripper has no declared grip joint\")\n return grip[\"open\"] + (_action(value) + 1) / 2 * (grip[\"closed\"] - grip[\"open\"])\n\n\ndef _vacuum(profile, value):\n \"\"\"A vacuum level from release (0) to full vacuum (1); binary devices switch on above 0.\"\"\"\n value = _action(value)\n if profile[\"vacuum\"] == \"binary\":\n return 1.0 if value > 0 else 0.0\n if profile[\"vacuum\"] != \"proportional\":\n raise ValueError(\"the suction device declares no vacuum control\")\n return (value + 1) / 2\n"
+ }
+ ]
+ },
+ {
+ "id": "b0912ee4",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:37:29.087Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "device",
+ "input": {
+ "deviceID": "head_camera",
+ "action": "image"
+ },
+ "call_id": "call_6d05b38858304b3bb75a6d40e1fb933a|fc_08ccae8539651651016ae26b18c8ac81a2990f177ed78f48db"
+ }
+ ]
+ },
+ {
+ "id": "0d916554",
+ "role": "toolResult",
+ "tool": "device",
+ "timestamp": "2026-10-28T21:37:29.293Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"deviceID\": \"head_camera\",\n \"timestamp\": 0,\n \"frame_id\": \"head_camera/base\",\n \"width\": 320,\n \"height\": 240,\n \"file\": \"/tmp/kinex-observation-orrg2pv4.png\"\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/0d916554-1.png"
+ }
+ ]
+ },
+ {
+ "id": "346e94ec",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:37:36.926Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/handover_policy.py",
+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n"
+ },
+ "call_id": "call_97f69f82def545d69f64000042e044a8|fc_08ccae8539651651016ae26b1aea6081a2b7e8af07602854ff"
+ }
+ ]
+ },
+ {
+ "id": "d97ec9b0",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:37:36.929Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/handover_policy.py"
+ }
+ ]
+ },
+ {
+ "id": "99102907",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:37:39.608Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "grasp approach policy",
+ "file": ".kinex/tools/handover_policy.py",
+ "timeout_s": 180
+ },
+ "call_id": "call_dbfd26603ee74ce5a556516cd3d58bf0|fc_08ccae8539651651016ae26b22d8b881a2a920f8a417752f5d"
+ }
+ ]
+ },
+ {
+ "id": "b5bff240",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:37:45.442Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223460.918079201] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.000841967121232301,0.5760459899902344,0.5073635578155518,0.11193818598985672,0.38478362560272217,0.011398900300264359],\"stamp\":{\"sec\":0,\"nanosec\":640000000}},\"left_gripper\":{\"position\":[1.0020332282239741],\"stamp\":{\"sec\":0,\"nanosec\":640000000}},\"right_arm\":{\"position\":[-0.003331375541165471,0.00015323919069487602,0.004788832738995552,-0.0013015313306823373,-0.0026872919406741858,-0.002288535935804248],\"stamp\":{\"sec\":0,\"nanosec\":640000000}},\"right_gripper\":{\"position\":[0.9922204071825201],\"stamp\":{\"sec\":0,\"nanosec\":640000000}}},\n \"file\": \"/tmp/kinex-observation-vu2mzt27.png\"\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/b5bff240-1.png"
+ }
+ ]
+ },
+ {
+ "id": "7cb874b5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:37:47.746Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "approach red block",
+ "file": ".kinex/tools/handover_policy.py",
+ "timeout_s": 180
+ },
+ "call_id": "call_66e5d7cd0a344460acc9e062f1d21b7c|fc_08ccae8539651651016ae26b2b4f5c81a2821f711cfcbf299e"
+ }
+ ]
+ },
+ {
+ "id": "94f007e4",
+ "role": "toolResult",
+ "tool": "exec",
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+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_gripper/gripper.urdf",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_64a1b5c11fcd454ab5594f92b8c9f74b|fc_08ccae8539651651016ae26b56318081a2924df69d48a139b1"
+ }
+ ]
+ },
+ {
+ "id": "aaec1966",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:30.307Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Joint device kinematics from the device's resolved URDF.\"\"\"\n\nfrom kinex import profile\nfrom kinex.lib.joints import JointModel\n\n\ndef joint_model(device):\n \"\"\"Load a joint device's model without device I/O.\n\n joints lists the commanded joints in URDF document order with limits and\n rate limits; names holds their names. fk(positions, link=None) returns the\n link pose [x, y, z, qx, qy, qz, qw] in /base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "22f2f198",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:30.308Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "0d6f892f",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:37.550Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Reconstructing red-block depth**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_08ccae8539651651016ae26b58266881a296f78725085a0fa7\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Reconstructing red-block depth**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mtdt41UEweewpxD4k79oao-BjCwazHnirLI8zI3jzSHyf4Tdw9bF4aVNdEueR99yq1lAKEyamU4_a8DKiUIFUFJRwYELiFGaDHAvLJsD_skxMPMBaB1iCEJz7B2OJu643LS2TLvkR8Df2RAOltTg6fOuHvz30a1yZ381w8plLvwJ8Uo3VxhbfLeLs41fR1BvxIL4dFlHg26WQRpOcXI6wdoOQy1mi_XeUF64Xxt0MPFtez4B71clQ9spc2j8w1oZ3DBwpWw2vm8N0jdQmurCqfkWDsCptInH40MxQc7zK8g3N5PNp88avDIGTr5h306GEcO2eFMFaxSwix6AhPOAHe40gsMzNs9zAd9TVDATtAdD-fk5WQ2_amFC_qwnR4e4_-CN55YTLm9IX7uqACkirlq11vouNbTNW6KVZsBP-fSxeDRQsPp9Mlv5x1w15idMyQw3uiQhEkfD2J5mzY0IpjHUKKNVI0j_GTFyFY3o9Fy7PBDRN38b92vSLNmnMOR7B4_nfTN9DDhzDyE9Q8g6hblV-DgQDYf_pZDGWYHsGgk36JONz7cww1CpOOgCSOENmy3n3a26wXffA40ooJwiifuLCABaFHGsAh632LbLHCpaLvoTq_jtu2fVzsblbVnUW1uht8bepHWLiQf1RLTpfnzqNaxsrzFkW6wzmI6UZrzWzrS-LyHW4qs1LGFi2Dd4375AeLldALU9WSE_9UCwwiw9JmBjfV1NraKmlNUILTEluX4m3_YgKCahgs5yilH7u6Ny5TuaA_xjoSayTuYFTibJbn6Y4cKbv3uoeW2FmqTHb4Tlkk0btYQiKsuM2oKeYQGcSyxAsp4rVgqjPSo5lS8dBDJgw9oZ69CUBdYgTV54Nl6UwAf6q4U1zyn9CMf0yr2edYZ_W_eitjDJymmopDjx918pTvEmpxzuUC6JL7BOWaN6gsM4vRyUhnhaB4bPDnGshm8vgErkNzupRgSRYruIdggPxwb_2zEyaetaQxps9jC_6i3Kj3JEFVPCdUOHVHcP2ATAcPSRr1lkYBqnax0b2TggPvulhRrFuZyF4JZlUG9irqxArpb_DExlQbWQprd-8Lgfu7St5THe1ed0HgNDBtsrE5SgceCXOLjuKwByELpjpKouzDuvE4Ok3kOcSZGDz5uodQ-Bq3Iyfs1it-82bMUZwqIdGMQKhPlVDQasOBh5n5CS9osPckjcBITzsgH189NeTCiaq1C4wnhxSzrx9Q-H9ZN3RAEX4Y03-uYOMZBL-ABaYGNXw_6DFMt2k9BPvChbmNf6ammDaQkxlHTQMaEsQCxvYxwVQ1la8XU5mff-hRygM5rJ9w7TmUP8PN8QHRHCaj15wCVB__T3WghklTHAQDCwH4lXcKepfgSoY3MTmvLXwctql2fUoQJM2mEakqOMKWpHdggAcwjQe5JQMyTOYnN6m7x4PgTbjKLYfL5nHCwas0e0mLy7ncnlYptbak7WZ0FUZV9wQBjdiJI5dJpSA4CLzOA_Rm6fpYKeDbbPREWCU3yjqzdiQ_LcMS-987zG_7Ygbx0v6GlpVK6UvZC01DkugaXLl-vwB0GJsqR9JNXLL__zCK6us0_VT8u6GAxDEeFs_0F9m2eeJVKcd9sDqBNlE9QzBUqB7TxyR8oLMNxWZuNeFM3MhzO392SGehpGy_AssLtcMSPbMV3O0cHi6jeBp6wHrOYi2ylVhuxj4lBWezR8-vxlq6VTaw0EOQQrWcA1J6PuNPvK36vaSJaC30cmyMj8pqBI8lf85ia4IPNWrbHjD8xu7WLElQt9vmAyxSQ2iVJ6mjEd3ed_M0fQNLdf42yt7QdaI3vFnOWJDCcv_eDq-0y9b5tsEV2Dgxn_J9TPxq4neR7ve-_ORXn7pbf_fCGzOHKSK1PC50NRixn7El1GVHjkG9QJdWncFOJ-Ix7Rcsddti-HnUTVcH-qDec8eSiMjJ5oowAem--VxGCZ9AELcCJ-VR3A58bjTbBBwmcmBeClTdNTuPBm8vH5MIaKDr6yGsQN7QoM8VzrCUscJR-oJstUyS5alZgOD3OAyOVF2eSd7aBGoeqGDllr-9JY7y-uYC9d2WuV95QqFlsKMMvUE8JUHdTgI3MnhFvtHc5oCGF8Aq8UuFh28fs-h8wPm0jpb2u4-mBLQmRmAwJcWoxT9sqcU21q9B_bwuzk3au6Ldz7ERElpiqCMG485i416qwumwt3FQVR47gtBg7BKrdzWHITsBW2AzipoBBdmV464Ap_yI5Yg9qPqddhhZ1lPalT1qjkLG4HtDAd8YSVJJ7K0gQ7dDP3bmLlAsDNXGbYL7ULNqf2FPV3o_3voFSgv_j7BaaMRZCASeOljUJLZaXL8WOFKAsr8i-hEFQIeK6CeS2eb_4eK26O6WuZ-qumSUobmkxUWQ3-tMwNzT7CL1Udmn07y7oZzDh\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure scene geometry",
+ "python": "import asyncio, numpy as np\nfrom kinex import communication, helpers, finish\nasync def main():\n async with communication() as io:\n f=await helpers.camera_frame(io,'head_camera')\n finish({'frame_type':str(type(f)), 'keys':list(f) if isinstance(f,dict) else None})\nasyncio.run(main())"
+ },
+ "call_id": "call_ad0c092304d045caae710eef68ffc64e|fc_08ccae8539651651016ae26b5d730c81a2a3f06ca5ed26ef49"
+ }
+ ]
+ },
+ {
+ "id": "9b35b133",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:38:39.626Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223518.853304393] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"frame_type\": \"\",\n \"keys\": null\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "426b5575",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:41.954Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
+ "offset": 1,
+ "limit": 170
+ },
+ "call_id": "call_01b5f2780dbc4b868019ad4c2dfe1f40|fc_08ccae8539651651016ae26b615b4081a29291e6a02e944ba4"
+ }
+ ]
+ },
+ {
+ "id": "e35b8613",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:38:41.959Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "b5e57b81",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:38:49.163Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "locate block and pad",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation\nfrom kinex import communication, helpers,finish,profile\nasync def main():\n async with communication() as io:\n im,dep=await helpers.camera_frame(io,'head_camera'); a=helpers.image_array(im); d=helpers.image_array(dep)*.001\n p=profile('head_camera'); fr=p['frames']['base']; r=Rotation.from_quat(fr['rotation_xyzw']); out={}\n for name,mask in [('red',(a[:,:,0]>150)&(a[:,:,1]<80)&(a[:,:,2]<80)),('blue',(a[:,:,2]>150)&(a[:,:,0]<80)&(a[:,:,1]<80))]:\n v,u=np.where(mask & (d>0)); z=d[v,u]; xyz=np.array([(u-159.5)*z/358.6421814,(v-119.5)*z/358.6421814,z]).T; w=r.apply(xyz)+fr['translation_m']\n out[name]={'bounds': [w.min(0),w.max(0)],'median':np.median(w,0),'pixels':[u.min(),v.min(),u.max(),v.max()]}\n for arm in ['left','right']:\n out[arm]=await helpers.relative_pose(io,{'frame':arm+'_gripper:tcp'},{'frame':'world:base'})\n finish(out)\nasyncio.run(main())"
+ },
+ "call_id": "call_e3e9014848e04057871cd9d4d50054f4|fc_08ccae8539651651016ae26b63b7b881a289f3ed6fbd8a41e4"
+ }
+ ]
+ },
+ {
+ "id": "337226d1",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:38:51.990Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223531.315992288] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"red\": {\"bounds\":[[-0.1951807511227014,0.1619458755140133,0.7403946746887228],[-0.13826190259151744,0.17530309445014303,0.9257439697592391]],\"median\":[-0.16744837463208706,0.16852240987786182,0.8441180625125884],\"pixels\":[77,0,115,67]},\n \"blue\": {\"bounds\":[[0.0630836271454373,0.10104295310740785,0.7421885613696891],[0.16190775280083636,0.19940375685842826,0.746340314718351]],\"median\":[0.11238624941640478,0.14487610727741018,0.7460899470946761],\"pixels\":[199,55,244,86]},\n \"left\": {\"pose\":[-0.2616530267915924,-0.1484765921145812,1.070289798713373,-0.021897730331534127,-0.02189688895282258,0.6015608300353317,0.7982265238813591],\"timestamp\":3.2},\n \"right\": {\"pose\":[0.15039597241518135,-0.04177619542231542,0.9706620944772414,-0.5838925600381027,0.20359696955881887,0.7134881688183462,0.32947289004538605],\"timestamp\":3.2}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "faf0d4fd",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:20.244Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Positioning for tall block**\n\n**Aligning tool for tall block**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_08ccae8539651651016ae26b6f151c81a2adb5880e51ef748f\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Positioning for tall block**\"},{\"type\":\"summary_text\",\"text\":\"**Aligning tool for tall block**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mt-yQjo3GeBz44w64DzXuic1IB_yRhMFB4uNNO2Vm-jcJO5ZCM3zb2psNSvVTH5n2godO-PwJCO7o3lThOFj2NDIc0y0rpZxEj5lJ-AeOkVHzynWTpGNTNjp2yK41qMwNFtrRjVEQQc1xqV-XFhg80WoaP-yFfyO8fFV-160HViYma-G9ywJ6_bolQ-iX_xkJAoWHDj6QiXkVl_xxPUpCgW-MJ8dkgpFMt4yKlAjd7P-DLBNriLJdnib4ScbG-unJfRpXL3m4Q7z2_1EB7K7yXQoNrLlKp_6A791NYoLoKeenvYkQzMCNUPy6Zhqn8r-eTFSjbn8jnvUQgBHFgFBI1dGXcLEF38pULTtpV9RULHcF1P2t8ljK_5XyoPU5G-K_UgzJrE6L_IpWFtm1d_qp1xi0rEomt0BbyLX23m3qX4tvm3_1hu5ab4twX81Pn0SSrK40PJftkbKA5konNdRbR2_P-8ZH8Li8iEF9_wDA_vZYkS_PpfBZY0fF5R_WGEJQZKnOBJfdvIiFx1CiFwWE5YWf2ExG7cS8C83QrMpaQsJFa4pX3HbxHXG8eaMG-nvM7vpDc29k1_XYKvew40a64voWqcSql8Zd3Z_9eWrgDQw7z_s_3SHnhcwGFVXwXzhgSd6829gv3zT8DF9_KyiDSzTIsuD1WOjAjo_7ur64B0CqbX9zRPerovAazm0Z11YAovKxCtaEi3yqH2sNE9NP_EY-Uj3tuFaWGsYqSQ9ogidC8-GeaNxNAQaLwx1P_rrM3VznGNTiQuu7998TQtsblQ9RyCvsoCxs2emAZosLKANqjIZCKOMyUYFyzHVWAdCQW2RS1Lj8Q5LMkECC9Ck26TEaPzNBxwkxbwnbAMtSvriZmNQ7u7VQXhQmHQBZj6bd9-XY_AlgraeVeINSVuh-DYDVwgXE4c4hcSHUZ-_DbUGj2XwW5cHLS2I5YYSQJ-7MJUKELI3oaF7ycF-tM9P6yctKAGGBtRN12INTGYv2SL2BTHN5fE79GWCTsQUkqkS2XFa8IKgzFgQPi_pl2I8rZDdEnnhCo9yT7SqQ8VKGUAbC0MdqHjyhysZfQdFso0b1d65qRVP8pjb88efKb_Jiv7NyLaUBEO2cwyZpIU74TJJWKIsdgozexMz5epCnYPvteEsfLyuJEuelAbeYJ6eVg-AZSYhevwAxQR-igkgKJqx9musnkeecsELz1ltaKXquRobURUPNlM_2ggn0DyMaHoHYzg8GchyIuYtHxndqy6sJPK1odPRKzqljOp_FidIGvd3YqmaHn44kmIdtA1kDArGezqSkbtFRUix3oswdYDBAQUcUJkaqyqR9fi3cAG5ZpArds7gHvocfRxmx8jn_Fh3UjvQXhHUPVszA77iyQYNsTp5nVdRF-w_ql4u0XOZoZTt7MwmvdhRvzcqUcsUs7oQkuLyVHfoxmHSOLyMXkGpyxAFCKbZuuQwKQEuKBN3--2jfD7ofdPdCa5wmhWI-ScCSJbwV1LIImomxhVbL02QaUSzseQJbiGimLRNwkt0C8nNzPZTV4f6wnErh7bmQQNoTKC2DpM9Kwv0jRUV6irhWrqlzwjzGh8_Ng6BOY5THMI_EiZXWi5-qPNOSIaUHxPR66BCKtRAVQCEGQ8u72IimNhCGjbK3-HbWeiSJxJ6VF9QLW9416GgN2CfEWfJi9a564DHueEL6NeTYv4CDY7phIDlM9qRlIbBNFeZOQmmas65Qz3M-CPiLMntmXKfCm6uG9aG2zUIkRGuzS-oXsbIPtUJWs9RzvA3SK-9Ncb-2UE7sANhe5p8vdu5oLjuE73qJsATeWCgFUGvlAOcdQJOyp5p62dv91bNW5gFZ0zLG5tGHBxJWWT6lJzEtz1MdIzw6Gv95lOScDrfc1Wkb0fJ3BJN8EcPqRsWnv-XcjE9phXEsJagt4QDVvzHq4BidK8oUeyJrtp8MCz-X-Z6pXWVBfPxcfj-Z4y_b7sIH5qFMCrKfKzSeTH19heQl_Yw95KZB0u0fyfpXoSS-wHm4bNnlrX5IVDl4y2mygqL_kULiqDuJMb4dhjlatoh_WTuWFN3ugHpCooY6eNhyL7wKDEtWrtKGI_uzj5prRUv_7aA64PHv629A3aF7xdLZ48OALXsFtTVELplrCdqAptEL5PvViIwKDmizkyHJ3orPZGXOOcgw0GQH9oMPvcZlPjkVzZQ9J_vNzoJu9CkCEWSiUSXRrDaMOsAdgWAWWGyzpnil11poStTTMkikocm8ApeqH7QSvTTAXPKq80CwHSiwOq9CNU0dtLHOupc5iU6zUg-gTzG53n6aaSGukg427SVLPNTt3vsKYbsn-GqccWn6o2PQt4xAhKg2s6LhS7YiXu_Ivz09btFsUtqwKXsZGokuZmn3iSNPMAbb8KZSpwPSk87R3WK0HlmVRM5pvuY_YWeSBQhf9f7AK7Sp0nqHbGPe4CU0HrxAN3pV3WrKvDLpRsGSpC46H_2xwbkSDd7WrP5yTJe0NfJK3b--sKp5r6rf5493QXk781X5DF9rQFbjTzm87hioPXKxu8sMepteKKIkJrG7Glhmwk9RFDbkFAI5k_lXtud6aLglB_tm37-3bXuL8cSyl7VpVjTk_17EHwtkzXHB5Pmim6lMtLrd1TdLEP2nOke66dpz-iNd9uxxRvUdIoMPX0x8JEYG_r2BNKsxJ_s-4L-IqR1_QfMFovhoE_V_G7HvYcaNAegqGoitbHrO3YI6VMiHM6a7_wnxn2bAZjpa3D94nMn3fhLE--FXXRD3y71PvInpydVTWRuUx4GXj0gosMt2TrO_B1yhOfGtqph1hNI0O_hOrwan3_mmtaBoLwMSuIEr7XkqNpAVZ7DQ07-XhPXYz8RlUNc3RmFEM4vS8yF_mLqJR2WMm9i35z4BjHDim87TI2d0P5ilDjeX8Hd74s7z1Oa2Sab-zdFmCJFhb9L9uLuNVHAVUbcZJ9ifZ1zuyjgwxBTmKEyGwNH8iDHPMbgAlb3KEtvDjRWJNfcjA5MRXtoOXos4Z0O63lLuroRa0sGFW9JmgnVwS_icqqAQN50XjJq7b5a9wcIFF-uvNJBLGpZgYdLd5Pt9ar_zVEukeXx6575R0i09UuvrnCTqnQ3Ld7VE6Q-H2OfEjyeA0MH6iHMTX5Wwnxez5bE2zMBZSSwoSEb7ii7XbWHP1kG7-8dWtxi1Qpg6PfjSx7nqcUJTil7trscfwPuJhSelILWXOSDumXc-_biuiBcXwYNP47X5mFxQqNPsZeDvamdkC2f1zl2KzkFdZeUiuMZEAEwyIoMvqyKRtdS0VIg6op9nZw7mFopxkBY7mgMQ0EPGb-pZOVuu7R-skm4lagyrZmF0cEiDiWmGessIs9Bkf4IvHDBNvnaeCvErPBMj7V-jfuuV20ZZ_H4wigFRbKXNdSxQvyCdenJ3hV3EPrS0wQT6erdBublNAX3yLsdhLzXgIdlBGPtHvrR1KRWDM8eujT9LCrVZ98mHXbgwC3YunMyZ78gMi3iPn23J1dKq0lbQBElrFln-5vPpwt2XHspeQOMGbQxKPIKWgaPX2AcsYoUjHIBuGK8qBXcc1Spl_6B1Mw6sk_AKFOQtDWp6a9f0rIsVFE2MG2f7dpSJ_NA3boGGHci3TxfTxLIDrs71-5UOZYo6m2KP-KAS5jfxDG1H5Jqj3cSbtm-s2oS7uf-MLQ1UjCsPHq2QCn6y4OP-Hp_Pf6mJDcl8naFmWq4dBUn3M7syeaf2KbYNkoDtWAvL0sXJ5WpY4Qnhyb5jCmGPxD6f8oCw7s9Er0uBAgIhz2Tdjnd01tQ0fDpauaLsdrfw8_N4H8ljug6mTJqguDl35NRKRVIWbsFyx-HRpFiTzSPNM3O2w7rpF3V3mD_x_2sv2OTzC81ADXiQV0xnC0FRRVO3XdViwGYO_Hnd5AORh68RxRQm8SAytwfbhzWjvChNInQbjD5FiaN2bkCoYwpLFU8iGTmE5C7yZbrt_EXPTQEH455IBk9dEA5Q1HUlCKgy94W8U_bhttez82FWAEiu3cjik2cz5Fim1mXIGQZumV6-Aos8qef_ahERuBm7Kr_Gy9RTBPe-q4KByOW9b5lYe6H3u49sMUklvHYj0cOSW_SNSNfdBFdlCsvPcXquetDrznZxWaPE50dz_qdq7wdSDEM6qemsa49orUt2XROIevhIBDPaJOJ-1L-pamu9_yBeJOp-WyGnbtMl1tUJVooV0mbvqRN8npYeyulQ-QWlk8RQQTYQo3aJvyBiyunEL4OL6EzMadpERk0KflDc3g0pnauO7HAahw5gSr1RepDP6YyhYVlji3m0BOJIiHlUesrPvg998EsjUa0knjG0PN4WOv3n9GGKJ3jRZR_V-GRDzAkNDQNICTPHZzgRwbXsEQYZoX0zH1kqnc9_8E7-S_Trvr6j0y8y045Rcyu9Umsht_A_2hXx-K0piRzcRm5cZM47bpJhmUf-N9bpHrwzNJ0AxYU3_KfDkztspKaspCxjqUeA==\"}"
+ },
+ {
+ "type": "text",
+ "text": "I’m using the camera geometry to guide the grasp and handoff, checking the measured pose after each move.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_08ccae8539651651016ae26b7cf40881a2b5d69d58eeb0b3e0\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/cartesian_move.py",
+ "content": "\"\"\"Bounded world-frame TCP motion with interpolated IK and measured endpoint reporting.\"\"\"\nimport asyncio\nimport numpy as np\nfrom scipy.spatial.transform import Rotation, Slerp\nfrom kinex import communication, helpers, args, finish, profile\nfrom kinex.communication import duration\n\nasync def main():\n o=args(); arm=o.get('arm','left_arm'); side=arm.split('_')[0]; grip=side+'_gripper'\n async with communication() as io:\n model=helpers.joint_model(arm)\n with io.subscribe(arm+'.joint_state',depth=1) as stream:\n state=await stream.next(timeout_s=10)\n q=list(state.position)\n tcp=(await helpers.relative_pose(io,{'frame':grip+':tcp'},{'frame':'world:base'}))['pose']\n base=profile(arm)['frames']['base']; rb=Rotation.from_quat(base['rotation_xyzw']); tb=np.array(base['translation_m'])\n target=o.get('pose',tcp); seconds=o.get('duration_s',1.6)\n n=max(1,int(seconds/.04)); rots=Slerp([0,1],Rotation.from_quat([tcp[3:],target[3:]])); points=[]\n for i in range(1,n+1):\n f=i/n; r=rots(f); pos=np.array(tcp[:3])*(1-f)+np.array(target[:3])*f\n flange=pos-r.apply([.12,0,0]); local=rb.inv().apply(flange-tb); rot=rb.inv()*r\n q=model.ik([*local,*rot.as_quat()],q)\n points.append({'positions':q,'time_from_start':duration(i*seconds/n)})\n if o.get('dry_run'):\n finish({'start':tcp,'target':target,'q':q}); return\n await io.publish(arm+'.joint_target',{'joint_names':model.names,'points':points})\n if 'grip' in o: await io.publish(grip+'.target',{'data':o['grip']})\n wait=await io.request('world.wait',duration_s=seconds+o.get('settle_s',.16))\n measured={}\n for device in [arm,grip]:\n with io.subscribe(device+'.joint_state',depth=1) as stream: s=await stream.next(timeout_s=10)\n measured[device]=list(s.position)\n actual=await helpers.relative_pose(io,{'frame':grip+':tcp'},{'frame':'world:base'})\n with io.subscribe('head_camera.image',depth=1) as stream: im=await stream.next(timeout_s=10)\n image=helpers.save_image(im)\n finish({'wait':wait,'measured':measured,'tcp':actual},file=image)\nasyncio.run(main())\n"
+ },
+ "call_id": "call_71bc1611296b4b78a0d238e63f5a7b31|fc_08ccae8539651651016ae26b7ee55c81a2afd7dc07a563eb35"
+ }
+ ]
+ },
+ {
+ "id": "c0f01b4c",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:39:20.248Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/cartesian_move.py"
+ }
+ ]
+ },
+ {
+ "id": "27ad9df5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:23.965Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "plan left block approach",
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "pose": [
+ -0.167,
+ 0.09,
+ 0.86,
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ],
+ "duration_s": 2,
+ "dry_run": true
+ }
+ },
+ "call_id": "call_9952cf89eb744af2b8cbffe657bed045|fc_08ccae8539651651016ae26b8afccc81a2afcac521bdbff710"
+ }
+ ]
+ },
+ {
+ "id": "3a18aeec",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:26.765Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223565.977362546] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"start\": [-0.2616530267915924,-0.1484765921145812,1.070289798713373,-0.021897730331534127,-0.02189688895282258,0.6015608300353317,0.7982265238813591],\n \"target\": [-0.167,0.09,0.86,0,0,0.70710678,0.70710678],\n \"q\": [-0.37572560008508377,2.272537219262441,0.9478505586577836,1.3291237834325125,-0.32947784190081975,0.012933085784625174]\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "219b9da5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:29.294Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "left pregrasp motion",
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "pose": [
+ -0.167,
+ 0.09,
+ 0.86,
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ],
+ "duration_s": 2,
+ "grip": 1
+ }
+ },
+ "call_id": "call_9d081ed3d01c42deb851ceb545a56207|fc_08ccae8539651651016ae26b9084f881a28c72b274a17a9916"
+ }
+ ]
+ },
+ {
+ "id": "aec57b8e",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:39.161Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223571.307316769] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"wait\": {\"success\":true,\"message\":\"ok\",\"time_s\":5.36,\"waited_s\":2.16},\n \"measured\": {\"left_arm\":[-0.36332982778549194,2.2126855850219727,0.8944761157035828,1.319221019744873,-0.30946946144104004,0.010132407769560814],\"left_gripper\":[1.0015521916476162]},\n \"tcp\": {\"pose\":[-0.1736376085877378,0.08114210634963587,0.8698353295464993,-0.0019216401989559503,0.00033106205038283427,0.7041296202769071,0.7100687822637771],\"timestamp\":5.36},\n \"file\": \"/tmp/kinex-observation-isoz5fmq.png\"\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/aec57b8e-1.png"
+ }
+ ]
+ },
+ {
+ "id": "1867263c",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:39:44.115Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Approaching surface**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_08ccae8539651651016ae26b9d445881a2aff8fd80d77c5cd8\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Approaching surface**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4mufdUKM6fDyPhSuIt5GA6xIPEcMTDEpRYyL6doxcayo7a88Z0PjutQ8VweSvPps3IrMsl9j2UU2W7IG_imFve-0RS2OYOGmsFsz3ORniUBBtr82ilB-dTEyDx3tk2MeXEsauzmH6rJ5XwWcaE6U6RxYyuiAU8NANbVb7zc_nfMwOrf6PUIJI1ky8_boZ07ic0YPnitsyHN-u_V9v14mj8sR2yCSeX1PFAXkdAdgx3QqcdlzusURTZ6krWzsHtANPK0So6SQh1fRQvWkOnRh7DtRbc-VCO0bGuDnJDojBPZzJKdoIi9r8hj16ZLnsCM90mA6IuA7nz9TLP6M0g7rOT4orysBgSdHj1hzhNIZFYaKOS-Zp4TwMFtBAyEIBtNyQpUjalItwCxAU1BCx3A6em_EZ1UF1OGZhiqx63UJrkL_xuHLvsYJkZ4fsYqsEoGd_46fBxw42PPJaiuS4-deE0KaHNg6Oat9hWMoAufUmRUXJ-xBrcprZWEbOv3RgPDLXvLowogIuSI3NDkDOzjPhWfehADQlMXwY--rFML1GlTkiXB6mFSKevu5ZT4oVnGqiPc_CjPYey4F5EorQ3Ic07Fl7YdXpZ6fQA7hTYwZR6JsbAcYl1pzzstW2FG1tzC-EmO0m4vCFYXJFe9T3u3FuMU5FmGmGkoQ-7lbTHuPzKwBmw9fPCRvtVip6OV9GHOeud-8n-Vqycl7JJ-UEkQJMJ7Vkc68WNcoE_aYij5kxiPknjHd4wUOQeSzk_OUPQOFJ7LweLhFR5fQez12FIRt94EAT2i3E6knrVxuOKeLpEcBkXCWMfBd-tLpOJwWt6hQmEUTLVLubIfYhbJzjOr0ZJ5nfnGYLTMy1Q7iOqATsiduS3qDuc-WpgK1l5d3StTmmEU7NS_H8NTANEembapHWpgBan84jE1q33w3mUw4-fQ2uFMH87HsPrRL3pd1rnygWkItperZWg0r4m3_W4uTfR89Z7sqP33bcHjq5Ke2LOTka_4JcgpbXytrZ-LOpNQWCTWHoerDZ24tbFUmZ5wlznc2FxhwSbmfEVylTWQpTQum3YXy0ssXyM_AhmMnOtpIhmxaWqSOFbu2TMtBUby5iETUAvZnb-tIMoqF1mFT7ar4Kqwd_REZddo5pNvxeKDFJy9Zu-vIGdxiO7YRTleKYBg-tIA0m9lnvLJwedeBGi5-BUDGnaZpOdVyzmCCX0J1jaLO78GI26qPCn_E_qreTAIgEp-1YcxSgveuIDAzsV-IO-pImHxH1RREvqHHfwQWt0REIBje54tTC2IR4NPyL96gCP2gC4IGkyKMa4SlBN2Soree4_VPQMhEBYcVpaWuMt_pdrfmo_7fCxrrsWGSguy_bB2eJylSydb9iFHfaUL-RTynT8ZRre-3i8sgWb-dkF2cxApD2D24qJa4l9LqSWTWzo00_1qUHclmWrkqdhypyuf6obLtd-yhWsgTbfs8fp_tZx6gFBkKWDpNufbKokKNqKqMdoburRtuW_mthFkqtGmcuh0uoWFfd5zjOF4QiulCxh5VhaupPvtZnHq9OoQaghvuqFioG_gkg71BT1AQTTiubnrnebzyFml-1hqpjcKvhUMT9WriB92gFOjpoPBLEf1aZNcNUTDZk8v7Vl1yy7xoY575Sn4VHMLgHlmRlxn5UFvVbZPBmCMl1uMRuX-wC5yPh4aku-0KCQ4LHAAY7dLl-oOZIn0KJxwBoH95XvK3qmHKSgjzonsUZfRyBrTccr2BnlNEpvSnSjhOxpszep132BR4vs6n-EhhI3Ygti1ZXhNWhYbQsSlw6gijbw7OmWIzIXQsxrRXIy0Q4e2-agIaiMGLnUc8j3IqetoM0utQ\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "left grasp insertion",
+ "file": ".kinex/tools/cartesian_move.py",
+ "args": {
+ "pose": [
+ -0.166,
+ 0.19,
+ 0.86,
+ 0,
+ 0,
+ 0.70710678,
+ 0.70710678
+ ],
+ "duration_s": 1.2,
+ "grip": 1,
+ "settle_s": 0.24
+ }
+ },
+ "call_id": "call_bcb95f3488544f8492645067724488a5|fc_08ccae8539651651016ae26b9ea01c81a29c4cde48f7e394a7"
+ }
+ ]
+ },
+ {
+ "id": "c76830d5",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:39:52.093Z",
+ "error": false,
+ "parts": [
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+ "timestamp": "2026-10-28T21:41:07.437Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"right_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":12.36,\"frame_id\":\"right_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-w35ecyf0.png\"},\n {\"deviceID\":\"left_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":12.36,\"frame_id\":\"left_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-ug63nito.png\"}\n ]\n}"
+ },
+ {
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+ "src": "observations/72608f9f-1.png"
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+ "timestamp": "2026-10-28T21:41:16.372Z",
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+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/color_geometry.py",
+ "content": "\"\"\"World-coordinate visible red/blue surface bounds from calibrated RGB-D.\"\"\"\nimport asyncio\nimport numpy as np\nfrom scipy.spatial.transform import Rotation\nfrom kinex import communication, helpers, args, finish, profile\nasync def main():\n out={}\n async with communication() as io:\n for camera in args().get('cameras',['head_camera','right_camera']):\n im,depth=await helpers.camera_frame(io,camera)\n a=helpers.image_array(im); d=helpers.image_array(depth)*.001\n t=await helpers.relative_pose(io,{'frame':camera+':base'},{'frame':'world:base'})\n pose=t['pose']; r=Rotation.from_quat(pose[3:]); p=profile(camera)['color']['projection']\n objects={}\n for name,mask in [('red',(a[:,:,0]>130)&(a[:,:,1]<90)&(a[:,:,2]<90)),('blue',(a[:,:,2]>130)&(a[:,:,0]<90)&(a[:,:,1]<90))]:\n v,u=np.where(mask&(d>0))\n if len(u)<5: continue\n z=d[v,u]; xyz=np.array([(u-p['cx'])*z/p['fx'],(v-p['cy'])*z/p['fy'],z]).T\n w=r.apply(xyz)+pose[:3]\n objects[name]={'bounds':[np.quantile(w,.01,axis=0),np.quantile(w,.99,axis=0)],'median':np.median(w,axis=0),'n':len(u)}\n out[camera]=objects\n finish(out)\nasyncio.run(main())\n"
+ },
+ "call_id": "call_3173ea39534e4bcea668577f8fbf32b1|fc_08ccae8539651651016ae26bf84b8081a2a6ac741a3914dead"
+ }
+ ]
+ },
+ {
+ "id": "cf187b01",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:41:16.374Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/color_geometry.py"
+ }
+ ]
+ },
+ {
+ "id": "df7b82d0",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:41:18.616Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure handover block position",
+ "file": ".kinex/tools/color_geometry.py"
+ },
+ "call_id": "call_8920028376e5431e9985bc22610f3344|fc_08ccae8539651651016ae26bfe11cc81a2a2a26f80f37dd092"
+ }
+ ]
+ },
+ {
+ "id": "79e69461",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:41:21.488Z",
+ "error": false,
+ "parts": [
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+ "text": "{\n \"output\": \"[INFO] [1793223824.665814335] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"episode ended during wait\",\n \"code\": \"operation_rejected\",\n \"details\": {\n \"operation\": \"world.wait\",\n \"type\": \"kinex_interfaces/srv/Wait\",\n \"response\": {\"success\":false,\"message\":\"episode ended during wait\",\"time_s\":20.92,\"waited_s\":0.120000000000001}\n }\n}"
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+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
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+ "action": "image"
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+ {
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+ "action": "joint_state"
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+ "text": "{\n \"results\": [\n {\"deviceID\":\"head_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":20.92,\"frame_id\":\"head_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-327div3_.png\"},\n {\"deviceID\":\"right_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.7629235739057715],\"velocities\":[0.789993865923448],\"joint_names\":[\"right_gripper\"],\"timestamp\":20.92}},\n {\"deviceID\":\"left_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.9997891133481807],\"velocities\":[0.0002649718226166442],\"joint_names\":[\"left_gripper\"],\"timestamp\":20.92}}\n ]\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/e6fe50bf-1.png"
+ }
+ ]
+ },
+ {
+ "id": "f6538a4a",
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+ "timestamp": "2026-10-28T21:43:59.525Z",
+ "error": false,
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+ },
+ {
+ "type": "tool",
+ "name": "device",
+ "input": {
+ "deviceID": "right_gripper",
+ "action": "target",
+ "args": {
+ "data": 1
+ }
+ },
+ "call_id": "call_70ae02b3dea14604a1a2de07a8a2eb93|fc_08ccae8539651651016ae26c9e0a0081a2b4ea17fa1083202c"
+ }
+ ]
+ },
+ {
+ "id": "7e4777ba",
+ "role": "toolResult",
+ "tool": "device",
+ "timestamp": "2026-10-28T21:43:59.565Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"published\": true\n}"
+ }
+ ]
+ },
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+ "tool": null,
+ "timestamp": "2026-10-28T21:44:08.423Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Building largest-component ROI**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_08ccae8539651651016ae26ca1aa8481a2b739dc56ecfecdaf\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Building largest-component ROI**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4myoYns2ZZBjq4C9yWAQ2YCT1EWFf_sEyLvpDlghcUiOQopoy1QJ9YmM0RRz8CxNPB1liYE9K7sbnhfZj5coD-cNNtjH3_szR51CyobxWR7N0zr7IZtmf4JRutgKVm2p6uIZn2VNlgHcW7UhqiWxZZ42NaJW5lRYBMSGVbIDYQjQ-pFinNYAnGW0XMWf_wk3sfPGnbec8uDwKv8c0dta5-RczBqpf3c-BbOzBqkxcPc6SvKHXybpZ2Ru8l0EM9I0I-AW0LkQDsMeC62d7bxORL8cH-Ie_CnMmAYL2b5OoON09gVr4XjFyE6Wf0PD0KfAel83M1u7nd8HLoP5RteYlz9w05IVtG3cz780E8maWiQNAaCc8lVG3uhyPuA2Z7FfgEzg5Gs-7W-_3EJqQtlM0b0zKrjt0lexQFyx4HgvGh56UYYUGprIfEvutLxRR7rsqOy9welw9ilOT-fCSJNnJJ56ADk_UzGRpVNc4uiLg0g5K2HN3jXK2j6g3PwGToc4HRbEgGRHHPXpP3evxdNmQLss7TEv6GFuHOlEPw4jHo4aZ22oETt5230olsjP39u2Yfx4TT75y-fze8N7l69RzC1VxC2RUL9tVnCo3s8YKkIf6NSu6J7oIE1JfeQkVuwuQIiuuyjS1XtDpFLvDWDu0e-X_atJMcRmbJpj46G7HDnCp6z04rHk1TSKfzJeEoC1utk6pzF_4ZWpgecRDLBmTAGtHxgf02URY8AJwT__Y9BtODMlxEEZ-Qkx1p8LTAmIPSvozoCxFjxQ1Ts21DK3HGv8mdUdDaKIUuzhFa86KBKj9tqJdkUqbE0c6WnxcUbIu0wwDJ_qRttsAjc7zcgt8sVMdej0nbep0mVLpj6eIRX23v96cTB6NilaPMz3schmMkZjcsX_9iMJ94NLawOsWBl2Rh1s-kywUsdQsNmx0FDDApN_riy9ozCTGgJWIIC4995oCF5vTGC2MhqpCUNLytSA9DXr5XYKMLtDMvsYqRbBaqWox39BKvRbbmuBFUUNEJEtpSu3xXk5oy8wL0LVpMCHC9__SvTGFppnw0-Bff5K1U2Jb3RcqJRF1yldkf3nrMtlC2p6V9Jx6BjcaauvHEAnQqmfx0La5DLIq9e5Xau8V85Q-3XCaWKxO96dQlyIfdiENkvMqPdu4Wm6SEqqINqzuU0tlCmzwvezLrm-p8KuVnrdqTGrh20CK7kj5685h3N4jETNr04abjgsUMCHs-alibfJzuZ06L4qQ3TO4O4o5R12kPnVmP0di8j_fTaZUxMhkSkwepNJgD5nONRM6s8Di0g9yidHVbbX6UShWBH5YfI0W_Og0qRkqZiRjY_eTM99711WYqVz10HZ5_UgncmSk0Vi_P_y-asrkoiS_5ZBEQCYUFyQdWzCyNoD16T8URphLIbxmZ-pabu6U2M36qr36C30_tJvH4UIHLL9-bPUW1Uv-Wnmf3-AvDqTgCmQT14VOC-yx0dAb0HPaKrmph_V0Bb6RfmzH8r01Xt06eh5IfYlR8lUFjRyCjrctn1pA9l3ypjf2EBlThwVgk-RgVvTkH2it_jFQfWF38a61DGftcIfh1I-WvoyNSxVFmbbqbkiiBNwLKCyeBduJFOSw4dTt21VK0WVnC8ie69jkBembXjtr4mqaYj5b0lQWngVPwyBNNI5k6aDU_WvziFq18u4s2oHkt8NbLCYdoVSRQtCN0yg5vpcR5AcMGNXYDBI-Y9_KgjF0z0MofVd_XwCKtBxauGgb_gvXSpSfLO9Nwrj-zpcSkiAi7yvkZbhmtTm6BackiuyTwOgcxayBjHX_jE1_UCAK7HTkKUZQSeAn4cuqNtUXsmuC-2LIzIDhdO3bMhDwP0eI9hTnaRFrfwLdVE-_pgwMqa1X9pNlafPVcvSaBGosRWNRMoFJDjt19bTh5h0Mnha5TBhcnc7G6By8SegmH2TZfoS7pD5PiW6ZvhrqHRtuRJTjYXTWGxKcdxoTWTIBvDNhVcT7J0rENYXrxmN1Pz5xJF1g3QhGc_hG5T9x_Y0XaGmNd4OS2r55AuzdMaZf3ApfjBiCdu37xdW7M7bEksm-7lvBEVpMzC2cORcIR7nQ7hEImbi7zgHx8M-L4glcbCI_SYSx3b_D8nPtvyYmMUVZ5RPnQQ3LfEmjSbjpM2PUUKyOn-R_5OJQHVS7xyx4PEoUxfv8hrA93ltok8olw==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "edit",
+ "input": {
+ "path": ".kinex/tools/color_geometry.py",
+ "edits": [
+ {
+ "oldText": "from scipy.spatial.transform import Rotation\n",
+ "newText": "from scipy.spatial.transform import Rotation\nfrom scipy.ndimage import label\n"
+ },
+ {
+ "oldText": " v,u=np.where(mask&(d>0))\n if len(u)<5: continue\n",
+ "newText": " components,count=label(mask)\n if not count: continue\n sizes=np.bincount(components.ravel()); sizes[0]=0\n mask=components==int(sizes.argmax())\n # Near-gripper RGB-D can be inside the declared minimum range.\n v,u=np.where(mask&(d>=.1)&(d<2))\n if len(u)<5: continue\n"
+ }
+ ]
+ },
+ "call_id": "call_7601c444d1924c5d8b54cae42375943f|fc_08ccae8539651651016ae26ca49e8c81a2935fd086d8f4b25c"
+ }
+ ]
+ },
+ {
+ "id": "7bb995dc",
+ "role": "toolResult",
+ "tool": "edit",
+ "timestamp": "2026-10-28T21:44:08.431Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 2 block(s) in .kinex/tools/color_geometry.py."
+ }
+ ]
+ },
+ {
+ "id": "fb15e3f6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:44:31.750Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/memos/handover-block.md",
+ "content": "# ALOHA AgileX handover\n\nRead refreshed profiles and harness each episode. Native dt=.04 s; all waits sequential. No reset. Available tools: `handover_policy.py` bounded StarVLA chunk + measured feedback; `cartesian_move.py` world TCP interpolation/IK + feedback; `color_geometry.py` visible surface bounds, not object centers. Load devices through host. Inspect operation schemas.\n\nPolicy returned 16-action chunks, but first 80 frames did not grasp; geometric control worked more directly. Do not blindly reuse numerical scene positions: measure RGB-D each episode. Red object is a tall upright rectangular block, not a small cube. This episode front surface was x≈-.167,y≈.168, base z≈.740; blue pad center≈[.113,.150], top z≈.746. Block width/thickness≈.06 m. Wrist depth at near grasp is unreliable (<.1m), head views may occlude block; color geometry now filters largest component and valid range.\n\nGripper TCP +x approaches; fingers close along local y. World left orientation quat xyzw=[0,0,.707107,.707107] approaches +y, closes x. Left pregrasp [-.167,.09,.86], insertion [-.166,.19,.86], close 0; measured opening≈.74 with object. Lift to [-.163,.135,.98], stage [-.03,.09,1.0]. Block bottom then≈.879. Right orientation [0,0,1,0] approaches -x, closes y. Right pregrasp [.085,.107,.923], insertion [-.035,.108,.923], close; measured≈.76. Right grasps ~.077m below left; open left then withdraw along -y to -.07. Carry right [.125,.154,.94], lower [.137,.154,.803], seat [.140,.154,.787]. Actual TCP tracking lag 5–15 mm; block bottom≈TCP z-.046, center x≈TCP x-.02. Verify measurements instead of relying on targets. Right-held block visibly moved while left open and withdrawn.\n\nLatest episode: release target 1 at t20.8; world terminated during wait at20.92 (523 frames), not a full successful wait. Held devices, read final image/block over pad and right opening .763, left≈1.0. Restored right open target1 after hold, no further waits. Full-open arrival and native verdict were NOT available; owner finalizes. A terminal wait alone is never success evidence.\n"
+ },
+ "call_id": "call_4312b178a5234e2b8111a2a90077805c|fc_08ccae8539651651016ae26caab28481a28e9d7cf3496c0212"
+ }
+ ]
+ },
+ {
+ "id": "5e715242",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:44:31.753Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/memos/handover-block.md"
+ }
+ ]
+ },
+ {
+ "id": "7ec0985d",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:44:34.975Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Handed the block to the right arm and placed it on the blue pad. Commanded release, but the episode ended before full gripper opening could be verified.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_08ccae8539651651016ae26cc1f00481a29048bc0605ab1e17\",\"phase\":\"final_answer\"}"
+ }
+ ]
+ }
+]
diff --git a/experiments/robotwin-native/kinex_policy-1/usage.json b/experiments/robotwin-native/kinex_policy-1/usage.json
new file mode 100644
index 0000000000000000000000000000000000000000..6d328f91c451e2f2a6396b2cd8bb9e994950bee0
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-1/usage.json
@@ -0,0 +1,386 @@
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+ "parser": "harbor/0.22.0",
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diff --git a/experiments/robotwin-native/kinex_policy-1/vla-io.json b/experiments/robotwin-native/kinex_policy-1/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..235db79f0159ef64a30ceab79e0b5a9b2a1bb184
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-1/vla-io.json
@@ -0,0 +1,3335 @@
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+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n",
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+ {
+ "type": "text",
+ "text": "use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793223469.135563916] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.04086500033736229,1.74478018283844,1.4346884489059448,0.307611346244812,1.0182968378067017,0.03287385031580925],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"left_gripper\":{\"position\":[0.9985552294687792],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_arm\":{\"position\":[0.012346736155450344,0.08589094132184982,0.07706005871295929,-0.05403941124677658,-0.005238042213022709,-0.005991658661514521],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_gripper\":{\"position\":[0.9958593384786086],\"stamp\":{\"sec\":1,\"nanosec\":280000000}}},\n \"file\": \"/tmp/kinex-observation-n_o6e3b9.png\"\n }\n}"
+ },
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+ "path": ".kinex/tools/handover_policy.py",
+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n",
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+ },
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+ "content": [
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+ },
+ {
+ "type": "text",
+ "text": "use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
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+ "trace_output": "{\n \"output\": \"[INFO] [1793223477.284126808] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.058308765292167664,1.929189920425415,1.599496841430664,0.3592958450317383,1.0783706903457642,-0.016372166574001312],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[1.0109648487784646],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.09248543530702591,0.4811040759086609,0.44249579310417175,-0.3714327812194824,0.0018695585895329714,-0.09739844501018524],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.9959367567842657],\"stamp\":{\"sec\":1,\"nanosec\":920000000}}},\n \"file\": \"/tmp/kinex-observation-u4ddnv07.png\"\n }\n}"
+ },
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+ "path": ".kinex/tools/handover_policy.py",
+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n",
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+ "text": "use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "description": "close left grasp",
+ "file": ".kinex/tools/handover_policy.py",
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+ "session_event_id": "3da59974",
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+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793223486.950859814] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.04435889795422554,1.231294870376587,1.0781995058059692,0.17081087827682495,0.6730543971061707,-0.069943368434906],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"left_gripper\":{\"position\":[1.0099254927851937],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_arm\":{\"position\":[0.2739063501358032,1.267305612564087,1.2323172092437744,-0.9213956594467163,0.01157537754625082,-0.31220439076423645],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_gripper\":{\"position\":[0.9980137077244846],\"stamp\":{\"sec\":2,\"nanosec\":560000000}}},\n \"file\": \"/tmp/kinex-observation-2otm1ktx.png\"\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/3da59974-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793223486.950859814] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.04435889795422554,1.231294870376587,1.0781995058059692,0.17081087827682495,0.6730543971061707,-0.069943368434906],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"left_gripper\":{\"position\":[1.0099254927851937],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_arm\":{\"position\":[0.2739063501358032,1.267305612564087,1.2323172092437744,-0.9213956594467163,0.01157537754625082,-0.31220439076423645],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_gripper\":{\"position\":[0.9980137077244846],\"stamp\":{\"sec\":2,\"nanosec\":560000000}}},\n \"file\": \"/tmp/kinex-observation-2otm1ktx.png\"\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/handover_policy.py",
+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n",
+ "sha256": "ea4a1f777901a4d4587296127db2f8de641a9d629bf02385600456c53d51999d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 5,
+ "call_id": "751ab5e219b74ccb88b491a911a0a769",
+ "received_at_ns": 1793223500508280030,
+ "completed_at_ns": 1793223500781733931,
+ "request": {
+ "task": "use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open",
+ "obs": {
+ "images": [
+ "/workspace/artifacts/policy/751ab5e219b74ccb88b491a911a0a769-0.png",
+ "/workspace/artifacts/policy/751ab5e219b74ccb88b491a911a0a769-1.png",
+ "/workspace/artifacts/policy/751ab5e219b74ccb88b491a911a0a769-2.png"
+ ]
+ }
+ },
+ "images": [
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+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-1/policy/751ab5e219b74ccb88b491a911a0a769-0.png",
+ "recorded_size": [
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+ "recorded_sha256": "a6e682bcb4645d4a4493f024c92a9ffdca7989011a29eb37e218aea406e8140e",
+ "model_image": "experiments/robotwin-native/kinex_policy-1/model-inputs/751ab5e219b74ccb88b491a911a0a769-0.png",
+ "model_size": [
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+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793223500.049809102] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.0294959656894207,0.6043052077293396,0.5100125670433044,0.10033784061670303,0.33127984404563904,-0.05462042614817619],\"stamp\":{\"sec\":3,\"nanosec\":200000000}},\"left_gripper\":{\"position\":[1.004523279992017],\"stamp\":{\"sec\":3,\"nanosec\":200000000}},\"right_arm\":{\"position\":[0.36748456954956055,1.8742890357971191,1.8310723304748535,-1.2713841199874878,-0.005831398069858551,-0.4040740430355072],\"stamp\":{\"sec\":3,\"nanosec\":200000000}},\"right_gripper\":{\"position\":[1.0009333870627664],\"stamp\":{\"sec\":3,\"nanosec\":200000000}}},\n \"file\": \"/tmp/kinex-observation-mpnweq9k.png\"\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/handover_policy.py",
+ "content": "\"\"\"One bounded policy chunk followed by fresh measured feedback. Devices must be loaded.\"\"\"\nimport asyncio\nfrom kinex import communication, helpers, args, finish\n\nTASK = 'use the left arm to grasp the red block on the table, hand it over to the right arm, and set it down in the center of the blue pad. Release it with the right gripper open'\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = []\n for camera in ['head_camera', 'left_camera', 'right_camera']:\n with io.subscribe(camera + '.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n images.append(helpers.save_image(image))\n result = await helpers.run_policy(io, 'policy', {'images': images},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n action_hz=25, max_actions=opts.get('max_actions', 32))\n states = {}\n for device in DEVICES:\n with io.subscribe(device + '.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n states[device] = {'position': list(state.position), 'stamp': state.header.stamp}\n with io.subscribe('head_camera.image', depth=1) as stream:\n image = await stream.next(timeout_s=10)\n path = helpers.save_image(image)\n finish({'execution': result, 'measured': states}, file=path)\n\nasyncio.run(main())\n",
+ "sha256": "ea4a1f777901a4d4587296127db2f8de641a9d629bf02385600456c53d51999d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ }
+ ],
+ "coverage": {
+ "recorded_inputs": 5,
+ "recorded_outputs": 5,
+ "kinex_calls_associated": 5,
+ "original_temporary_image_paths_recorded": false,
+ "normalized_action_tensor_recorded": false,
+ "processor_tensors_recorded": false,
+ "executed_tool_source_at_call_verified": 5
+ },
+ "contract": {
+ "request": "policy.infer(obs, task). obs contains three ordered RGB image files; no joint state or agent conversation is sent to the VLA.",
+ "image_preprocessing": "RGB conversion, then OpenCV INTER_AREA resize to 224 x 224. Model images shown here are reconstructed from retained input pixels with the executed preprocessing.",
+ "request_paths": "The logger replaced temporary input filenames with retained image-copy paths. Original temporary path strings were not retained.",
+ "service_response": "actions, inference_s and call_id are reconstructed exactly from the logged values and the executed handler return. raw_actions is internal diagnostic data and is not returned to Kinex.",
+ "agent_response": "Kinex helpers.run_policy consumes the action array and returns actions_submitted, duration_s and ik_failure. The language agent sees the exec tool result below, including feedback and images selected by its own code.",
+ "output_layout": [
+ "left_joint_1",
+ "left_joint_2",
+ "left_joint_3",
+ "left_joint_4",
+ "left_joint_5",
+ "left_joint_6",
+ "left_gripper",
+ "right_joint_1",
+ "right_joint_2",
+ "right_joint_3",
+ "right_joint_4",
+ "right_joint_5",
+ "right_joint_6",
+ "right_gripper"
+ ],
+ "diagnostic_layout": "Left 6 joints, right 6 joints, left opening, right opening. Gripper conversion: 1 - 2 * clip(opening, 0, 1).",
+ "not_recorded": [
+ "normalized action tensor before denormalization",
+ "backbone processor tensors",
+ "exact original temporary filename strings"
+ ],
+ "backbone_prompt": "Reconstructed from the executed QwenOFT and QWen3 implementations; 16 action query markers are appended by the model, not by Kinex.",
+ "model_metadata": "experiments/robotwin-native/kinex_policy-1/policy/model.json",
+ "executed_sources": "policy-contract/sources.json"
+ }
+}
diff --git a/experiments/robotwin-native/kinex_policy-2/analysis.json b/experiments/robotwin-native/kinex_policy-2/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..05956ce17ac730415f4929395992b0a8eaad66ab
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-2/analysis.json
@@ -0,0 +1,3 @@
+{
+ "observed": "Kinex ran 15 policy inferences (240 control frames), always with the full original instruction. The video shows pickup followed by lost placement. It then tried agent-written geometric recovery and stopped at frame 498 of 600, explicitly reporting failure and opening both grippers. This was an agent decision to stop, not budget exhaustion."
+}
diff --git a/experiments/robotwin-native/kinex_policy-2/artifact-index.json b/experiments/robotwin-native/kinex_policy-2/artifact-index.json
new file mode 100644
index 0000000000000000000000000000000000000000..428ac29c7d7c25df16c8f5974a9376f4ff31901c
--- /dev/null
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diff --git a/experiments/robotwin-native/kinex_policy-2/detail.json b/experiments/robotwin-native/kinex_policy-2/detail.json
index 67c366a2dab980ad647f58831ca5d3428247b65a..ea0bfbceead52b863c018cd103e44bfdf71839a3 100644
--- a/experiments/robotwin-native/kinex_policy-2/detail.json
+++ b/experiments/robotwin-native/kinex_policy-2/detail.json
@@ -502,8 +502,14 @@
"usage_source": "provider-raw"
},
"cost_note": "API equivalent sums the native Pi session cost estimates. Subscription billing is not reported.",
- "media_note": "All three native views and every frame retained. Frame timing is unchanged; playback starts at zero.",
+ "media_note": "Three 960 x 720 views side by side; every native sample once at 4x simulation speed.",
"artifacts": [
+ {
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+ "path": "experiments/robotwin-native/kinex_policy-2/analysis.json",
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+ },
{
"name": "artifacts.json",
"path": "experiments/robotwin-native/kinex_policy-2/artifacts.json",
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diff --git a/experiments/robotwin-native/kinex_policy-2/presentation/frame-mapping.json b/experiments/robotwin-native/kinex_policy-2/presentation/frame-mapping.json
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index 0000000000000000000000000000000000000000..6724a2276654a8dc2d47ba1f497ac6deeb3b2782
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diff --git a/experiments/robotwin-native/kinex_policy-2/presentation/media-validation.json b/experiments/robotwin-native/kinex_policy-2/presentation/media-validation.json
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+{
+ "schema": "rosbridge/recording/1",
+ "run_id": "ebcedf7e2ae7",
+ "task": "robotwin/place-dual-shoes-aloha-agilex",
+ "state": "complete",
+ "views": {
+ "third_person": {
+ "received": 201,
+ "dropped": 0,
+ "segments": [
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+ "width": 960,
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+ "fps": 10.0,
+ "first_stamp_ns": 0,
+ "last_stamp_ns": 19920000000
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+ "error": null
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+ "left_wrist",
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+ "fps": 10.0,
+ "topics": [],
+ "error": null,
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+}
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+{
+ "max_steps": 600,
+ "seed": 0,
+ "episodes": 1,
+ "control_frequency_hz": 25,
+ "provider": "rosbridge",
+ "realtime": false,
+ "stop_on_success": true
+}
diff --git a/experiments/robotwin-native/kinex_policy-2/transcript.json b/experiments/robotwin-native/kinex_policy-2/transcript.json
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+++ b/experiments/robotwin-native/kinex_policy-2/transcript.json
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+[
+ {
+ "id": "20d7331f",
+ "role": "system",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:18.709Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ""
+ }
+ ]
+ },
+ {
+ "id": "c215ee7e",
+ "role": "user",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:18.710Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "# Task: robotwin/place-dual-shoes-aloha-agilex\n\nuse both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open\n\n## Work to do\n\nSolve the task efficiently using the running rosbridge environment. Follow the\ntask instruction above, including its completion requirements. Read `harness.md`\nand the device profiles for public interfaces, units and calibrated frames.\nReuse your saved tools, skills, and memos.\n\n## Limits\n\nYou have 600 native action frames. The execution mode is `stepped`: physics is\nfrozen while idle. Use `world.wait` with `duration_s` to advance the native clock.\nJoint targets are ROS JointTrajectory messages; gripper targets use the units\ndeclared in their profiles. Reads and command publication do not advance physics.\nWaits are sequential; concurrent waits are rejected. A command or elapsed time\ndoes not prove arrival; inspect measured feedback. Device stop holds the device\nwithout ending the episode. The safety timeout is 28800 seconds.\nDo not launch or reset a simulation.\n\n## Completion\n\nReturn when finished. The owner finalizes the episode and reads its native\nverdict. An interrupted or rejected wait does not establish task success. The\nnative step limit stops physics even if your requested wait is longer.\n\n## Saved resources\n\nMaintain reusable code in `.kinex/tools/`, skills in `.kinex/skills/`, and concise working notes\nin `.kinex/memos/`. Improve existing files in place as you learn, replacing outdated\ncontent. Create a new file only when no existing resource fits; do not create\nper-attempt reflections or numbered copies. These files persist across fresh\nconversations. Update them before finishing your response.\n\n## Robot and device access\n\nUse Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place."
+ }
+ ]
+ },
+ {
+ "id": "741ff487",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:21.491Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "ls",
+ "input": {
+ "path": "/workspace"
+ },
+ "call_id": "call_2be0a7f253ee4abf86ce531d7ad43b28|fc_0b5218887c37459e016ae26d2d0c78819f8cc39f5feaf7fdcb"
+ }
+ ]
+ },
+ {
+ "id": "c4aeaddd",
+ "role": "toolResult",
+ "tool": "ls",
+ "timestamp": "2026-10-28T21:46:21.499Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ".kinex/\nharness.md\ninstruction.md"
+ }
+ ]
+ },
+ {
+ "id": "a0f31098",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:24.611Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/workspace/harness.md",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_d9fc0acab16d4ca2a46a36ae77694e1a|fc_0b5218887c37459e016ae26d2fc904819f835d2d1c802765b8"
+ }
+ ]
+ },
+ {
+ "id": "e62f1e22",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:46:24.617Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Use Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place.\n"
+ }
+ ]
+ },
+ {
+ "id": "4748d1f1",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:26.699Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "find",
+ "input": {
+ "pattern": "**/*",
+ "path": "/workspace/.kinex",
+ "limit": 160
+ },
+ "call_id": "call_07a13441eb1747dbbbee6d0001fc549b|fc_0b5218887c37459e016ae26d323c0c819f940920553b103914"
+ }
+ ]
+ },
+ {
+ "id": "84d5c0bd",
+ "role": "toolResult",
+ "tool": "find",
+ "timestamp": "2026-10-28T21:46:26.726Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "devices/\ndevices/head_camera/\ndevices/head_camera/profile.yaml\ndevices/left_camera/\ndevices/left_camera/profile.yaml\ndevices/policy/\ndevices/policy/configuration.json\ndevices/policy/env.sh\ndevices/policy/node.py\ndevices/policy/profile.yaml\ndevices/right_gripper/\ndevices/right_gripper/gripper.urdf\ndevices/right_gripper/links.py\ndevices/right_gripper/profile.yaml\ndevices/world/\ndevices/world/profile.yaml\nkinex.json\nmemos/\npython/\npython/.pixi/\npython/pixi.lock\npython/pixi.toml\npython/ros/\npython/ros/build/\npython/ros/build/.built_by\npython/ros/build/COLCON_IGNORE\npython/ros/build/kinex_interfaces/\npython/ros/build/kinex_interfaces/rosidl_generator_cpp/\npython/ros/build/kinex_interfaces/rosidl_generator_cpp/kinex_interfaces/\npython/ros/install/\npython/ros/install/.colcon_install_layout\npython/ros/install/COLCON_IGNORE\npython/ros/install/_local_setup_util_ps1.py\npython/ros/install/_local_setup_util_sh.py\npython/ros/install/kinex_interfaces/\npython/ros/install/kinex_interfaces/include/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/rosidl_generator_c__visibility_control.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/rosidl_generator_cpp__visibility_control.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/rosidl_typesupport_fastrtps_c__visibility_control.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/rosidl_typesupport_fastrtps_cpp__visibility_control.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/msg/rosidl_typesupport_introspection_c__visibility_control.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__builder.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__description.c\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__rosidl_typesupport_fastrtps_cpp.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__rosidl_typesupport_introspection_c.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__rosidl_typesupport_introspection_cpp.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/json__struct.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/lookup_transform__functions.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/lookup_transform__rosidl_typesupport_introspection_cpp.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/lookup_transform__type_support.c\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/lookup_transform__type_support.cpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/lookup_transform__type_support.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/wait__description.c\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/wait__struct.hpp\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/wait__type_support.c\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/detail/wait__type_support.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/json.h\npython/ros/install/kinex_interfaces/include/kinex_interfaces/kinex_interfaces/srv/lookup_transform.h\npython/ros/install/kinex_interfaces/lib/\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_generator_c.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_generator_py.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_c.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_cpp.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_fastrtps_c.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_fastrtps_cpp.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_introspection_c.so\npython/ros/install/kinex_interfaces/lib/libkinex_interfaces__rosidl_typesupport_introspection_cpp.so\npython/ros/install/kinex_interfaces/lib/python3.12/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/__init__.py\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/__pycache__/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/__pycache__/__init__.cpython-312.pyc\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/_kinex_interfaces_s.ep.rosidl_typesupport_c.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/_kinex_interfaces_s.ep.rosidl_typesupport_fastrtps_c.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/_kinex_interfaces_s.ep.rosidl_typesupport_introspection_c.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/kinex_interfaces_s__rosidl_typesupport_c.so\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/kinex_interfaces_s__rosidl_typesupport_fastrtps_c.so\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/kinex_interfaces_s__rosidl_typesupport_introspection_c.so\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__init__.py\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__pycache__/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__pycache__/__init__.cpython-312.pyc\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__pycache__/_json.cpython-312.pyc\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__pycache__/_lookup_transform.cpython-312.pyc\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/__pycache__/_wait.cpython-312.pyc\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_json.py\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_json_s.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_lookup_transform.py\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_lookup_transform_s.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_wait.py\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces/srv/_wait_s.c\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/PKG-INFO\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/SOURCES.txt\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/dependency_links.txt\npython/ros/install/kinex_interfaces/lib/python3.12/site-packages/kinex_interfaces-1.1.0-py3.12.egg-info/top_level.txt\npython/ros/install/kinex_interfaces/share/\npython/ros/install/kinex_interfaces/share/ament_index/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/package_run_dependencies/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/package_run_dependencies/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/packages/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/packages/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/parent_prefix_path/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/parent_prefix_path/kinex_interfaces\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/rosidl_interfaces/\npython/ros/install/kinex_interfaces/share/ament_index/resource_index/rosidl_interfaces/kinex_interfaces\npython/ros/install/kinex_interfaces/share/colcon-core/\npython/ros/install/kinex_interfaces/share/colcon-core/packages/\npython/ros/install/kinex_interfaces/share/colcon-core/packages/kinex_interfaces\npython/ros/install/kinex_interfaces/share/kinex_interfaces/\npython/ros/install/kinex_interfaces/share/kinex_interfaces/local_setup.bash\npython/ros/install/kinex_interfaces/share/kinex_interfaces/local_setup.dsv\npython/ros/install/kinex_interfaces/share/kinex_interfaces/local_setup.sh\npython/ros/install/kinex_interfaces/share/kinex_interfaces/local_setup.zsh\npython/ros/install/kinex_interfaces/share/kinex_interfaces/package.dsv\npython/ros/install/kinex_interfaces/share/kinex_interfaces/package.ps1\npython/ros/install/kinex_interfaces/share/kinex_interfaces/package.sh\npython/ros/install/kinex_interfaces/share/kinex_interfaces/package.xml\npython/ros/install/kinex_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results limit reached. Use limit=320 for more, or refine pattern]"
+ }
+ ]
+ },
+ {
+ "id": "312a0fda",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:30.011Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "bash",
+ "input": {
+ "command": "ls -la .kinex/devices; ls -la .kinex/tools .kinex/skills .kinex/memos",
+ "timeout": null
+ },
+ "call_id": "call_c9d4800136cc4be1a80e7f4eec97898d|fc_0b5218887c37459e016ae26d356528819f85f584a5574f324d"
+ }
+ ]
+ },
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+ "id": "fe633654",
+ "role": "toolResult",
+ "tool": "bash",
+ "timestamp": "2026-10-28T21:46:30.031Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "total 44\ndrwxr-xr-x 11 agent agent 4096 Oct 28 21:45 .\ndrwxr-xr-x 1 agent agent 4096 Oct 28 21:46 ..\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 head_camera\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 left_arm\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 left_camera\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 left_gripper\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:45 policy\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 right_arm\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 right_camera\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 right_gripper\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:14 world\n.kinex/memos:\ntotal 8\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:17 .\ndrwxr-xr-x 1 agent agent 4096 Oct 28 21:46 ..\n\n.kinex/skills:\ntotal 8\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:17 .\ndrwxr-xr-x 1 agent agent 4096 Oct 28 21:46 ..\n\n.kinex/tools:\ntotal 8\ndrwxr-xr-x 2 agent agent 4096 Oct 28 21:17 .\ndrwxr-xr-x 1 agent agent 4096 Oct 28 21:46 ..\n"
+ }
+ ]
+ },
+ {
+ "id": "7198fef0",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:46:35.380Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/workspace.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_6705f0d2e2394a30bb581ea44d385871|fc_0b5218887c37459e016ae26d3831c4819fa634b638d90788be"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_arm/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_e58691f7e16147eab395daf95a28a0c9|fc_0b5218887c37459e016ae26d3b4940819fae10e30592a8b3f2"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/right_arm/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_60f5baa90b4a45b085b550c6542a738b|fc_0b5218887c37459e016ae26d3b4944819f8262615e431e6507"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/left_gripper/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_12bf679f95494399bb47080d1beebdc7|fc_0b5218887c37459e016ae26d3b4944819fae385c7f7afc6f23"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/right_gripper/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_88760df5480447ddb8fcb3567c44240e|fc_0b5218887c37459e016ae26d3b4944819f9deac9b84c192193"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/world/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_03371d20a1964430b350f091a1a0b420|fc_0b5218887c37459e016ae26d3b4944819fa8b82bd928c268a3"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/head_camera/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_b9931bd73ee64dbc89d5daad25d34ad8|fc_0b5218887c37459e016ae26d3b4944819fa63c5ea7c8a37119"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/policy/profile.yaml",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_dc800044efb24048a2da7659cbdf024d|fc_0b5218887c37459e016ae26d3b4944819f8b44321c1a8b9031"
+ }
+ ]
+ },
+ {
+ "id": "9674672c",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:46:35.390Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "identity:\n id: robotwin-aloha-agilex\n name: RoboTwin ALOHA AgileX\n kind: arm\n model: ALOHA AgileX (dual ARX5)\n source: user\ndevices:\n source: user\nsafety:\n source: user\n max_joint_velocity: null\n max_cartesian_velocity: null\n keep_out_zones: []\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\n"
+ }
+ ]
+ },
+ {
+ "id": "bbec448d",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:46:35.390Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "name: left_arm\nruntime:\n domain_id: 83\n nodes:\n - entry: links.py\n factory: create\n ready_timeout_s: 30\noperations:\n joint_state:\n description: Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4,\n fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition\n stamp; do not infer motion completion from a sent command.\n transport: topic\n direction: output\n endpoint: /left_arm/joint_state\n type: sensor_msgs/msg/JointState\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n joint_target:\n description: Joint trajectory over all 6 arm joints in radians, timed from receipt\n by strictly increasing time_from_start and finishing within 120 seconds; velocities,\n accelerations and effort must be empty. A zero header stamp selects now; a nonzero\n stamp must not start in the past. Points are absolute native joint positions,\n linearly interpolated at the native control period. Replacement clears pending\n references; invalid trajectories are ignored, so verify measured joint_state.\n transport: topic\n direction: input\n endpoint: /left_arm/joint_target\n type: trajectory_msgs/msg/JointTrajectory\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n stop:\n description: Stop arm motion and hold the measured posture.\n transport: service\n direction: input\n endpoint: /left_arm/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: joint\ndescription: ARX5 six-joint left arm of the RoboTwin ALOHA AgileX. Geometry is the\n sibling arm.urdf with flange (fl_link6) as the tip link; measured links are on TF\n as left_arm//base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 8, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 7, in main\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/__init__.py\\\", line 98, in finish\\n result = plain(result)\\n ^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 12, in plain\\n return {key: plain(item) for key, item in value.items()}\\n ^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 14, in plain\\n return [plain(item) for item in value]\\n ^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 19, in plain\\n raise TypeError(\\\"images are not data; return them with finish(file=helpers.save_image(image))\\\")\\nTypeError: images are not data; return them with finish(file=helpers.save_image(image))\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "18061e3f",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:52:45.319Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
+ "offset": 1,
+ "limit": 150
+ },
+ "call_id": "call_bf701aaf00e144f99c654465d20fa7d1|fc_0b5218887c37459e016ae26eace220819fa5e3bf1ee2b54732"
+ }
+ ]
+ },
+ {
+ "id": "af46c091",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:52:45.323Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "3d43df48",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:52:53.367Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure shoe surface coordinates",
+ "python": "import asyncio,numpy as np\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n poses={s:await helpers.relative_pose(io,{'frame':s+'_gripper:tcp'},{'frame':'world:base'}) for s in ['left','right']}\n points={}\n for cam,pixels in [('head_camera',[(315,160),(175,200),(175,170)]),('right_camera',[(270,100),(270,180),(250,40)])]:\n im,dep=await helpers.camera_frame(io,cam); a=helpers.image_array(dep)\n for u,v in pixels:\n z=float(a[v,u])*.001\n p=[(u-159.5)*z/358.64218,(v-119.5)*z/358.64218,z,0,0,0,1]\n points[f'{cam}:{u},{v}']=await helpers.transform_pose(io,p,cam+'/base','world/base',im.header.stamp)\n finish({'poses':poses,'points':points})\nasyncio.run(main())"
+ },
+ "call_id": "call_29f165f826c5442a94f4599d8b7313e2|fc_0b5218887c37459e016ae26eb18030819f91651be63562500d"
+ }
+ ]
+ },
+ {
+ "id": "212cfb7d",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:52:55.537Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224374.798465320] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"poses\": {\"left\":{\"pose\":[-0.04576036873904488,-0.1518396196357057,0.8105108280162003,-0.06397159671261682,0.6655944712893721,0.1116262315077717,0.735140271677748],\"timestamp\":10.8},\"right\":{\"pose\":[0.3158530877393279,-0.0837637020994616,0.8411548580346625,0.5416649392500444,-0.4740655883365559,-0.5247640136212739,-0.45440471118866305],\"timestamp\":10.8}},\n \"points\": {\"head_camera:315,160\":[0.3105280301800081,-0.047369169413844336,0.6644731372869409,-0.9486832972651138,0,0,0.3162277683730379],\"head_camera:175,200\":[0.0007164514080967438,-0.13173156963338484,0.6424513366211899,-0.9486832972651138,0,0,0.3162277683730379],\"head_camera:175,170\":[0.0025748496589661773,-0.06011766118549816,0.6424117683126856,-0.9486832972651138,0,0,0.3162277683730379],\"right_camera:270,100\":[0.3420385028964361,-0.0843225323833221,0.7120579827021101,0.9739351910892778,0.0678785002499696,0.012351526088398351,0.21607913495984335],\"right_camera:270,180\":[0.3485558820624562,-0.12394106388230323,0.7274574502446138,0.9739351910892778,0.0678785002499696,0.012351526088398351,0.21607913495984335],\"right_camera:250,40\":[0.3286115784257454,-0.057996926368941285,0.6946765327046098,0.9739351910892778,0.0678785002499696,0.012351526088398351,0.21607913495984335]}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "23c278ae",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:53:11.085Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Repositioning camera toward shoe**\n\n**Preparing gripper alignment**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26ebb325c819f93be8640125cd612\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Repositioning camera toward shoe**\"},{\"type\":\"summary_text\",\"text\":\"**Preparing gripper alignment**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m7GYPZR4v3IYhof-RwlTLodWcW58RDWElEaRX2djJj9XGxw-GP7GeSRTZ7qbyYtPxLbWrOu4JUqanQ7Lf_hMufODJdWZ9u6BL3w50Crn57Br_MQq9gOYh7D9Xevc3sBthTckoyVgpWhBgXzqWFld7iQaAt5uthCBocb0aHQM9Qw53V4APxCCfhCZUQWoGlhMJxqZpTNjZXp16LXDig3_9JR27QFj56YfSuHv9rftxdoaFKuy9zPLCbyRVFuTx-zeKPTWzx0k2teDGv1QDiJkW_X-RagxyFuvQDzP4NG4WE6UbIbmPA3krfq-GYRy6CBfyvAvxYTYwCkR1k3uEEW8jviAlUzHOh-029q6vkDgBHtBC1k74tanw5RKV5qVWAqB3Ye4OXJPFHiHNdZ2eKC0Fp47fm1EZJNr5S0N2WFZOD-vor1c35K-lBHFbQrt6LNYIxSb9o3Vt6lEyXLNqEtbI5P7ionA_kjiBJDfVAllMIcfJeLeROho4KmDdHdBgwxFT6xBh4xnJBXE4Enn8LjJPlqYEpboGLcY-ebj6x5vUUmhiynzKdCh6fdDiWnrqBn4uNeqVl9yfkwMtZR34Lk8g-7yzpLAYAMMT9a6Rs8INyun-II7xee-m9zpdHqy9v15lQ64djiAKJsF3FZnRe2UhM5Lwm_n4cQ99PPwEL6Poy0CKVBg4PRawxWRSeNjAlBFryZvRCPfoMuQ1lcwsvVWw53n_QljTXAKtW8hcFQTw1BFc3anytHEMygOsGG0iSfn6QB1IjMRUOn9gGaQsFrpwAbM7o0VJhfS7iaPhU1ky_Y-8eb5bDZ9upPruXRyWHnRAyKFf1qvlBnDEoak_Svtm752XEmlkwF0G9wSVwjJTyKaCsA2KDUTaoXE6FvqU_MLuImSJt5ZzPu-GdKnPYIm35jg61QQyUZMJ7LuaNFJXu5MLiG04RgjNxTi-Gldz6qOGlAtvqLq88bOigw-hqvK61S5JlMZhSQI3U_PJjz6Bpyf1qIOh5IODiU0CA4dFkeN5wXTpPIASMPnZ-KxmGu-x9i6VRH4QuBbVSYWwOtTnUe_rn-rrsUEgVbqX0sKa-Pnm6mnJwSMQRof7ASQVEL0jEI2MxGSBrB94rOw-ku27HXD3QRMvdtBJ1lkGZz2vRJUUduUuwp-f8RhOVaD-odfyU3zuTJz5viYn6VUo0VScrEpTf9G5d_2r-SoMUin3hJzH-elRKRDGhgEQs_PfskUKrVCcxsTYSNkisAXIrwex1R9QUOLVXjb7HLKjswoLOQaUH4qUjS-tV71vcFbJsCr-YNehyXOOLZVHdpacCRedo_rsdlyBEcJlFF65eVIknjs8b8jbGQ-ANjfGYLndt0xLjnh91wt0niJzOSwgNuw3xd8nXvbGY0IRUE8STrxCeH5UdQnN_FbAIO24ZDzP2DIQAc9K2UhaT0FAqBF8uecsdRcfa3qMwRnCf_u7PIq-tmS4100JGtRQhLh32eml3ud4i_IgH2TMZUeBz91kc5N6kygFTmAkYedUS_GmQ2mdbm-1Zti9RQ4cQR7BBVmq0xoGCKjMrazN1eGJt0N74dnCeOVG9YfjFmJ7iPZSlR1h97A-wG8VoE80Ysvpz4jHnwKvI8jZ4RnTnCVDQUP-guYIpAF1TQGDRWjWutEJ2Xl3VAOuf1Lz3uQCVuAJ5jkz1BgADw355yY8WFotftAPtLL5F-Rz2zXacfJkwP56mSXHxcGX6C9qP0Igwwj65EVXIn5Rv2MhWUJ_R5VKB30fympSA_ObCL7MZxLDgwfcuwRYC8goa7RBUbbJ7cNx6NtKVcAM2JFWvJVh9keJZx0X4tKXjjxPOR6YdetgPOp177yIjNpWkzQfjf_ryvEpUvfu777NuAgYTEZUUd2VDW9DJwqGFx1jYPS3I4n6eaWqbHhBledSOIOGWQEId56jwgAyJv0m1SS2YyOqGiaTwEo7cp8eMly-URj_F37LzH44OdxHAhaCfBy5QGTuDLM56sWoS9WvL1B6VeCs_Rf5_Ohzzm1m3FcxHnn9i0YHIKFYNiB8r2N-LkuG6sybXiqCAX6uBzkMiRdoHbuYMpeMxn7YD39AD9ujx-8ND6XiNYn9SV9VxWK3e_d7SJ3OERUEychiHa4f7iK278BjIkxQ_iwVByPm4-rwsmO-10GX2XbO42JVBlfPaNaQ38yZ8osC8zUPXiKeVM7dSmJcDfF2KQTekBzYX70VdnHXzXP8h6fmMmusRuy7TyEmDt_h9V7x2bsBgYk5S0pbujGfHMqZe83ClIZBntq0d9qrutau9VbnNxHok9Ois2U9I-Lbk2jcPaibwfzdZ0gu_7WYXwe_tX50dpi6pe-IH_OCxOTD5CRltG0Cx-X6zCc1GbxZB9N0ARbW0rX6d-tbjceoEiR3WHTnp4IAJsThToBc9yEclEUR3p3ZRhFD-xYE_aQcRRS9vQVl1zPPNoTgl4j7AXCONC8ChcnkhMJ5mH3PVVE4i_yySOhsU3BAG69i18MlWtyuPkkDK3iYHDUCpLREks-vqOgEiNi-PPdyzQbyGS0gVzT2kk14_qoRSzkdv5zgErSyVfiSFTlqvsDdqbThMUKrE_xJ80tPh12wcM5LLr9q_9w-4LQ1GgXUj3AecOVPcnPUo-uJxUvMpIqgu2mgL5PANkA5QDjFxifFWs-jWax2V1XTGa-B7fPiXOSBYOguaIyuIoQqtPeVcLR2m4FMbmDYpBpMrgW35VTo50IQGnRuD93aA1FVeEB-m_pAYxftHwzG_peuYDbQIxJ2NLqa9n4fKUYMXdeNXr8bGJxq4R3axmmUERPdA4gLeX_DWdbcg5sT309fmUxXZPtxhKdKb2PURxE1yuwuMOaIJJLe2GDAeeJfX9d4pvv3xVqHMGzcJ-iQo4PcOwiffYBazkllBoVrqelJS76WPAhf_KF8Nyz3gApS7SLrysaIZ-OVbjFzZUSApnDHUe3TzLqddINvjJkwpFZ9ZmPgJz0hoilgfIN5KZ9npF_z3EFPLVNFEVfo2-lI3rBJk2D3JMBLXCOQzlVjyEVKexq8vXQUkVcs3SmIrvR1xmAMzxFYM8mujh157PyMajM73UDL5WtG2kY4bzjWP1YX2VNXxoCKhosvqECNpYvD-FJEnCCzo7ZHbh02SnjP4PAVB4BPYfkWCl1Un5n7XmGxHWt_0VUYwLNwt9NQ6Sl-sx4gVj87V3DG0jrspRVqDxjObEboovkRlgAv61meNmGJjQ9z5a2ZLXC2NkH00TH5qEY9YadOLgOZ28_12jt-ZdSoLc16aLhOQvSn4rldyQz6zOnELmLf5b6-Z-AqX7N3stvbarFtXzW5qzsBCOSvT6xO2Hx64sokB1AQUyBh7wS4c5KgVf8cfs-j-d-M9fOkIroS9XhHvkIB49iqbiiT7nFcaY1bGnPmFkpii_MtU63PDe3K4_jlsI9Izsc1vYSYiXB1iXsK8v0Dehm57becT9TiLAM1S6TAtS7b82BwRm_0WjkMUIESDnyo7OvqANDFXjxTxLVqN8d36MEUmxOOZUW0A7RYpCA568W5ps40O45nX8tha7QLqC64H1WtYdwdS4Ap7-b37zl-GPBCPe33VkXyAxh4ZbuN-z1DpWYbfdzM256RmFpQcxqRPNY6fndA5GPtp2VrGs_gHJb05WwNTW9u3IJrnwR8fMuwPBKXHUAo-9b6iW6P_oRMzqLpExRbGLxGxKjU4JhtAeaoV3SA1w70AK8EZgmVcF61Q6VRh3B7mgNyH203Sc1CBAtydgVKYPLdCtDnOEZo-MhVVpmmjnsRhuvISUXn8O8W2l3kmrGbVycDSDJ21DghOb2re9h5GTVt-JIdNN\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": ".kinex/devices/right_gripper/gripper.urdf",
+ "offset": 1,
+ "limit": 180
+ },
+ "call_id": "call_69cb68b39b0b434fb5973109b24a4381|fc_0b5218887c37459e016ae26ec31f00819fa910bf9279b5ea66"
+ }
+ ]
+ },
+ {
+ "id": "48632ce5",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T21:53:11.087Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n"
+ }
+ ]
+ },
+ {
+ "id": "e6e6cdab",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:53:24.544Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Estimating shoe pose**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26eca22e0819f9f9b0c2dc1336c92\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Estimating shoe pose**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m7NnOdA6qF5uXqLmc1t9dJTjxHhZdzD6cO_FO5VJQSXHQMBgovRHMAPKjUDI34AN28j8Ck7h2WBTeR58PqQRYC5xrxtswGLyryvo0FWazdhZTlgEaK4aQoXevpIzVKdeGV1aW8X1ribGDijcWcYKNoJsrQ7nljcS5UZYeGFTCSW1TAguF1CisH6rEAN3ynRIYlAubeu-d6zZxH3oLM4sgsGAf3FihQXIf06yfiq2_wLC3MEPDyJjqBBTvNOWRgmQ7r_h1GHR0fEZCJFMQXurzV6ZWt_FtdxFfiNyNAGCDTxdHnA3AxZ6EZA73D1LYnXNzDvpmJJs08QgLsSgXdxupVx2HkcQkAcZHHNh3OdhX2I_TfJ19h5kUsWgb96U8OGpHtf6L0hY0Jbu-CDFVB85C3_-B9HS3tLhiWN89HIjt99wPgg_O8lQ54gk5hu2cUhaSlU1EB-u8KuNY5yUKjkob3AAsOJidurSz1FxvbDEAhVaw8uibum8HlYmo-afsAYsgOSMHXtPoKIialRN5AHIhVW1l5P4OIMX0hFkxZKfdr1hLQ_MmUK3QJwVIFwEUqr4Al2xzDviWOhP65py5hrY8_1Bz2yp1gL2xSVhAk17VLZ18bt0VXfoeFTtdkKm7K9tGhLSTTc01LG7X63uU87llWfQccoO1SfOcGwLlPEhkJRqrd-2mJnOeILzPZJmWkoBK3D2tieXltXm5L3uDG1xrUJ_YxHiE17TemNbfCG3TiqWm1Oq4I-lncMH16FtY6S3opmeY6Lyhc26miUjMlkkzF47QvVsuKzyhy21pDl6uaj_b5Co2Q1f7fxyFRr9sqLI8FWl8vzbgdF5DpFgkVB0W2C5iL4LEpafx0ghJxJ06tzoztdTzc1D8Pm_j4EKOLJr7WYUWjdIcbQqX_liH6xsMdhIBwqx8a7Fd2TRMl20l5v-6uMQl84SXwxp3EX1AIbIpuVP4OoVfoh8yoOb4ltVy1kBBtKBVFyQT5xR-FW2pWbM1bgF0nK4f8YfrA3JJynrP-z_j_o96Ugf9CnWkBOIO_wcxsb85-KD-G0dgcGAEytCZ_ZWJJYGjL_rv5aWTu2NfLFRc8BmLW_ZW5XcsYOFucgYnmh9Zga5bAEWFVUx8algJQMoioDgrl2ZM2urP5rfd2EZYhE6XMpQo0tS9l5FgcuNIoMR9716eTq78OKKaJ_AURwU0sEglJyo7oh9XROqZqOKPKRAqQJkTE5JPmcY7cfT86uqk3c-FrPkFkvIse3SWolKTQlVF5VhL4Zs_KvncC1NJ3bBjWR6r4YuAg9IvKMCj7haxjKbg62wUutvHV-t-I6-rbqCBPiVZKTbx_uxZ7yEZON2tu7XRatS8zW0-TWhIoK3VTUgW77Uef_vV40n-HyStRWaJINifnllJrYJJAnLHp-ALuHoWiMWrfx3VLz9irR_9HJtydif8C2vwuBGDfUN0sW7AC3bIo2jNWnbcF9EQxQO-S_YQ1WsvJt56TfkZSJnrKMOqk-4IGKb70K3W0H8zfhTItUeEvP7sq8hb843QKJWtzVUjyT4icqYxliz-T83tTPXV_ZuYWoMSKo5j6Q7Ij3Ks7uZFcEnX1iKc4uFQg2eNXjV_04fYlcAkfnLl9LmKV0nR3wAnUFkw0W17cT0AQd_CFyixkUXJNPqxwLpD_VvwizeDabdkD_It9I-V0Sk-UIbzif4pcNT5wIPTJdooV78OcxM0ddPW05OlwJqQI6LN9UVUkop-ZFRae1du8KrSfviktGHUoKBPbtlQGvX8P1AxcrAw2XC2K1rmUlyZyejqakHnxjIOe1fvublMlUxLqVHUDq-hPa3oncIXLHn4zlUxp4COoTPRrHD4UAPC31ghXOUndkAXfJoM2suBCa0VTX6XWqMCdEz_xKpEz7eYLFrp9CGKwit4qpRsxQCff4Z2GGXtfcLyV0B1T6-QgNUtx8fKPZPVUgXo81D-FK-R4OHe2uUyvbXrU-FK13sNglpdXB4qXVq7oP7W1vefShZaqbtOXNPkDEi4y_vC-t8M8sZQYghHC1fgW8hQCsIZMr0cJPQ-WOjgpQX9L91ryhvkqHkXENEBgY_5DOjuc=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/tools/cartesian_segment.py",
+ "content": "\"\"\"Bounded world-TCP moves using calibrated transforms and measured seeds.\"\"\"\nimport asyncio\nfrom kinex import args, communication, helpers, finish\nfrom kinex.communication import duration\n\nasync def read(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts=args(); seconds=opts.get('duration_s',1.0)\n async with communication() as io:\n commands=[]\n for side,goal in opts.get('goals',{}).items():\n arm=side+'_arm'; model=helpers.joint_model(arm)\n state=await read(io,arm+'.joint_state'); q=list(state.position)\n if 'joints' in goal: end=goal['joints']\n else:\n current=await helpers.transform_pose(io,model.fk(q),arm+'/base','world/base')\n tcp=await helpers.relative_pose(io,{'frame':side+'_gripper:tcp'},{'frame':'world:base'})\n target=goal.get('pose',tcp['pose']).copy()\n if 'delta' in goal:\n target[:3]=[a+b for a,b in zip(target[:3],goal['delta'])]\n # TCP is 0.12 m along flange +x.\n from scipy.spatial.transform import Rotation\n off=Rotation.from_quat(target[3:]).apply([.12,0,0])\n target[:3]=[a-b for a,b in zip(target[:3],off)]\n local=await helpers.transform_pose(io,target,'world/base',arm+'/base')\n end=model.ik(local,q)\n commands.append((arm+'.joint_target',{'joint_names':model.names,'points':[\n {'positions':q,'time_from_start':duration(.04)},\n {'positions':end,'time_from_start':duration(seconds)}]}))\n for side,value in opts.get('grips',{}).items():\n commands.append((side+'_gripper.target',{'data':value}))\n await asyncio.gather(*(io.publish(op,payload) for op,payload in commands))\n await io.request('world.wait',duration_s=seconds)\n states={d:list((await read(io,d+'.joint_state')).position) for d in ['left_arm','left_gripper','right_arm','right_gripper']}\n paths=[helpers.save_image(await read(io,c+'.image')) for c in opts.get('cameras',['head_camera'])]\n finish({'measured':states},file=paths)\n\nasyncio.run(main())\n"
+ },
+ "call_id": "call_f214bab6552e4fac894e29af38414f0d|fc_0b5218887c37459e016ae26ecdef10819f94cee84862a9979c"
+ }
+ ]
+ },
+ {
+ "id": "d7ca3c2f",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T21:53:24.547Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to .kinex/tools/cartesian_segment.py"
+ }
+ ]
+ },
+ {
+ "id": "bacd7459",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:53:30.996Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "clear arms and inspect displaced shoes",
+ "args": {
+ "goals": {
+ "right": {
+ "delta": [
+ 0,
+ 0,
+ 0.2
+ ]
+ },
+ "left": {
+ "joints": [
+ -0.23377,
+ 2.10649,
+ 1.59874,
+ -1.06015,
+ -0.01728,
+ -0.65544
+ ]
+ }
+ },
+ "grips": {
+ "left": 1,
+ "right": 1
+ },
+ "duration_s": 1,
+ "cameras": [
+ "head_camera",
+ "right_camera"
+ ]
+ }
+ },
+ "call_id": "call_1dda0b3177e74e1891be115c85009f3c|fc_0b5218887c37459e016ae26ed8cfb0819f9b33fcffb6845c21"
+ }
+ ]
+ },
+ {
+ "id": "2335c3b2",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:53:39.781Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224412.462059980] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"measured\": {\"left_arm\":[-0.34138405323028564,2.0631067752838135,1.5276085138320923,-1.006088376045227,-0.01025577262043953,-0.4240250289440155],\"left_gripper\":[0.9917404543269764],\"right_arm\":[-0.0485311821103096,1.9509698152542114,2.119028091430664,-1.7710597515106201,0.0023190497886389494,-0.17672263085842133],\"right_gripper\":[0.984824080358852]},\n \"file\": [\"/tmp/kinex-observation-umnt4jud.png\",\"/tmp/kinex-observation-tqaq0u11.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/2335c3b2-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/2335c3b2-2.png"
+ }
+ ]
+ },
+ {
+ "id": "50af7cee",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:53:54.394Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Scanning foreground for shoe**",
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+ {
+ "type": "tool",
+ "name": "device",
+ "input": {
+ "deviceID": "left_camera",
+ "action": "image"
+ },
+ "call_id": "call_154911b1bf974eb3b49061fda0895957|fc_0b5218887c37459e016ae26ef10960819f8bd1d9979b84a4ab"
+ }
+ ]
+ },
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+ "id": "1202e4b6",
+ "role": "toolResult",
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+ "timestamp": "2026-10-28T21:53:54.552Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"deviceID\": \"left_camera\",\n \"timestamp\": 11.8,\n \"frame_id\": \"left_camera/base\",\n \"width\": 320,\n \"height\": 240,\n \"file\": \"/tmp/kinex-observation-r0rh5wg1.png\"\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/1202e4b6-1.png"
+ }
+ ]
+ },
+ {
+ "id": "056c2182",
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+ "tool": null,
+ "timestamp": "2026-10-28T21:54:05.543Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Preparing right shoe grasp**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26ef6def4819f95b1f104935bb9c2\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Preparing right shoe grasp**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m78W3kgANebXqgTrSps9uTzJN3Jzx8-4MWUNwBpfmPAZ8d-srlvmi_3hqxfjjFYiMqUmjwIyvsyDApp1QeMVtg41gz_J0g_UtHnrdiEHF-aBtL0O5KnmNg4rKaM7k0wQoJXDeMRP47Le3D617XCM2PmCSdjBRBBB1JfNvKGAA8RGWXTaDIGrDBUDEgOvkAekQ0CP-ZhtkLTHDUp9lPSj48Pse8YvBdAUL5J1vIhs2pJ3UjbmMnxOn7VB9PGi1jbuMknb1SqUR1RvYlpF420_IgtUw2MuZxNCCxS6tHWHmYeYh8q7s-legtM5VETDUUtL2s3jPkLVeQSNklElWqDftRwu1gUmAz57Xan8YHDts7BQYflN3o07kE7H4GNI1rYSV355eKmSFz9E31-tJwbIIRDtOewpe8iB0R5bfP4IqG7xCBVfcOniX-TyQrU5Ba73uuchXaE0jj3UTKzz3uh6RkvXtLkBZF7woJyBD2K-oI5uA1vF9OrYO14JSZYyW3xXjbu9lWEgvScIvpURm2Gb3tPm8X8Iha_i_WKk8G_WoIWbFf1_0feGnqycecnNt7kEzmJvvWBJzIsg4Ue0OxKEKBM-wBnBECsb_VMtuqQ7QIDF-0QuknwYAMSsHsUh-5hzEeSlAYsf3N3JtolO8opcS7Dc4pqQpo3UvsXoniRfzGENYuq6ZIGxI1SY5Iwr2ZEB8N-5H_O4fYPlyWu6y3bSeQwrGDUh-uvJxOe-jLc_c96gINRB125Y1GlCNf0w57GiUE-sQJAIstR-zyvbw4EVL9oOnuvmusQX_ltwhwW5YQdIXlahgf0ZYG-4fS2BQ-yuDt5-06Dh8Dn150Kx8pzgQRaUxM2BRX9NhwqaPl2LDqgSN9wNaw1Ioyb5TVJY-PrqnKp99bu-hVzBhg4zzu6MJUmyJES36b7oPTLOxNLfGoIdV4l13_yMJq_4HLgPeRlKBcFpZkcSXgdfDb9zwYbNPf4uNYAUVsto0TzsP2jHxUojPN6W_vtY-PjfhuCLw6UpZRM-xt7v6sv4l8b47B5fEVJntM8UrWgEvh3TervxrWHHm3NUlmwqyOS6qhXy45PIhS1_1VBIXlPGsY7xaHaGeRalDEtEDfriRRANNLEHoo_CiGterb0sEAuzwvX66O2X-7G04ghhWiOOBj5qmDf5YIdb1vDifO6JChfwjznfDrq8dTN0eZ02YoCCAILhHXF_y1ibtGx_udu6U2CwWYy79Rn81P94l6MiQQ95-hLV9qd423BCXNsh6XBhA3Fyit02qjvbZcfqrHEwLTtzZE5QAyXX3rXOm84WfOuffGKE5g-esPyhYq6K81yFAvs7304BEH3frfeNqkcuUsgX0cFbImv-EZ14UaA-wFPQJTT3bq6DNGFWutGu0naziCaN2vuA6UV4t36VwlUGCBAG0mvSbGUycoVuCL6VmlSjGcrSm-Kgjxx4yzruXdmgOybDTPZlEWs6s3BxiKQXO4AJNlgzz_ZGErUZzsQ-qL6o_Tslx9GWiXyNAPq9MyUpOjziUUsvDCjhB9lYAIfL1LjEhljTh3vJ3C96EoGC2-63POuRGatIlL62kPesbC9ihkeD12x1dULCOpuzk68-eqj0eTpS7BOcCO5dDMsIsHqFyudebOed2xkaaYVdCvJpdzM0Tevd0NJVg1y2ySN2bVSpnVEeHaczMGNGd9wSlmDh4VeDALSiiQ4IfSW96A520fIykhN_sOAD0PG0W3plnMEIkSsZmxP_H2kz0pv5f76K60yGFIxHyICYwkn8z4fpCcMIJpNUO9UVKdypq55-7qPbAxYByiSoouMJYqPPDG-ji36Mk4eN2ayvVT2QVzQqtohC7jHlIiPT5nN6to8jG8M_VN7HJihxJlxkCVlaApyRPeebGzhEetytwS8uUcFW5pHoBBUIryw1NIHUdm3AdZUR6DyCXwbTlYg7VzbNNbhuURlbm2_98W1OyCehOCeglrHB9ol7S4wplknv3mkEV2CQ-_SO0aUzlD-p7UIySQ78irmgVYUZPPIOX_pYvr0hnwZZIUFwVbkqsorn6mjTMiyjzopOEJkYchCaCO3Uk8CuWWaW6PHEunC9ZZvFynpaeOcIy5vN4MzWoKpzbk3lMi8y8fAEtEu9HyOnOUc6sJb8dpBZ5Hvvb-W2S_owyweQzxrdZfYPaTOZYSRpW8hfPubRwdqjlg_nKzdQMBXYXcTdr6bPKUNSUCHJmPxQe9vXRvRBVL7HrLRX-AmHK2gOaOmg5U1KozyTQ-d8khGA80f3qeG2wtQSpm8P1C5WS0PN28KWQC_H76Eiry456w1Y0P2drsQ8ZYsRNfIkcWHeWOJVw1OUwlYaTOWiwz0FbznXGXmalz5SbCWYItAMsf0NWTbs4ZR2xjPZPJ5gdFxK45XO8P6Wa5HB0KqqUR63DRkELaoIW4dpTBS\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure right shoe grasp and box geometry",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,d=await helpers.camera_frame(io,'right_camera'); a=helpers.image_array(d); pts={}\n for u,v in [(220,25),(220,65),(220,130)]:\n z=float(a[v,u])*.001\n pts[str((u,v))]=await helpers.transform_pose(io,[(u-159.5)*z/358.64218,(v-119.5)*z/358.64218,z,0,0,0,1],'right_camera/base','world/base',im.header.stamp)\n poses={s:(await helpers.relative_pose(io,{'frame':s+'_gripper:tcp'},{'frame':'world:base'}))['pose'] for s in ['left','right']}\n finish({'points':pts,'tcp':poses})\nasyncio.run(main())"
+ },
+ "call_id": "call_6aa81a8a753445fa80dbc6b1887899b6|fc_0b5218887c37459e016ae26efab2b0819fa0c67090db3118df"
+ }
+ ]
+ },
+ {
+ "id": "fed2c8ad",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:54:07.704Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224446.993372814] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"points\": {\"(220, 25)\":[0.33912656027719457,-0.06270945464371132,0.699152728908267,0.9742144348625146,0.07054615050136454,0.01317976945776365,0.2139059822258145],\"(220, 65)\":[0.34366378336074566,-0.0970220567701838,0.7184123702623861,0.9742144348625146,0.07054615050136454,0.01317976945776365,0.2139059822258145],\"(220, 130)\":[0.369180866644661,-0.185229663768754,0.6765957202615971,0.9742144348625146,0.07054615050136454,0.01317976945776365,0.2139059822258145]},\n \"tcp\": {\"left\":[-0.1764191407332653,-0.039818355705945996,0.8221104464598411,-0.5187487037504172,0.46380859131529467,0.5349435100330139,0.4791834868324896],\"right\":[0.3142798555779541,-0.07013205333858658,1.0078345324518556,0.5420236400350569,-0.471363514483094,-0.5270262727561408,-0.45416970251444916]}\n }\n}"
+ }
+ ]
+ },
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+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:54:16.362Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking right-shoe grip height**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26f024910819fb337fbc95e31b89d\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking right-shoe grip height**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m8I62EC1vo5Vnm7XUqNtifD0uHPcNsoHujd4BPxpW9HvL41t15oThKYdZKFZzHvmj0g9WjC6aqBMJe8c-WE468ImkanJYLi3h_AfASkU8qc2VN_JEgul3C7x3SxUTGyDtQmA5Cd0STvIWwWc6bU7NsV3LpkOwGlO4l2mplwoGRcNM6Ko25lAZAVum1icuoiRGgnSW34B6jk3I3ioxZ9ehd2u754xHbEulY2LL0qJYdSZ90AKc8z85JjnljkvnAtRImTsoTHMGgWnqsWEQzIxEvXNQgZHGfkwJcPlQVTe8EbnLXaO9Pglfpld05aFm-_kYdJVl-fz7SyovvkqUFyPnn6E84N2L37hh3cGZCkgH4r5cjQHRanIDnvoriVyBAmQy2Wn3Veyq8fEtIvAKnj7KcNhFFv576Z55IBUJKKXYyWoss5eqYlDFlSvG0ypecngiPz8tbvqAqovOssmKoWeMTB-wJprqUyZCm2xff2lqCc7uk6WyyAc0Hc9OHioNdfaic2bLf-8Eh1FOaKpAI82lmHf4MNuOUtgaaV5uXanWuRJWprPqL-T3FS9S8cer_vhaug0KibORkpY0KxJ3BIAui-6NWMPKHSzYiyTw73R3At6U0mNL8LRBLZMyFTXzwC6ThOqafucrs0BZNd7G46CAVOq28a3lNJdMhUjxbwRyKw-kzKkWVj9hWmafRSkuiMuk_KBZJsv6UCH2O3FjbUticw5I54GlWsKSbWOvhULonlyWKddGiEghVA2m-DYpazrTqTdy2c8NYyl8dM8ZTy5RNCaB6-9xsTKKP7q3F8w8PyAVwBN_XJfNdZzDPIEzaOwFBicACaajLgIbyoVBDJdISbWEpvRCf7ANyAECdwUYsoqoubwtzEojrNSnsisEwYo6DNM8_BaE17YnOz-A7KL5BvcrQZII-mX1R0xr8GSDErYz8Ui2ZFJhWkg87UT_jKrJlgQ5WQgCOHUjYYDfyGlR2Ua_O1Pqptyx4vbMhnwK3Vm4EV2RuHDgQ8zpmkwHIpQQV664j4UXdrAI27yHE9noE1XUZSKS_vgWHVumhwfAVD2altUBaQGbEVh2hE6ut3ttd8w6zHLsMWB9F8VnAxnaFS2EStHuDCMOOnVLS-kGeXJBcXPH3NMHnL17iHJacN8_hgnYo65WwE5TnCxwtqSYopKcMk5TrKObzkDW22OdpQE7ahMhMYYpL-WynEMKsG2tVscKvm1oPn0ywhknMRMEVGkP-lLOdnwVY-Dw-m3TLp7wF0G9-Arybh2Kfsj2EzCMcZaPKOv85rU07BfTc1L5I4BVY77-pvnvETD_hXRMOYVETItZ-JSUMPhf9mnKh7IP8ubZTTqidI71fYV1QeMsWpL8N1fkZxhyj5H-wcxCkNqvjX3x4Yt6usq5rfFp7VLa-jXWBnOYw01sWveap5kIEkVyEUR0uTsM4JO3RhQ6mpqYEXnO7u_pnEhM1d1Byo7idIWWhzDVAN1zBU8AUODY1TFDjn_-ShpxFz-odxo03lFol3EK_QYFZyPRAYLz1aJeAB8SMtBGhh7tC_0cKFqp_UkiIElh96uWMAw7K7zOMxcQgsOyRpYbtRh-kbPIcAQv2RAdaTrIjdWv2sUJptLFk-h-n9QEiYxxUFRoLf3DAVUQUDT66b3rg3HMpVBxXL4Se5jkWal8GYx_K6LP4cfDAKpkwPwWbUNXE0iUHGlvwDN_YJjGOKFF88cu0Vmn6nRUBmXDDRpWzDJR07clKHwKt0IOpi5dGEfEhRHJQRIWfM7UTavpUHv6JCFP7-8jJncSzHysvjZEU-kIPY5bquydlzVQeXk8ql9PpI_1sVdyXFRIVSHFpIlMp4dNx3aixvgnMac7Jcb2fSESoyTAVYlZAt68gKfQhQL1TymCgLXpS-XswRYLKqmfGUJLItVCEjgPDu_qrEfdW-Jc4Dw5p87TcBMOUGdKBbI67aYHQcKc8JczMPsJJh1l09sHm1shEMos8wSkgZFX6iLBjGN13gNcuERw7hukiT7bwI4BSfWXTqw9sUT_TSOgHV3jBbaSYK_zM5V5SlNW4WPJERBjh3OF5uvtjPUjVhv5FZjVYseKMF13L-zdtAv-UoWfcSS6n80GQjMugzsCVFiu1cAYB-k_nxZTI2JrudQbwVPcTNMEx_Y_yfp_vuo-AEIFzEe5ZJs0_m2u9sx6oBlNTKC6-xwtNkECWHnck4n4V4XdUSvcEMSC7XsXWaqe6K9wSsBHL3p4YJlJi-GlBjseHUmPhWN1g74SSmABQr09rBZ-dFdTrHxl_qvw9uXKHVNRBw9cz-gOdl6MCN2zDCwB-ZXKRN5phelsgkBoza_ZrxpQx81lvQu77kNxQmsg-MPQGvZiTfhIWX\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "derive proven grasp pose",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n q=[.1836943,2.449954,1.6583215,-.7642399,.0036793,.2217132]\n p=helpers.joint_model('right_arm').fk(q)\n from scipy.spatial.transform import Rotation as R\n p[:3]=(p[:3]+R.from_quat(p[3:]).apply([.12,0,0])).tolist()\n p=await helpers.transform_pose(io,p,'right_arm/base','world/base')\n finish(p)\nasyncio.run(main())"
+ },
+ "call_id": "call_45e0314da90347b3a18bf075d2d65a4b|fc_0b5218887c37459e016ae26f081b14819fa6d2a75446efd05d"
+ }
+ ]
+ },
+ {
+ "id": "d7d7d2b7",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:54:18.870Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224457.863503532] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n 0.21555207762772288,\n 0.019347892345493667,\n 0.6978195099953525,\n -0.4912582223427763,\n 0.5016447242922935,\n 0.5008975819995253,\n 0.5060825445689198\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "ef0b2d37",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:54:32.690Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Positioning for right shoe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26f0e60c0819fa0431e2b03c64f08\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Positioning for right shoe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m8YuC8Q0LafNSvEGa3Le1RbBO6z8tFnXlBqG_SVofP7RW9YFfzYFMg7KXuj90-f0yn4bJau24pLyK-wqEm670ihAgDo1K_eeZInDxAnGu69q4ms4v30iVlV6B-33IhKnisbaa-qH3XMcrhatM6e79uV9gto_lNuYG-kr4acdEVDHPZsVBTUZTlA892qZeejCVXaLGrX2e4E4MwFBA7f8uX8agxogGjAwFiwyZUW-jZy8XWvJD_fp5EWv2it8tiDwJ-6qZP8_43HPriih5v7qfLbc5uJzT8JSUE0hrMY3y2CL2ZSphsHOXOiK86SzUN3S712eRYe5UDwui_ou2sioqmNHoEYqrB-6HF_7qKBdwR7dOjLW7X4aF3s84qde6LFHpt3sFJn8i9iav_skRivuNCa-4PeOgc6oaadr2Ab9mzd48R402VJI6tFZ4Rx7uKTEZZvuuBygmfV76wdIqFZ3i5z2rrZ8OSFnOh8gtt3kJvQ4NOkbmrVR1YoRznHX5IbskpgS1ImYqWk9srC3W9lPYLKt5tVyBb_PoaE2dE_CjtObmbX9XIaGtQ44q-9D-7Kt0pPtXvJy4RnoEjNVY-GHnyRDQt1C2LFeFxoa932-haC_hOmU8By0nnuqr6DYUuIA4m2YGggZDI3LKxHZNYp4luyppMViT_kOLeMg0_W47woDBjj_UPNjFMiU21A-eligSLE4a_mV6QQ91_RrJYvwzTJCYbzvSlfoFYlvSiC0QoLKhg8KVeUSBA-RtHPu8vkiWCYrQc9GOq35FyiwbelnC1nlYgbpEOXqkDvCl5RHmU3MAlBpYV-ZPY1C05Ceme2g1PSq_9tc99SvJjx_-kkNE0kYWJBaP5PHbE2r22qiOzBuuwRh-UFT1B1rx1nfB7TSk2kXXq5jdQjVJdv-SB0XkueOEhJVtnS4diQKDsp_wKWS5-MRMAjtFkqBtWobl9GayDlEeBTnarokivNFTpA_0gO_4Wws2c3tfZlHbnMYBg94Z9Zl_o2cUHWFMSUdk2CAR7V9xtsJkxBscXoQR4zVWKhpMffADfVA-ntdaNI3A_62erPH-9s_UKeHr1kXlzReUE8vbse4WA2bun3p2BJ8ZouD0AyzzpiheVWKZvYLPBKZbskA3ixSyKGAYxgNoNKjSrEXDVTQRCycdP-H9W6I5S9014x1jZRRZcK0ls8s5Uz105uCrtQAwbU_ofaiQAVxwnQP3FLL5dMeo4YL0pX0D7ZJpdCbhI1DWsAS1Gmff2zp38AbV8haRAyKgs3A_UAwXpjxrYTeYXPk911w15Qmc6r2iuo5YWA94PIfOZp2-oIvdxpRN_dXZnElIBJQ6lOzlX0g1WrKiAjFIRfSwdU2dq6NLyiWrvnAeLBM5K3cGJZ4eQAyad0c6SHT4rC9vhGOM-Gkchs2Ws-mPEnldVvEoMOsPvyT54_1xevQMZrArpmQie8S9uOvj6R_1EMRL5PhHyphZrFcVgN7NKYYBqC--E_LE78RPRjAfOLY1G9tTEBzyFq-QrUEtJOwZdq3qwWkTAVz5-QZZoZaXjZ17fyTQf8JMTvWyew9CQOxnCS1srd5a_j_LS3prWPtSH8UuTI4Qf0JQ8z5IiTc9zWv2d5vr2zbMEGwurCepTnjuUcpzRzXJhTl1INNEQCz8J_oUf_5yV9koxF-_EURjKZxNTINVaeSaHEnnkfpdDPNsvszcriYM-1AHhRy8DoiWa4ChizH0hm3kR49CgnEwBVyakprXY_M8agB9Is8Bi94EurE0Mx-dBKYcBPU2bBuNy3ceElQNT4z-rgqFdRa6gUjbusHoAh8teGkEOsgDkTGopqMuNf9UQ08mXOqPnyqHB9BJI4o2KRdIk_LFIoJHoUu8kTctOrtvwm2rPJoFb6yDsUX2pmBZaLolfUmzv3dZuuZdrTIbh4HRJKuFmoU8Hg7tTbJHOPMF8rm9xYcwar8h-4A7LWH8zY3VFjLI1fyI9IFDkkcN8bVXAIiLyYN_kU6idO7PagZ8ttu66Oruqgjr8-JtDyuXb7OPtkS7b-6waLgf9LB9u_Rts196wHNQzaG-j4LN9pVkBf2Bs_DUwVLSAJMMv0i10K2ATLg_pfXg_KPhWlZT5LTqliAkg2khYbhFR1ImGh5oNatIgvqIZobbEKSz6bW_ErzavCjbdpqktYNc9ksPlsepDsU_F-edYPsnm6fLaTVVAqUtTPcm7029alxAUeDjKN0897B-9TD1QR3c6xF6RcYT-0528c2jRVMbN9EhPzmqfoglO9rVdW--cKd86TyUaR3QupnSQAQzDhUzxv4PhDjNub9PHDJMEarU1QxY-SRBTIEaTt6WvzoBPSXx7YFIqSXZEpVq-EFiVdPMET_Pa3w_bPc6lQFjZCqRAHW4WoQs6gO3oJwJuyzPWZ6T1FwEuaWBwdI7xT-8slrIXD0YeBEc80LKsP707nO15acm4Rd1K-B4aGQLL3cW47GTJkuERxkJ1S4rhjavRnS5DSXrtdYbZnZehrvM4tb4lQd52G1GoSVqQZ_t7M-DSFpu2dByk4FsdZFvZIgvR6TFqKnKPZSdEaC0FI4rE2a3PD2DKauvCixhKLzKOgBonBS5pNBkxLQHXjEpC_dL4ss9-oR03X8RO_vVOhE6vBqdXn98z9HaTzc5F8urLYdYhH2hFF01BpZwt1ov61jHQX0mnCiBHFPzMFfXHux7gjB3R6_y6hK4uZ3pR1m13-7T0lf-sRjzJHdhVTIfnWp1X8ve2imTQ-wf8868BSdG5Qf0lblAyvYeXkwmOLBYwkPlyimBpfbtz4jOJcfA_7YRwb-a7OtVq6e1kzB7EpgRvdrkONO0PvSObpuvlZoUL-Rkk6RWQwNIknywvmHhAMuJFcKXl4aiL2mHawsdPEy3yDhzjN61lgZUKh0OTEsiu6EHoPnc5R-Vg6ovxDBYRQ2FR3qyfvqTqdzs4rjlv3xdZ2kFRXQAmbzO-faJfnK7aOWh-Qs7rn1YFv5zOtxBSK066a-S2I0-yivUd2AbeEvgVDLV5hUPoHgf0vGc0cva24F24z0imsJJFLwZNpB5DJL4Ay3Zu4Elw7MEWRf7d3jVGCgfJfqRIzJJ16-63IZ39fl3JW5DDW2egPxY1nNo7mUCMDX75_-qYpPOzpgzke0VRO2_Y-BlmQHeyAKi6CTqyd6Q6GaaMoIzR55e_89iuGsZSAX7qnBCK1sDSQDMkVGpbPmbnTetdjbBPznMAxKOmshMQ2PcYKqb6mdifWx_g8C1CqyDIcsCxSFN0Vi6_nHvCgXNAX38V5zGe5yhYIKGGT9PICWotmLEaSl-O0-pdIY8RqA3Z1ySC44fR4GoJeE6BRs1qd6LQSLVmHjr7W0APHIloXnvCYD1ncxfrzFv_jSknG1uip5uBbPmp5voA2iO1beiIwUOPpFQ==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "align right grasp and survey near side",
+ "args": {
+ "goals": {
+ "right": {
+ "pose": [
+ 0.344,
+ -0.09,
+ 0.82,
+ -0.5,
+ 0.5,
+ 0.5,
+ 0.5
+ ]
+ },
+ "left": {
+ "pose": [
+ 0.12,
+ -0.28,
+ 0.98,
+ 0,
+ 0.70710678,
+ 0,
+ 0.70710678
+ ]
+ }
+ },
+ "grips": {
+ "left": 1,
+ "right": 1
+ },
+ "duration_s": 1.2,
+ "cameras": [
+ "left_camera",
+ "right_camera",
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_d443b9d4d47142c481adf1611a60a24e|fc_0b5218887c37459e016ae26f15b024819faa44c5f948ba02ae"
+ }
+ ]
+ },
+ {
+ "id": "9c169656",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:54:35.336Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224474.085063475] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"Traceback (most recent call last):\\n File \\\"\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 40, in script\\n runpy.run_path(file, run_name=\\\"__main__\\\")\\n File \\\"\\\", line 287, in run_path\\n File \\\"\\\", line 98, in _run_module_code\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/workspace/.kinex/tools/cartesian_segment.py\\\", line 41, in \\n asyncio.run(main())\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/tools/cartesian_segment.py\\\", line 29, in main\\n end=model.ik(local,q)\\n ^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/joints.py\\\", line 54, in ik\\n values.update(self.chain(link).ik(pose(target), values, {**DEFAULTS, **options}))\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/kinematics.py\\\", line 231, in ik\\n solved = search(self.joints, options, [target], [seed[joint[\\\"name\\\"]] for joint in self.joints],\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/kinematics.py\\\", line 156, in search\\n raise ValueError(\\nValueError: IK search exhausted (time budget); seeds_attempted=5, iterations=410, elapsed_ms=100.172, position_error_m=0.004569528253270413, rotation_error_rad=0.00035777856102559653\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "c2cf6866",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:54:41.260Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Reading solver defaults**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26f1e4e6c819fa8ca5e62e85431e1\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Reading solver defaults**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m8h6AZV3ntJcxSglBkCJLi8A2J7W3ckhJe89wPOafROb29zH27X_qBquLl4AAgGMR_dDUUx5CdA1MwHS4Z_LSTmK_i4YrJoLMqEJ8Bbn6gEgmUC0BCieLvhevNi0Cz3fgClIZeTSyKj-kCojg3-BVGVjn2GuE0PL8YS_8NkoembD4xauyhpIIELkE2fkAifeFGbOTOJMIvjGs7V_ustmJU9_Wk1d96iIQ4Mxsj21pR9h2Um_w00Tl9uyD5OpWcUDxXEbO68hYCWm4l70wHPGdY18lBEPGzzUBfhzjmuHBYIiAkO_1yYjrxoqqhZlYw7HGcswFSUeGi51hk_nsjAUB9ir3m7pir7lRjz6dIdd46Sun4BsHiX1vFzLXXfymtY9Pi90ZHB1IaxxhscoTiTEXVv7RHXFyL-NokaXBLADXZa-sMOaRd3vLXhTOjobhnhgBcYDVaMPu_9f8DEWZhznZ5zcuHY9p-zqBD4BqgL12z2R0vOkBkIY1wZjAmZyC88RVSLnRI80IvN3pC6KwBNvVR74K-sc1WAwdOdNsHGgJSIauJWrpASoo8N62CubWv4d3TlEOjvkW9x-bcvzPNG-tjlQDRQnCpXKvK7lyM_TkRrsuwvVx7U1bd2lDOpJh65PUiwdbTfQ18r45fZSJ8KqMedknp2G3_0q96LaUl9kmgs9W3krlMIYcP01R5yQfQlzzfE12gGoJHge18SXZ9gNc0uvpEELxlDBGL590Xdq01bsvZhV6KnO549aWiT9ounn8h7I5AYeJ5RDT8bpyBxd5qUAgzWQamPF-ew-JImZKuTj5hiK_Amm1ROM9QDJtjc5CS1by9VI5RueMim-Z4oabVZ0hGtKwIK50xhf2hvVK7P-sUPNjGoFDn6aaeKEgN4WD2rRofNje5mNDVYZAtCYXsGkP3I0dlwL3l1a9jRdZJr9jUfMiU1kBib7uBHneM5rSvp_txP6IjCPi6vm_tGBNohPCX5nugiqegVHA2wWGx3scc6qyTpAa3ZCBsZdkYqwKNIs6uhiwOcP3NQJFLX8ldaiJ2URd0FLrD0BjNkvnmTChdAUQ8MEGiLW_DrpcrPsP1QEcoujgMyrfgwuWfZeP35LSKJcYZqBjkY8QyYITeKzaTVFPqxj4ZIlaomLfTecceDUus77mm2wTiokhg91JAuvAH30qWQiYITynN951g7tWKPmvilxYJh2034vFKxxbvDz8Z5I05KT-oUF5dgtqY_RqlGKmcF_4Jwgn67NcYiHjllDxmUnx51cxeaV8fNgPR3pGtZ9ohKZgi3f2dsVOInrpdCfJlhoDDoYIzyX4a0R2W51YemEWpKIha4P671EcBJikD6CvPtv4mRqqhig_LxI1KzCtrx79-HVSiQw-YLCzSeS8q0YyQEtjFCyY1-_VKjHoiu0bFvbEExy0aTFEsS4V4JmS24F2kSIBAqa1uw53m8Gv18JKRMdclbY7UwDGyFhhduzXepzV7nDeRn5IJVrqRPzkCc8J8dUtGUJwe_wxR6CXuLVKFnqPdKCbmf0p2ecPliiOeqjKqmFSagrBQ6zKYRYb20dk2OpSFx22AaCcV2npZGI8EM69oi3l3w0QOzddLgcQE41pgYDBdc6hnNCFsUjiQaLwLaYtAawpTx4UrqxxB5bGwLuCoIfbid3jYvLmmlank6nrspZS32ouuSo-tjRCsKKQ9c146OaSd7wi23aeDsX23mejPhdl0jw8HnTYe9ykgztDyHkKqwa3VD3K_aTOC2PrdAiOCZk7FPvPk=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "grep",
+ "input": {
+ "pattern": "DEFAULTS|max_|timeout|budget",
+ "path": "/opt/kinex/packages/core/assets/python/kinex/lib/kinematics.py",
+ "limit": 30
+ },
+ "call_id": "call_1898ea06c50445418f6c0a4b5d2cbd22|fc_0b5218887c37459e016ae26f211c70819fb513db13c372e3a5"
+ }
+ ]
+ },
+ {
+ "id": "64693190",
+ "role": "toolResult",
+ "tool": "grep",
+ "timestamp": "2026-10-28T21:54:41.285Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "kinematics.py:15: DEFAULTS = {\"position_tolerance_m\": 1e-4, \"rotation_tolerance_rad\": 1e-3, \"max_iterations\": 200, \"damping\": .01}\nkinematics.py:50: DEFAULT_BUDGET = {\"max_attempts\": 5, \"attempt_time_s\": 0.02, \"max_time_s\": 0.1}\nkinematics.py:53: def budget_options(options):\nkinematics.py:54: search = options.get(\"budget\", {})\nkinematics.py:56: raise ValueError(\"IK budget requires max_attempts, attempt_time_s and max_time_s options only\")\nkinematics.py:58: attempts = result[\"max_attempts\"]\nkinematics.py:60: raise ValueError(\"IK budget.max_attempts must be a positive integer\")\nkinematics.py:61: for key in (\"attempt_time_s\", \"max_time_s\"):\nkinematics.py:62: if number(result[key], f\"IK budget.{key}\") <= 0:\nkinematics.py:63: raise ValueError(f\"IK budget.{key} must be positive\")\nkinematics.py:127: \"\"\"Select the nearest verified solution within the existing search budget.\"\"\"\nkinematics.py:128: settings = budget_options(options)\nkinematics.py:131: deadline = started + settings[\"max_time_s\"]\nkinematics.py:134: for seed in seeds(joints, targets, original, settings[\"max_attempts\"]):\nkinematics.py:153: reason = \"time budget\" if monotonic() >= deadline else \"attempt budget\"\nkinematics.py:204: for _ in range(options[\"max_iterations\"]):\nkinematics.py:222: positions by name, within the search budget.\"\"\"\nkinematics.py:225: iterations = options[\"max_iterations\"]\nkinematics.py:227: raise ValueError(\"IK max_iterations must be a positive integer\")"
+ }
+ ]
+ },
+ {
+ "id": "297d3ddb",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:54:45.527Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "edit",
+ "input": {
+ "path": ".kinex/tools/cartesian_segment.py",
+ "edits": [
+ {
+ "oldText": "end=model.ik(local,q)",
+ "newText": "end=model.ik(local,q,budget={'max_attempts':12,'attempt_time_s':0.1,'max_time_s':1.2})"
+ }
+ ]
+ },
+ "call_id": "call_79c3154ed59947fd8987bd6bbc0d8430|fc_0b5218887c37459e016ae26f24856c819fb3f53b874a8c03d4"
+ }
+ ]
+ },
+ {
+ "id": "ada27295",
+ "role": "toolResult",
+ "tool": "edit",
+ "timestamp": "2026-10-28T21:54:45.533Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 1 block(s) in .kinex/tools/cartesian_segment.py."
+ }
+ ]
+ },
+ {
+ "id": "f1234d2f",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:54:50.313Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "align right grasp and inspect near side",
+ "args": {
+ "goals": {
+ "right": {
+ "pose": [
+ 0.344,
+ -0.09,
+ 0.82,
+ -0.5,
+ 0.5,
+ 0.5,
+ 0.5
+ ]
+ },
+ "left": {
+ "pose": [
+ 0.04,
+ -0.25,
+ 0.94,
+ 0,
+ 0.70710678,
+ 0,
+ 0.70710678
+ ]
+ }
+ },
+ "grips": {
+ "left": 1,
+ "right": 1
+ },
+ "duration_s": 1.2,
+ "cameras": [
+ "left_camera",
+ "right_camera",
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_e06b39882ea4416382986dcd89c24d40|fc_0b5218887c37459e016ae26f284e64819fa920b9f3e8cc677d"
+ }
+ ]
+ },
+ {
+ "id": "5469803c",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:54:59.252Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224491.855424014] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"measured\": {\"left_arm\":[-1.007556676864624,1.9853966236114502,1.7999980449676514,-1.3873368501663208,-0.0012377145467326045,0.3198549747467041],\"left_gripper\":[1.0055662935430354],\"right_arm\":[-0.11214446276426315,1.8662967681884766,1.3592849969863892,-1.0733658075332642,0.0006734680500812829,-0.12759973108768463],\"right_gripper\":[0.9959410239349712]},\n \"file\": [\"/tmp/kinex-observation-oewipf9p.png\",\"/tmp/kinex-observation-n29q4c9q.png\",\"/tmp/kinex-observation-bxtc_9a1.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/5469803c-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/5469803c-2.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/5469803c-3.png"
+ }
+ ]
+ },
+ {
+ "id": "1c836c4a",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:55:12.031Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Scanning for left shoe**\n\n**Lowering right arm**",
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+ "type": "thinking",
+ "thinking": "**Computing TCP camera projection**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26f843b20819f85bc561d9683aea6\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Computing TCP camera projection**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m-JoCkYp2wXgqhvK6wluBBio6bGCtyKnjyTwXXfHG63-t4AA7G9e3Dr72iKtygwLZrDMZR-iPhfZ-MvlBOfLUpy4YyzERn2ifK131jbqWF96Z0jPtsqmJ6yNjbTc3uVmXCR5XNJzB_Glo3JqtP-TTwcRvOI6SMVtd1CIRHhPxTwRXRiGq_FzWOAPw3qFSH24m_tQfhazZQdM6b740YBNGfzlL8a97VfTSYov_ftdm_PQ8mg2izxhSvw_xBuh0G7DVpIAl3s3ItYCh1Vsdl7wB_2NEJXfkq1P_1vSIwUWP8z6t73SQlmqYZhbe-4p_PGYa2mmaYTzGGX_g4Lm_OCpNbk9zMK39Gw9ysCLThq9p2pqFVqi8LXGDoUhzPIeOQ124pa2x_xRa-HLkVOQKcG-AVgmass6CyJIQLYdUZ1bJTarz98sMv1r0XdAAVULWmdnGYnjKe4qq-TOoAhV4pI237B6V9bZ4BDSAY5C0O7ISeFzLCp3BXFdT_glWJyi2VAcKqOn9HoeXeAZjyLHk1FAlsOf3jCsELs_XBsyrtB43uAs6zPs1KlF7a_XAnGp4xflnqRAQQOY7xvTj2CMojhrWJEsxg7UjqVgHArNOu8SqMkw29CrcpTLyMz_8vxcbJ2yJaBo5J6CankyFcpF2emeIXtnFELpUapgNFy0XxP1gm7iUDIUiiGJceW1RfvfuHPPbfgUitFYlBQ0SCZZEm-U_HTtMzBW0tjRwbGv_76C44oUk6IARvYvmE10P5Bkh1nGB6rQv4HbsIGsTCwenKmIOqBftULNhjaQqHgG9Y30U3d1YJHLXeY_wU0M04lsrZASTsDccDAuVZV8FbsJG2m-LCMCUKGdIzeLFONrwCIgeuUWgWB12trRDdjaKSgpaWzD6xU3HQQcT-NU4mM8sDlQhz2UNQa-DjngxY_ICSFp-k3cZIEIrAw1aMFs9Jnyli1sf7ek1S4OTBezsek_ICzGFucBYoMmHKDDzY3bCvyMVc240X9hvPIb7HO5WPKMCRMMnwGHFsdLXP2O-AyD1-9wAKEztWWLq8kzB5XEzK8CWms3x48hdIGyfnU5OqPUsuPIA4q30mHnqOOr5FvIHuPJdNE79zGy4hKkExbdycYcsTc1vW-CGGjxyPvO9tAyHCavaUw5cTEaEPLI9L-LIvTMGfQgoNG6S9gedmpNDduJoKjqsiP54HGhh4bauYjLeYJxMWOYs2KIA7mHPepb5pWJMgPu3OKXmDrO8mJ0-BAxP5t86BRh3W6eQj8f1_zXVt_GTVyoQFFPGHBNKBiVc-Jg8KEsqedwapZygVvZmt_WdZ9PXcvPuiWnjWy7rN6FymyaL1cruOrU8r44fcdFhFXgoIesBxkNa_-qTlDR5VoHvC_chlg8IefYhRpUkvK73PWguaFIZSyjgDAiOLPOQYkFson7wMXSuRjPWmTov3E0TkwYZIY_ARBYzx8PYvbcDDiyTqACsnnIR3tVSzGCknAKdLp5GLzW7ya2fYi6Ucv2N-ZXoGQYEyMNoJrzfHh6gfsB-NyYjP-aIcU3qhjEqWKffnladrfDPr4G6wGBR60XYbCeEI0YDSRSsxR7XOKjHkOGdLVkN7_BwyVx6amqNxl61ba5hyxc5xvq6UvhZErp9g69QhmJ6UUfbiKColExxWTPsT71W6V-9ZghsZC1IVkgcIpwkV4AeuxfVUO6aEvdab6kEKHJLvIEdOMQ2IIeAgQ3T_WayKGyoK_kMZ0ZP6Brldj0SCn3cnm7W5V-VxiCF2WcEESPjGL1VR0i8pfrp_Sarm3m7x6hwRx590kA5_XI1cXmraRYjBnfba59CqN0gE46mIsDWXR8TXCM2GiDO84-g_Ey1HpD88VU-HBDIunF7schbuAsK_nZNuoVmiON_H1Hc2uiZc4Kl8dCc2D_rH1pP27UISHnu2YQpyuyrnT4mvV5OqBLqh5TW_WwApJrZGJDg6RruMXqo2gtXSuiEvJkfiLOIdC08h3VzCVSV_fCFhDn3dELiOzfAZTiJ7TvEGtaXo81Rgef-vbQerpFq0SQd4TYd2P8UzLhaAk5MsLJSU1wSWUfXe4qWOsx0t6G213MK5TFIP3gz5bi2bdjfsM1HSc9t9RwO6GCXXGdVyJGpU7oFfbRg4Yk04NgIIlDFSgMnnou4EmMSG-Us1XGmroS5Uj3Is5yO-TR6BNpRh6F-EECnveiocLeR3rKMJgrBbcmf9uFfvg4OIEpCSmpzmj8QV29MkQnMyf7IrZHxu91brOQtJ_cU70_axdI7KQqSIP_LtsAhfO8iKcNUcWZpEcy94rc-zWO7NU03GTF20VrTS6gHbx5yKu-q-w6sEqhDrVUAdM6axOPVC6iIK2wrV1jIxOmDX25dXwWpq_vFaxvsT9rcuDXRTqFremiIhVsj54Y8uSJh--vvFFrtX58yjVtpVRKyCjEKYkmySI2Mw7WFS6RwMRmUY_2ALB0ZN36AJM7dTLruu82uQIAp6EWrFTXmrz8IYVIClZvJYb30Sf9BVlbVBQkl3_xGZEz6oa6D-p_ZhILPPzvJLtNQ13n8woyJ65\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "compare tool center with shoe surface",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n rel=await helpers.relative_pose(io,{'frame':'right_gripper:tcp'},{'frame':'right_camera:base'})\n tcp=await helpers.relative_pose(io,{'frame':'right_gripper:tcp'},{'frame':'world:base'})\n im,d=await helpers.camera_frame(io,'right_camera'); a=helpers.image_array(d); pts={}\n for u,v in [(220,190),(280,170),(280,220)]:\n z=float(a[v,u])*.001\n pts[str((u,v))]=await helpers.transform_pose(io,[(u-159.5)*z/358.64218,(v-119.5)*z/358.64218,z,0,0,0,1],'right_camera/base','world/base')\n finish({'rel':rel,'tcp':tcp,'points':pts})\nasyncio.run(main())"
+ },
+ "call_id": "call_1f2454817820440fa30d581a8b7bb57c|fc_0b5218887c37459e016ae26f8897d0819f865d0760571e0e3f"
+ }
+ ]
+ },
+ {
+ "id": "e94429a4",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:56:30.087Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224589.387025232] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"rel\": {\"pose\":[0.031999988504280985,0.04039803789401142,0.07136523029414477,0.5893679914824401,-0.5893679004513149,0.3906986006032956,0.3906986716386298],\"timestamp\":0},\n \"tcp\": {\"pose\":[0.33640272493657036,-0.02633167088001903,0.6917798048149151,-0.49874693434276596,0.5009926290810037,0.49905228115506656,0.5012032539440671],\"timestamp\":15.92},\n \"points\": {\"(220, 190)\":[0.323961443569907,-0.027427434548870908,0.6438170953602051,0.9801154340873507,-0.002145094267080949,-0.00048323939059973637,0.19841597948260303],\"(280, 170)\":[0.3420592549054097,-0.019472769566128686,0.6447653287773406,0.9801154340873507,-0.002145094267080949,-0.00048323939059973637,0.19841597948260303],\"(280, 220)\":[0.3453272239232121,-0.0403433584497698,0.642715433205389,0.9801154340873507,-0.002145094267080949,-0.00048323939059973637,0.19841597948260303]}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "d063d515",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:56:47.844Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking shoe depth mismatch**\n\n**Visualizing right-camera depth**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26f93014c819fbfcb963ff45c45ed\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking shoe depth mismatch**\"},{\"type\":\"summary_text\",\"text\":\"**Visualizing right-camera depth**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m-cMg767Bz32pLqGWUmJQfokkO5g3ktdXeWN57klilToBEDvRgnU89O8Zlspg9QHkHojZf54QpJlbeSCePz3xgAcfp6QgBWR8W9jI9zD-3WU__3xRnlXyx4h-Eze4tI0xysnhAQCVSnA5bYLJE129oGTz8yhhxD0WiNQ4R_DQq9ItUn0omfGMJZcwMKD_Z48JffLJfaizKHkmCT6rTNrG-qY8QF4pHfss1kxYbMb__PAzt8yW7Qrm2PyPMYkQlCfRMwo0_bAbD3mqUCkDIDc7RIBdzZqlqc9gywwtdLGyra5hSPHdt_BlZ1Ettkio3ca1_LQ-jkg34sekO9l1vX3YnlPFwmXPSN7Ucj-s2YHdzZgAJO9yWphQjFjnKU0VZhO66-jZ4Rc9Df8-YR3GFVf-DDJZzNlJ_oQkPpBZlZCjoXPTo_rQ9de1ojiGb-NYlQzF7GqtHht7oQIC3vADp9I1cu8wXFepIbKDYCoyqzWz9_RWK9Ao_6crpQt1hIhTd3mbv8EcE5e27AXw_E7ss4gpIWqX9ufs3ZKOUn48QmrtAU1TR8ll_I2uLnm-my2UvD9CfK8os5gZ0AxJNaX5-gdL3CpdLCVqT_PMfEHBRttz3CB6AQjkccjZoAnmZN-i2ft3GUH50yFy0aqFBC_vNtqvW5F3I86_gQczMq0mxb4xFKfXlFJIDtDTI9xChtsBc0j8FOXOggSKrLyxfjpqBUliH99CSQcGrxZepw8SsEoVSERq3lYx4xDmz_dqH3xfpyGER77cTtbVRRNvHTWJL2gRqt6Xs-F2_6FtD5ppbqd1HPYHtdhtjADqonoGxuU3XE6GV3zspY_0jDfB8-khL3664fYopJt_vpsOxI5qhkLE0kqPYuRKfO9jT-KuKfzWmddtjRKaLmraN1tX-XbZycQoapxOfQl9K3XyQNJX-gT0s9npGd7IN21mM0I4aM32XB4wU0vaPv9EkQrzl325-4k0_j0nL5_uAsiiPq_ZDTgbVj1QCgssHpgbFUVsBDYzg8N14sPVq7jycJGs9uXSmHbwd7xMERwNRPEZm1ruc63MvfwKqoiBsEOMlaVUrpyyJxPBVScc-1s2hX7W42A8kxruvQG5KBZeYfoi3Ipd4F3VvJDpPQCyBnbChhU6N14pESMoBJhwaP0mZVBp1lyXuD9G777S-gHlBOOJdAO_9KlM6AqpXsjFZitD70iRugcrPPrKJtE8lRiYxoFlEO44I7uCSpCmQj65BUG2uI_X8lBZY-6ibRXRsCLEpSl6XMf2N-0T0knHf1CERFUizVFxXlMrxVGZAUZ0Sx1xN4Cre3MXdSHc01y1TOKE9KAJ4t8U0Buzg_EA8hats-JEznujWKkcx0VVZ8Od6gukemvy5Xu7Ez0s6_waS5wIDvRLMDRWdl4ypoL7kGTwd1QqKrVs9z8x5MH79bb5Ob-BEpz_t1oXMOhRJTlEFTBWGSAKUORLGeeUJN6J2I7Jb4yzFpH2MKhWDh88AozowV_sNeSaYrlqrHZ6qftI0niuh7T85rnIWI6sgwuFsW-C3RjTLJ2oHywpfV7tcgJzZyjRG2kdQei-wvIaUBwy1UB1Ox5dkBv7tUSyiKdg071BmJa5ZNJ49Vn1TN3gRHfYqcMKJQEkA8jKqDgP6wLElreGyFalsM3Xfo5ARO70qcfp_0RmRfyqmR2nNCAQptF8YoXPwfWiG4thApe0rYB7RDOHtyHGDydIb8T6fwdQV_RjmHHyRJHeYgBgJia73Wh2VDxKqAvmrEieGYwywO7HP438ohpAteaoLf8EeAjgYKCTD5TgIlvTKZYLBB_7CaLJlTdsR-1a8557YK4aR4yrXhnu-bJRu1Jy4-w_ViLulEXCZXQbw-lb3ID48Rvq-e2vQpzNjKONxpx856XZAIC27v4Ydh0KF9XsVu9ncVsEEbBRV6a3wyF4-Y75h92Jy7yVLmdf0nhW6z7vmfHeGx1yT6IaPkIAcFj9y7TnWJ-5DUFbAJ1rSLZkG5VsyQqUbDjLsS5mwQgs3vOe0rz94JFVyPYAXd9eXl0OrFs51E3bcXC5v5YTaMiDme8LF1tHx7-ldZntNV6Vl7w2K4FEhwRSQX9cKmJI0zf9QgKYt1EApFZVdDrQe1UlkXXdTAqrFvALQePxU6RXed55EBniw4wR3veC6v-444B7tqzjVaKxDpF0bLmAXWKdVigYZkBZ0dbiOlYs54dMAR_tTV7cEb7ughH43RA_pP0YEJHvJjuMvuzRiNQq0YfEq_gJ5ZEPAlDSKa5wV6nEvUjIdAV5C5XRfAD4ex61lRT77ri12hfE1SJr9Hn-0SepvM20a--gAcIMWpClsEnehMamjoo3kekAOQsqG2DmOmH7EhWbbfRd3QkT_ynbcw9uEt72iZ3WNoyYOzuDpyvdBG-UgMtjbdaRe7it88y1aZmyZz3gCEk43yWUWAJYJjq944XZunkh0KtRyjPFXDKO-IEIacmATimPjRqzTWDHv5mHCYqHDgA2oZjnsF3941ws1NyS1GZkuyNRctUU0mRCocyNPJTlONkAnT_Nd5uEDLdPmxKF1dH6v96xktJzAwN5GIAOeIbNsG5AAUgcYdarxWAQ7nVAMKsuILECCvgtwORwJs-PxQfSFy65EhksQg1dxBLInTG1ImblutDygZSDEpXrWCkWmCbKvw3CI_Fq7r7d_77CrL3nkN7o3Sex-CNCEHsLiekNBOqGKh_pNH8wojc8kv_NmksYLVRILCC9JAcJZvHI8BSezdORhyFwxzUpOiOqKa2UsdgUxdEICgDAu_xraYAxXmVZEiR6QtbylPPD-EdZzLN_KSa1mE-QCBviObqzRegUVc1e8hh32G6pqZOOtBvxPDhpyOPFxiOdQE3yaVEpKgBAxINQOHvGKwkQ0dbjrBhCjY-iwWabadB6NRWH4pPWK0ADn_NU0HqZd0sQGhfff8-WY_PBevrfJouS0Bf8FsE53MhHOjAL5ewSDJekY5KNgGRETd5FeeHibJj6E0Hi8Hjnx6b6YtN0vKV_75WtQSrLi7uIujpbzagW2EoeWSargEVPwM4MY8JGAI41yWMoCTrU_P9aVM_kzqLQfF0o_bPe-SiVYNs4ta_QYj32lHLnvpe-dRgLOWKJOhIsLCNYMEecl7zzy4TS0jx1-OQzlZvNgfpaZ1F3HE3XGzIMUFNOIGCf-zHActvKkmYolxyADCkPB4Dsb9Sa3Qe6nZ4ROdKt03QGq8FcXXuxqOfHlwo98OZv03g7ByesYLeV2FPv3kZK9Jr3jePCZJfTG_HKFSG1jDipU9ZgGRkfI9gpRSMMabf8hoM4veIUi8t-sPNBQHhDCaFHlCK9GEnLnpypEggpBfOSvEEEHD2G5LLPEQcUBBsef4ziWzlHC68sgkZyVDIRE0y1hE9954vxg3te_F6GE1uBWoP3qpQu68L3NGYiPh7QjJdU-zJ2XZRNxVrJfB57WuoNP4iVSWnwGjpC8fALPrI3p-L5qE5XRwL1wPQ6pIllhTV5OXeVb89wl6L_sRqgshzc0zQ0VSh_Js0M0sCuU-ubefF-61QlfbBUgkvjAPWK69pA5qgF-MUZd1Z8neD6O2OqsVJlhu6pFxH-B2CP3UYaTtfsCGVCYYswmYUsdA5KJnQFvnLM0PUAPYzTBc65aytGgjYhQncPX8iAj4zA==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "locate elevated shoe pixels from depth",
+ "python": "import asyncio,numpy as np\nfrom scipy.spatial.transform import Rotation as R\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,dep=await helpers.camera_frame(io,'right_camera'); z=helpers.image_array(dep)*.001\n tr=(await helpers.relative_pose(io,{'frame':'right_camera:base'},{'frame':'world:base'}))['pose']; yy,xx=np.indices(z.shape)\n xyz=np.stack([(xx-159.5)*z/358.64218,(yy-119.5)*z/358.64218,z],-1)@R.from_quat(tr[3:]).as_matrix().T+tr[:3]\n mask=(xyz[:,:,2]>.66)&(xyz[:,:,2]<.78)&(xyz[:,:,0]>.25)\n pix=np.argwhere(mask); pts=xyz[mask]\n finish({'pixel_bounds':[pix.min(0),pix.max(0)] if len(pix) else None,'world_bounds':[pts.min(0),pts.max(0)] if len(pts) else None,'count':len(pts)})\nasyncio.run(main())"
+ },
+ "call_id": "call_20a1bf8d69d64695b29c470a62ab6cdb|fc_0b5218887c37459e016ae26f9ce970819f9904f7258f62e640"
+ }
+ ]
+ },
+ {
+ "id": "03964626",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:56:50.492Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224610.029616113] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"pixel_bounds\": [[217,104],[239,163]],\n \"world_bounds\": [[0.2889084230314078,-0.032890889789939426,0.6600515195421714],[0.3053804617258074,-0.02516070082117358,0.6626498111904289]],\n \"count\": 86\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "a706de89",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:57:04.555Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Raising the shoe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26fa7c08c819fbaf24f89ad488072\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Raising the shoe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m-wrBwC-P6PhwoByBhSku4rJzf_FTO52cehVUQsKNuil0TAuSOfn1eHlOcHT78ToZLRAJ7hlqzfPzJlfqG7YjCgfnfqIzDeO0iQK7AsX0N4ai4zE8rDBcKo69jsbbgmp12kdoTc_kCrcyaUR-l4at40MfvFX8Oi9GoSvW-ONbEjVwJB6X32oZ_wSep7OhmvoTQA1aKZFppUcOAbfisPnDRm65NqFKgz_1sJ2UgI4dQjFVPBgQJgBjqzPPdajvTZINlDAvzlA-dPHYJEZkKe6SCLLVYshFDiwuzpoXQdniVvuNwKp-691wuUnTg9zU-gc6vJb_5oLUFdJzrJaJ8LAr730UBuhJ69bCSAdfr3ckw6kBtHmllKYIy9Cxr58O3gmUB3F_5R1woLQQYGrKYQQ9OEsP_bAP1KvqjLUMtQ4gZICoyyEQpWmjVA-eaPIou8yIrq2OSD7OuwhZFXRTF5u_qcVdNh5_nUmx6DMYpsCdd3cC8rsu6tn5v5FjDoKmu812Q_lLiMY_5zmp-3UK_moP5NqQ5k9CdoTscr0VnoVDjrN45LOwAcCWwV0sSBShkzO8tV0JYvEfPmcKsNqV0BPTQ-K9_9v4cXV1F0Ka5vP1nXth9Oq72uvzvS6TfDhuZjXjb0KCh1l20vYlzlrVsC8pHzsTHruEvC2w3ekZdnQzJFPdTzerhbpuOWxeubDvRMwVk1pjlq3eo6eq61aH8O6NAsHLaFkMGf4PM-U5C5dPYDF-8NLDcZrsog4Lzh9uoIDg8qPpjfYzdbeZSaE9P9oIY4Sf_evQEaEQNyHXRWSmbO95EZuKJe06HBXUnZ7aAK9aoD3FB3wDrDsGH4UWjAnGTSpyrJcEQTrmz8A0zza1nW0Nam2XidJ33Py97DRNVR2ToNKSl-QHRvynfadY39cE8AdQBGWT3sxLvGAvrwXmrCKWTzxMhMCVk2RvqiY-eONtVrX9uQsRYo2inGzzngCBFyAHTYgahOJXTtT8E0FO077I1T9VhSNDhs-FnvA4U9pnL17WT9MU5yvlEkU81h1oABDA6zxMUJvfJEW_lOQ4Je17r872zGiohCiffnpTi7EzCIUC7pT7IX_rxmFtU1mfW0OclHEQY69gxwCgI2Qn4FUNCGJAXyqUOYIqBuIsCprY2MBczK7bV5JfEXgbTJhzyhgWDgopEd4JPCyt8bpalm-VZd7abaWQWRejsiYsQTFFHJUdFUduBAhXPMIsoDKNMXEymYx9ANIma5BanC_LZ_DGL8Xnirn3RBummchhFq5VB6C1Ed-v7e14Y2L7pvugncrGewLmn0qHeFEkiSe-rWsCAax4gDd_2VFYYDK8oLwoP_9ZhH8MWa_5IwwLg67jw8qV5dalARdeePP-SX45rWZsnphnvGyB7AVXSoWNzSPSzYg95VwVxE-9KM7kgrpT9-Wq50IcxIW7Xov-oQgH0odRPkZYDlIuTAaPMcQx7IfKrclnUQ3cPpeRuTlS9V0Oo6IcdsmDD--1Oe_Hto3ul2HRyY6O2FCitPgs0ml-R-GjxuzlPbBpv_EM8XRYy4gwk_xjOmeajNQ2_PByEE_VlESZuSvCHV11GkZVLE46S5vVbZI75SEs0ZHNmv4xdlkqlfidTJCTiBcGXjaL5QsR0YE7B76MyM2qaC0WTpXWqXKKkpZDOVXISyUyrWfcL4Srx3FnlFZW8JOl34t6fRFWwWf06EU2PDNL_LnDDYH9H85GQ_cJ6PqZMaz9s9J3CoP1Ry2rB2ybCzSaOZpUQZAlRPJNh-VbagVzmo7xddnzo7prxgIRNY6P21Qmf5JO2GHCgMMHe2O0hcUZNGbC_lwPxuz-21ITJGhDv5QgOVahdEaQ5cWj8paWX9gEI--pFrqyXqltFwp6hGS6_oS8PPpP9v1sJGxycpj_4GnX6Pai7Psi_n4lLVB6xDB34zfaKNhUbUYhhIpiWlonCnGkiE-8_-REyMKe4CqPEf34kpilpL2075PA0vvsaOv3dYHd8NGEsGHGKg18QZg91a4KShH5CnXaY5qQLklgO_tSO17IyuqNPyEXgc0BssZlgMIZ2rCtmJiRagpq5oGqgvCoP_T3UZj6myXoC5XubxkeMKmMjzC28U6tCm1xa2aGmrxvdLbZmBEp6H40Y6232Z10uxlx8kEHnWOLDm7Z18Nkn04Kmt9dVWpZIBE5H98sQtSoW8uENcXlpJEmePr3fft5zl56xbYaIEFjepPwErkR8LmXTakD1ADbMnybqPYmfvhvVbvjXH45aIxa7zCJFw-ZpQcxtobD2w_4hFYCx6wms4exdRnLk65eDeVazAZOhSFpKMMtVgniEylOUVMxYl2G2LfebJrL-IzXxJ_E-2nhu7-WM1oy813vQV0StayCSYEgy-La_J8CEMzPi1VgARM1JsN6DnCeOkJE3Pkl1Ia57YjOg_7ek45fJnemhrPUD03rHsW6ZIYPgnc_1RFuxEPvWiqEf-VGZsozltbYy0ZcZgz5tsXxIPe_uLof5R2taD9ZOzj_o1M_7SdZbVPU6fxtl7SGezM8-coQ5PCKTIUrf71g70miIVnLzXdW8gA6hokUEUz0CGa8fIX51--y81kkEXjMW3vxVScBQTsJYMO2GzgAnZlgVWyI93BT45bKf7iClAJLjD7YNEt0tsm-C6ukLTRFUt8gpLZRUez7ibnRGBtt6om_tQ___BY3mOKtuE-t8lJjcJizvqXEtWYm0kVpIxrKI2tskE68BckPlENUAg3mTXwQ4xm9EDtakATnz_8soAbjM9pz3V2NZwKirrDZd1lr58-1yS83czcUES71hZKLEblS9p6uERUlFPmnv_SaZnpgWckJ8dIpGed8vjL7-B7tif0byscBe8uFUCJxMUTuLF0_tYO2FTKDGeemVaZPY2Cltu80e-EgmIqDz_C0zl1S2y_i4ATVzvDWna4zX4nlumvw8jicGHZMcLrNIa0UAAEjg19bFM-lq60_pMy4mET3B3CFyqTSCiY7CTAC5PC44qzBhTao1xeWdO0tHHDF40i8TPDw==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "widen right wrist view",
+ "args": {
+ "goals": {
+ "right": {
+ "delta": [
+ 0,
+ 0,
+ 0.22
+ ]
+ },
+ "left": {
+ "joints": [
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+ 2.10649,
+ 1.59874,
+ -1.06015,
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+ -0.65544
+ ]
+ }
+ },
+ "grips": {
+ "right": 1,
+ "left": 1
+ },
+ "duration_s": 1,
+ "cameras": [
+ "right_camera",
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_d7c02ebd0c924b98a4290386fea210b7|fc_0b5218887c37459e016ae26fb04b24819f92f6f47a3457bbfd"
+ }
+ ]
+ },
+ {
+ "id": "7403242e",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:57:11.739Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224626.173253423] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"measured\": {\"left_arm\":[-0.4864189326763153,2.1139965057373047,1.6437352895736694,-1.1013754606246948,-0.012391126714646816,-0.5226401090621948],\"left_gripper\":[1.0006968649950894],\"right_arm\":[-0.09558303654193878,2.0816221237182617,1.7370487451553345,-1.2321414947509766,0.002054061973467469,-0.07567489147186279],\"right_gripper\":[0.9936021512204951]},\n \"file\": [\"/tmp/kinex-observation-nsqsy3z2.png\",\"/tmp/kinex-observation-46fp2462.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/7403242e-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/7403242e-2.png"
+ }
+ ]
+ },
+ {
+ "id": "5bb3bf42",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:57:20.502Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Measuring right shoe toe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26fbd3820819f94bb884601241650\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Measuring right shoe toe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m--HdCASI6AXM6kFHeBa9uuaN4wao8cgSZYrWiX4BjiGI0Wu5urIQiG8gNl49SU9OldbaeP3sL_Zb1x90UQkM1zP7HisPYpJDXVL5GFsKVEBTOdcvXY2QMiIgAVwbQH7RGeL5bfOtoLiWIIFpuAakiA5IzFW79-EXrEtT5KcM3EMh8hsBXo_gJ1F0Y-D-FeIRu4_x3Z9SsgDf0GVrXL7VnUICI7ff16OWHmTkGCHc7dqNm3zwa8QBbFBu6BMQjTR4tCT6GiuJ3pqbJEorAZ6usyMUzqe4fcPeDR3KUhosclJIySp5gY08ToWdF3toAx5KU_pjo2fMjhLc1G2xZfPOxYtdTOS-Nc3CD-qhEhI5hBoDhtw2xsSOc7NfSIwa8f1TrTEIAdOHKi2LJWP1wZXYto2LvPPD0lHOj9RlCGEcBXwdDw7_UyQGlqj-c2AooyM1X0AF4fnBcJE6S15eK20ArAJR-FPkB3fZc8l4QiWNondpVOz4HKFUhS5YGItXl3iUrJek4o20z3LIKYhohI90Ach8JHnm33I3FYcNvc_ZiS2mrn86hEDF8FPU_Caw1w8E6bxzCJR4hiWg0oosPxxUIQxqeTa3swzBaV5cgR7RQ6oARYFk9AFRA9dWyYruSbHEUDeFJ-ocOHIp907fX3kZUVKw7cC3cjNLyAMYttXm3qjBgSMmdvSMHp4jjWrz_UMTpUobnWabfY2FRZZn9FK-usSQ-MiOp47vmdIUxIZ4qaf1pi6SUo5yhm0QZ1wDx0iJiGqsPhobt-YzYG-qM-ZPK9X5AmK_7iWVuH5t6qWwO2o9tujcOYe1Pok1gI8d8CsROdvQvzZqL5uuR9wsytYp5P2ztuZCXC1MePgrz-dJgnzLsFqBhSb-628G1GBN8g1-9sOBQVf9B0AmlgWGTY0FzwphQzRW7-b1Uj1tIVb_oEszq9uQRFPPD-wG5gN9pPIk1AUWIZzW5P-xveNAf8TF9lTiHNa5qXdjJ8oWJoX1qyKh2LTdOD_10qujDQfLknvZ_1-w00c30wfyUtf_xxsrtEmK6FuG7Vm0THpg8yOh2OtXkqiAFRqv8flOjlE6d2tWxowhpjo4MGMtu2c9L-NCvinaup2g4R6baUtYRR0Q1_J8vgA-57NBnOpp51fTSLXqFxs52_VR_XS89Yt4cbbqrUB9kWwvYFajugLxz8Pcg923VtKdsa4yJQ9ewrw8ZBpp7FGN-GLS2vIjtprDsCP31C-JA2uT2KjD_TwK7_VQhjFBowAwLwIBSSl2RhdudzXvApXGQl_1wPIcXdJ1lVcs_PFph73o_O-4kJ-eCS3-6oDFHGgeMwgXyoDTX4b9UNcEWHtF217KU1V1jwBCVQCRr1_46XNImQZbm6aciXkrXcQhfvpn0zvmz3VodOlHJAqE8-ia7JSx1JtZnFZ67JnbxFh8Q-sXcvjnzp-pzUJVdp_fjjksGqanhBiqYRoKLpfnVbTMzIBNjk6zz6rz1zUBi_yiXtix66ZuHteGf12JT3OdtODX2ptA0hFnKTIAZ93OA-d2ZtJkLEIBrNdmGCoZwmtynwB1q6Y7uAxhCUMcxZ3re0yf67CBQzK6grARpnjcgBLmAcRKGNnIrpzUBtkLgbGWow1sJCSoPA0Rhv7PtxZP2IenOcQhfB0Rp2RJ0qSsSUkBJOjjzpV006kCLjxL7-Acg16XL9R7e2_7oKbzqyUhV_v6GAXCnvMSaxeh7SSJQt\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure recovered shoe forefoot from wider view",
+ "python": "import asyncio\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,d=await helpers.camera_frame(io,'right_camera'); a=helpers.image_array(d); pts={}\n for u,v in [(200,80),(200,120),(200,180),(230,120)]:\n z=float(a[v,u])*.001\n pts[str((u,v))]=await helpers.transform_pose(io,[(u-159.5)*z/358.64218,(v-119.5)*z/358.64218,z,0,0,0,1],'right_camera/base','world/base')\n finish(pts)\nasyncio.run(main())"
+ },
+ "call_id": "call_09d533fa54c44e92bd7cf0e5f290f468|fc_0b5218887c37459e016ae26fbea500819fbfb0dff90c7e68e4"
+ }
+ ]
+ },
+ {
+ "id": "55624b8a",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:57:22.896Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224642.187029003] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"(200, 80)\": [0.3319128077876595,-0.021384687358054988,0.6807880606684285,0.9794699809940978,-0.0010291198589706435,-0.0004335844173035729,0.2015869768816695],\n \"(200, 120)\": [0.3320860201227272,-0.047179444335913354,0.6896982618039296,0.9794699809940978,-0.0010291198589706435,-0.0004335844173035729,0.2015869768816695],\n \"(200, 180)\": [0.3313421415530356,-0.0816889616404346,0.7110633133544213,0.9794699809940978,-0.0010291198589706435,-0.0004335844173035729,0.2015869768816695],\n \"(230, 120)\": [0.35305419668191745,-0.04801774041168197,0.6878528021042477,0.9794699809940978,-0.0010291198589706435,-0.0004335844173035729,0.2015869768816695]\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "a447d130",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:57:33.712Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Lowering gripper toward shoe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae26fc5fc74819f8e4bc13c36119521\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Lowering gripper toward shoe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4m_Nzqf9eNi0oJmg0poGi-MVHfMzpxRqVpeWAB4HcFMQ_KByUuRIMQMw_-eNRM3vyT4JkS9n9kDApJ-Tp7FWggwVqtFfFIDJN_OiWTISQcLPpjPTQNZG-zhRQMOMusHZzUsSNLj0FK7wUoJsV69igc6gOzku8uJkcE9Z9PBPaoh3lgnyfdXSexIMvckdrO5bHbqjNP5IF48jCEDV3I65cQJOZBAJQPJjuT-xUaDAeLWnASUZZ2a2R7Gbq750Ar-L8M_jMmMAJsiKuhmvEsi1NNZbxbnxSKRIhKX7M_I6S09EXePUYHZJiyqF_JmeYKHgJvxhvCfztOmFDq1VfeAFoNqgs-FMhCdbLTYo_sbK7o4Q7RbTnEeIy1xYfRWKNbdtQqtF_kjbxGPWcrWzZeTHNZzP45UGBVGYHmXQXUslJ8J5_Rv0t7XkoEYxJfkT3qJbJh1xjjY8Q9j4cFGvLSB2adATemyls5NCVvjtZKp51MsGpZvwpDLor0fAmdxubJDTZVJXXerTmJGZpOVGBxgYIVNdiOVLU8NyvFK3cRNR79QB1UCRFp1LG4X-qfNo0ru1kIXjJkmKGQoNV3nC3crdajIvYH9sEQYAaYK935sR2BHzgEUBjeSeDwyO94MugLUaf_k1YvlGdTCe1CisR0xDnLOoarvnteXIp8rP7CBgHU7tuUJIxFEjcdBNTwvSnNia0dqI9QACIURBui-5TwbpPsm__k_fe62BWhAIHiimofOzztSG8vyOM40guog2ugyjtwHn0qHpg6k2nk2d5i7MawSu4ihQcVm4XQ-0dCQv8dc2gPCPTTgi86HS9eJvhjSTPA6PdYLYGaPHJvGQaTu-L71cVU7FNBCym02e88TDAQrMLuMvdlohORvGXIKmnU5DjBrrHMsr4UVcyTdHXx9y988S-TGTC1iIAr8PeCWpiWyXSKSEhBHD7XQgcf1W0D8PWtGeYXriaS-I3LEucDKPiyGiEZPjvPzYv3_ZuKJ2bcpY8cLHybl6K2caY95oHGAzdjXyyAAlpzTUZ0-4qdadgPjCxANjNDw1vAcJ2uq7E3ueZyLp2zmDFo3k80GEuwu9mGigschi3c9ZG2W_GIOVoIHfkypOaKEhxINd9ult4dVcRu1dPCtw8IiGviWGJz3Z57TvPNwhY061517R_JkNs2LKa5ZNvpJ693lm-Rdb1fkjqfZ-ycfYWiFCIn73gi0CpF9atfNLYbGmxrEgvLiehnMEBa6YdEaViZpZ5oWozje0fiKwvCy9BHjAiHSkPu4i3JMNAw4Vw-aQDESnmMvR5rD_QvBYJFvbD0exuy04GwsOCiEoA7Dpe-pllbnb0ZLnjKCbbA3kYvX4htzzNKWIZLeNLBNID5NIy5hyQHIk3RcBb_5Nc7ypBAQJaHNkW9EywnWMdAnB-OHfIrQt_j8F830lNfB32EmWUbKPBbHm498n1pkdMgS8uctiXd11k7aMhO-976dqg2fWFBknxmgkzpAVxq2dRsaNyvaXNkWpqNMRC_QdMor6gYljlPJ1BKOH6D584xX4xCIibZqlndEcIMI4BzzH8k5THemvheve0sYi9p1BMMgjLqSrQ2fkBMaGNCEM36T8rTOlJPgZ8xxhcxDf0-VU4LLPoiOdIyn2LqvBMcUAd_umHZ1US1QG1JBwdd9a4cr8pobw30xPUzlbemo8eH7DZZ7it1JU2bEMTVytbOGM9eePUhyDDqco-Ce99ld_bnbPnceHNhIZuHHqtTI4z9P_2ClA05PcXYDaAXPEX8nAXDyRM8ZB4bFlSTGHo0Y4QV5yYPx0gIKbxgmS7K1ANK1ZiQ0tVrSvyIqjAQQFxkFzYs00tWhVZVtqHkjCyNEVuy946MVjP7oXPMjhG9sQQAV4hGW5i2yVfYLr-yTumLF3E5SCMJD5dxP0z0_N9BEQkBYQiG4nLJtNsILNUrfubCZMniYZ7xyve5GfIyg-lOdRx6IG6ocHxNmnq7NwPSUXcoEvd7VqgqOOhhCG2STxNiRIEBmDR95Y1szPz2xLV__gLj_lV_MfRGMe3yDUVCTbKVNptkbbFrbSFZ7H75N79_LHO5CXQnXzgOcPJwNU1R-yKnL2ozeU_kTPRP9lWZcZOvKkCqNpDFJTtqEh_1tzNpRBo0cL6jibEMh7hWkJZ4ieHnsWf6rW2RQS2IpV6eG5N-b-8DxXeD7haeow_uTiJjFUXCnuVoevkK2nChle0YpAot_JdULtK_LRJsIJdkA51jz97NQE61r2C9rBO49DOj5Ooj9FmdciXWa4HN3BVed_tTl-BAeu4G72-wqSjr6-0R2BV0ndp1PM9hJE8LXUbJ42TrFgbyRKdIPBd5v8x7sWsAxmoOgm05TWTiSiZe9Jw0SqVoYzFhgABPRKWJ9L-Ec3qngewwiPIW8pTgzIKtMoA_3D55EyOU0mGct6hQLvyVUmQTZvSpqLYtVVMVMDJELa7YgruvQmrCzbNF5FycCYlMiWDGiBr0UmlW3W6lDDlTrgrrZ2QL-nhfgQseEvP-Bxr1n__5ph9d9jFqnMXD7Kb_LX9zCYZerMpv5jiVFgLOj3uZGj-zeCSeQG9eXawwrUcvJW22Ko0HIyhEEXww0-PesuNIeaGm5XbtWa3uzp1CsM3hXUnFHFa13mYIBn1UoNtKeOisqGPIM6Z87st-1Zem-OffRLyc7tWt2Lme20edggZ9jpQjZfk5xs-s3PVXDqVIRBLSASISXE8iYAtw-BBXhQqN__zvMqgsDNRBVpV4CCamYmE2DCMgqfKSDkyouf6c2PYVMpt2wC09vUGnq38f6tSB69g5p69h-icXUCocnbwg7JpryfpVMatPHijnRORRWHMu0KgRI41XaW-0hUEjh9_sftyac8dkBS9Xn99V8S4xztJeY_xBKl0318HLkSHl8HXx_q6m05LgMHnGAee1DJq-CNSkN7ixooSiSEPvSQ3cQxQtqzKI9Z61GS20GTjpT76HVzuXuV30QM5vc7_Pzt637r0xDdLBOoqVBXdkDXYfm4rRVXRNEXI7GZHw==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "descend for firm forefoot grasp",
+ "args": {
+ "goals": {
+ "right": {
+ "pose": [
+ 0.334,
+ -0.045,
+ 0.669,
+ -0.5,
+ 0.5,
+ 0.5,
+ 0.5
+ ]
+ }
+ },
+ "grips": {
+ "right": 1
+ },
+ "duration_s": 1,
+ "cameras": [
+ "right_camera"
+ ]
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+ "type": "thinking",
+ "thinking": "**Stopping after shoe contact**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae270014314819fb6cd96a8a16fe2f3\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Stopping after shoe contact**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nAEWuzut77zzHX_UpH5fg1RUvFL0MzY-788O7XqkHEPkE8Gt0PkP9O5sLMA47s2--b22kweNECMlEymMElgWPERidcffwK2yNXPVu0R8j4KuYzhOYb7hTS0k07WteVqFMvQ61Q_v1x4pYYiC6nvTp8y4VKyU8fe02os0Xh9iCCxCHp7vtoiAjWbE5g9m3ik9hGjiRW7zMxjcaDuK2Uo26JZF-x3L6aU5rkkhBefs5dRo-Gdxa3Ex2KhLh2V0C5sDU4hD8kBkZjycGnYpEbyYcz6HXLZdccQz4VFGaswGcYT6dd6rzWtUZRR-6-OCM13_UOEb8Fr7l-vdayErR2qN-jqFcfQayTqBs03rXfm5_-mFz5ZsjjnOaoRYSO6thYEAOkkCufTYKMP2aBgj5wjLpXowa-ETOQyPIlyHs1UOzq_aB9vBupHpoFyS2XDFUut0P9M-nlBaDGQY-10ExzR68IeULGMr4mM6Um-ZHFrDKgiCaWl6FkiQEfbSOGVqHzoB1FtdetgH-7OBO6ibeGT7vwACsl79z2JloD4kcWf-0Lj6qFOp8e7DlbxZuHZJPjVAPdy8OkBO_O3ZrHPNY9srYVfmcwSZBf4Fw-S7BX4WCXKXZ7iRvO6WI5e23TYgMXIZ3lGEZhb2PKEQLPgKVbrhDbaRFkgwSXX8EulefFqwkIoGZOw7HxfpM1ygpU3-7Eo3grE03y_j14bqxG5WF3onsR0b5-CTiPRI1Bs3vvHryh5Xu9beYTVvUGNcejNaA84DMoQsZDS_XhWuDQLThWpFldDt_OdNfn_mZQ5T8apgMEJ0v00PRaNa8JQJdCXcQOa5liqKVTUpvMmydzZRI2y4ugfbD4783BIIn5xnf6R9j0Bac5HTgQM-br4Rf91CnoGO1Yqo6q8x-SSFM3DLk7vXRQB4eWbgqBBLvglZh1bBuT73tb2C2Fegl_p5bq-FQoZ-anIY6Oyf56bCIFUBiKnyZVXLfaUK_VWo3FE8CG0Ken3jSmOqu9nwwUkKr_ssSlTbpoBwqC7EsUFw72dTIiyK4zM4Bam6fSS6v-aEnpHfo7n03XbZRgolm5l7b6ayzhmxsTgLnOfxucM5AOSvQzTyAL1Fwx5lOXNDzK3bQiS1HQxHNZYdT2I5t9eFVvnHx8xfd6MLJPIcxPPtICGML9cZrsU0JsG4RGC5kGUjjVYKxIjSzqjVwym120ZUFFoWdugEZuKSk6EpfbLjpJw1fq5XTJfM8p3c6oLccSR8PvPPjvzOBmR2tl6W85zmuOLHxQgsYkQE1ntC-0k1ajRznskTUePBSxHz_vVyRfCHnkPBELPfGVkBXtAqb2UIfHYFlevy26MCnwy9qT_Zb6cleNJDwQ7pG_aCjQnbmYrfHJP3C1uLao4x9U3nBTEo_Oh3x9UgRGqJ5nHwhc3h0hGFr8S4RruHTXYeQ2EEcEv5gmYyB70tICanyXnotn8lqfsQRXde1nWGHSBUzMU-cfSQyoVgUdxIx2eXQ0IoTc5jIn8-cQZJ7Z4RZr56S8R8Gd_wl3Ky64v-LoJYAirCk96N4eVTumE9auMfMM6mlzfUt_MmXi6CbH0i4g_Xoy0sU1mZBJ6C8N4iRyL6SBqX8V6mCnYce3pT4xjpFDqAqlbvDk5epjj2LytkzRo7DzgmBxxNUbrS_5LHal9t2H8xmhCKHkcf36q9Q==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "device_stop",
+ "input": {
+ "reason": "Shoe was displaced during grasp attempt; stop motion before further inspection."
+ },
+ "call_id": "call_af13ee3ea5cc4286990e46befd9552ca|fc_0b5218887c37459e016ae2700445d4819f866a87f83acd87ad"
+ }
+ ]
+ },
+ {
+ "id": "5a30abce",
+ "role": "toolResult",
+ "tool": "device_stop",
+ "timestamp": "2026-10-28T21:58:28.541Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
+ ]
+ },
+ {
+ "id": "cd41a609",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:58:43.618Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking the right shoe**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae27009656c819f839feeef3880521e\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking the right shoe**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nASMqzUA-pH6r-h3J0Tx6VEBzxMkwcnQ7mxf_9UFYebE7OAobHWiJF6f1sJDHNwBmyLyZKhPs_cecLvNeG93V6T8hVxilYKaZjCgpb7DXRoYrJQZIRLa216RaJtuexclKu5ITghiSJ6R_5epH4yi5WAVXrTvxkeolOngordP3z2xlvpByKvpVzPhXVzJDSFR7qNM1o-E-WeK-vJFNIl50DIeQDN4jjLMXPimu_D3a7491XJQJHUn8U9KQnPTWgxsnQ3POSSyYOl9HtDjORjZ81bh2aKEmYSk1gaQvc91w282E-txMp9XrJ5qHD4cc0QfK4KHOrp5CG0qQX9_4xPBwRS7me-s3GpwUzpgOVOu-9HwluiyGTioEFoZs9UFn5n_mVzgQp5C4aKe47tLF5GqAh2FKMBBA_n3OgkZN57CGVAUN5Pc8F8j5fjZgK8e-28bM9AR7YgfHzFzdZ-9gj9_T-PRKpvvZtMsXVLp_LTgOAuhoTF6XAfm_lgV1rNFUcgTVlsPBtTbiMiXSry4IySNazReIokuKxJVLscnqdAnlUN3d3ZbZBAg7Eb_GRHnkOdh6DIwuBYBMrzp9tnq91-1_VMotBbjVxkSzy7ZR9WeeJ9x51_fObCOtETX--ujD8bjzASm_45ozw7p3gZdZPJeyefn1nNfdXSNzPwm2_uvvCO4R82AsVB9Yod3lw0g12SD-bqa92P88h2KeDTN6ptulaZRvHDythzws3xXQsQR-7fh6vAYs2vYtb29O5eGAEpaPX24jvMG491z7d2bHf3wVGByD0tqPr9gNwLDOZ7b3AFbnB1IkVP63X37oDdLhTVCuKJWWzQDpWqZxrJ9o0c4dqlbwK2V9wvrphoF6urraU3_XX4AqoGypo9RKeaNhKt30Iqls45PPwUyGjHYD84J3eM1Vow3HkWRzCa0DqNxDnCb95JEM3fWzfS_YmhTw6WyeWgJcMsfV6bV0a112iBeFNm8UE0rlacXtid6ijlPxz3gUKef4fCBgvppuQHBEZpFK42x2CQZzrkOPpjg3Wi3XXEv8D6tq0EWhSSs1NYTvp4yiHiuNvvhUr8WR78hV9yoMEofkulu1qha9I0N0kKluDqRydKpRuY6gFzJPHTZ7-8d3NSH8V_fS_HTE2hbYyYF8w6XgshG0yHn6iIpW4kIi6Zg4uNt-RKtA1fszZJh2v09DcZVTx4zstEG-yiA0TprqyKo55UbMfxOP_Wd-Mpgg908Jew-dea-w1dLXitM01bNeEuR7YhFyANgCRxZNSBOjumFHUp_2OcCxFhBfHW1up141E5_N3QrCOtDJEvNjoQEEJ5Xza8M7Yo_NdNNIK-kMi-s7GvJBjo1SyOff8GedHyQcQ9tpN_WCD6ifAVu1E8GK3XMHck5cCbmt1JHfp7qeZTVTJAu_32pTjCHR51KPNGu-YJ4sjGI7nDZ1CZjs-j9iDnvCFE8gHqff2UH78rmh4aRVuwrLIhRMfhQe0Uf9Vkji2y3BPSH13ORTJwP7ohuyNN4XsYhvRMhF1oE6Z5MVG1O1oys2smNbA85TfQL8X_ybS_PGrbLWMt96Xa--7YoYBDfY6mImLu--ZzVbdHGsnhTYC8LX4JB2jScXFOPJ6ijaIWtuURg36npp5Logb4xMVS4DOPbLNWEmZI4-fyxosGtykUVnW-u_WZ8Fu4lBpx0hSaY015gSDES_mEjnVHMBL2xCK4on-gKbFjNVb_bS0PYHKUJdlZy4CtE1wzkAU9ukPt_jhzm9KpXecWNPWP6iG3I2sYybPsBLwuSUTnjGZ_3LeUJ3ocTOLvoyQsm3zw5JZpgvm01mBl7-SaFOYSaB1Ps4NVjIS1oaEkB_B9GYcGP5T08ZIVlLrXfExdqzgK3iFiq3DT-X0V8nybfqO_nMRqISSJMuuQlYRDgaQCgmYKJfZGV67ogRpls_x2Qn3Dd0dBoF3P-dFsBDoLrLO20f4jiyZybKEJbONEVIQmY6gpMDoB7H2MNqaxaXSGzfewEBc_-n4DuDMM8rZEb5Xx9PjfW60YD2N7-hpdKZLw0IoyZqUNSnKuIuKR-N5vAI_7aiikwcmMCvFgQi9Jjc6g-dVR7f0l4hUIk1Pu6Zob-Na9vB4RMVpWfIkTf1bCCnfVipWQoSlfGlgjl6UU9csaxhl-x3oaAY-PUH0t3vl23FRzOLrLzJriEPimMQSMzyQRiMu-9JK6Ti6nwcGxYEPzIaDAsXZufDg1s3OYUwJpqABQ7xNFW_i4z0Rnj3-N1mBlWXxxVv7Msw93d-t7dW5UvWqf4B8latQR-GGJzUxuExc6ZjUMmBI3ff04lfEWbSib_86jzsSnOXzhqnILgTveGUf2Viq6afusCOvJ4Bqo0X7fkzMfAvobqBbZs0D0AU06MkQZDclTQUk6lw4meTXYOzo0cES24Mj_CaTq2CkGP2Vi5Saym9ocD0S1jV8P8mIZ01GtAux6BX-FVri5vma2_PRlGP-nfs1Tt1a8B9VvfkrIbA76n-oOgqqn1gw2YdtJInDaeGbEKW06ELSZ0hagxEhxE3DCLsgg4Bhc2n17EzpvUokXHFNlICQSBEIOk1qQIHt_Z1ko7XMftbv1UT1BZ59-oJ66F9uSy672CSAjJbgsAWOOG_OWDm_hli7EANh_y9BHoNOq8naK05N-2gtbRWSCJC6FpXLDrDyCwx19NqANLDCb3kNDR8Z8cFPtrRAsAXGaZnDb1z7j0cljYJXAo3j7NWKWbDkM2IFL39XCoMttWNMI6tkDYilgG4IoaEu1W906DH9HF_pBqYb9hCsWu0GqIRR73P_VpdGmyeK7NJPnJkYhAeKFY-vHlgSLGYtmOdETgOQG-l_cNpRmy3dI_6s9MHESfViGpa19Dbz3dKIxCL1JjFtdI4x7eHWpnKUlIxWFfgFG1TmI-rR1JBRVLGuPd4hAPThzdreJBdEq2Uzz9113SscUF5MCgGAbAqx7Wx13fPKAXCoN3L_a6cLaWqTbnnuvqaiVoJoqRFHqsvqAw3DE380skJJrPqf8oY78eGYo8XIpMT6Iniy0n71u0BqJvqsI5dVGDe1-uO4SZH3E-5D4clX3SoPwh2_oE2F4sajXZJtr0qtZk7rr_SxAuVs0eHAfSmviyNQXjIF7V4dmxO2eYYHC1KJaXW5GTYKcy0b59EpZCmwD5KjX-P40NAZofk2oK3v1kzy898FQI8Gl5w7Tyn9q1uZj8WGQecREM8uQNlgUjrsksl7L-9-MIQpag1xgTPEDji9Yrn49uQwL5PAl7Xp8azy4AEwiULjFVhfRkIlNo5aHAOXZ9K3C_6A7v8f9fHskLXmJy7IaaY1WXB65X2nscVCiXQrKLor-B6-wj3WJ9Sh3LltVSX7hkln7HaA_H8FUF-uaC6x1ZcCRzWpxUQS4hLY5IG_0YaWW1JYxXnNPIg9nnf39lAI2llsEmi26DDG0l9aQqGMhmM5CedSbMsb6JCEFbaJjIOSZNT-OJPZKEa1z1I-8hCDuIhMxYkwqBBp0iqswSBnFGvpigd4XxF0nL8zKK14gTngRTI2IT7uV6qp2D9AsX_3beOl1z50Y1vRE_VTALNY6jnJtWBeX34_yNyGM2zVOU8QsyHaWMQmmZI6SCFLlRS3kmiG9ztLO8hrTyFHVdHQcpOY6jPDfIHBLfn-PKGv-yOX42QjCjAVjysAvQv407SmMpWT3C13kMXnHf3YeMIru6hAkxpFE2QeHdmFgymB01qm80vnSoK2Y2ErfEU9DLjTuURnjcDNRryb_T7acCWcKdnQfP-y9AFi5HZEz_EmvLhJjakwUGaXgFPyKunDU9Z4S08-8tDeBKBvGS95DpA1KN46YYwT6wLykW7mZPBGlkC8Q6RCQ6ylA9Mo5PxRMvkztOlHL5aFSWfx63F9fDoZfk40izQIEbjvvjHYqVrMAAQa5gukHo2FmoRCQ_xUDx6nXxgSljTVCdzkMlpHRmtcQNhUCPl9fqV_O0Gj4X9rDMVVY1MlZOECCOrQPllHufIcZL_Cechf33Uq3mhNx3YyFcdH9wKcEMnrgH7cAMOP9Dm0Ld62P4kBNMVt6-BIibSsiAGAnpu78INp7bQKsv4D-e8Omwb8u1y1-B-81wWV9kFAAHA==\"}"
+ },
+ {
+ "type": "text",
+ "text": "The shoes slipped during placement and recovery, so I can’t confirm completion. I’m stopping the attempt and leaving both grippers open.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0b5218887c37459e016ae27011a1b8819fbd60fcf06f258943\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "leave both grippers open and verify",
+ "args": {
+ "grips": {
+ "left": 1,
+ "right": 1
+ },
+ "duration_s": 0.4,
+ "cameras": [
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_a839ec63918748f7900267391ba467f8|fc_0b5218887c37459e016ae27012f578819f923e53216d95c7b9"
+ }
+ ]
+ },
+ {
+ "id": "9c30e840",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:58:47.503Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224725.282645542] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"measured\": {\"left_arm\":[-0.23749713599681854,2.10660719871521,1.5987579822540283,-1.06011962890625,-0.017240097746253014,-0.6554499268531799],\"left_gripper\":[1.0024560825391249],\"right_arm\":[-0.09411459416151047,2.0698814392089844,1.4282174110412598,-0.929033637046814,0.001976696541532874,-0.07476774603128433],\"right_gripper\":[0.8706039027734237]},\n \"file\": [\"/tmp/kinex-observation-rljb8q34.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/9c30e840-1.png"
+ }
+ ]
+ },
+ {
+ "id": "63d3b8df",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:58:55.175Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Waiting on .32**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0b5218887c37459e016ae2701c7e70819f974ae8417b3b89fc\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Waiting on .32**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nAedaDUebpo2qDrcrzG-SVyjV5IRQE0Nuk2YtdzTrTkKqVtHFNnqKUsEo_OfOVbscLtGntqjCswMU4CR-_3gKOUvxyp8y8iCgbsBKlOJX2iou0vcH3W8hra6R3e_pjPC_p0UfRQMNauqg-FBBqjuVJGlh36_zkM6PnBZF130PCI8iDMMtbRvtX-wBh7uAajb8kZTzhl1kfYMyav3BBdOxgqDGv9nhR0oxFULgvEXqaibROPejJdjNdbbOkN6oRI7rolVJayCfHAdu9yMlQfCRcBtaGQhaCl7_H4UgGr6lkDCLkZvkk6IbfpNCPswmMq_MfLU6kJKB1QVI7flRyQ9KJt4VO3WAkVk6MoJTsnT332sseDMuTVK93cc_G_tmFQ8Ce2LFHHQWSg7BWCPgQqUM08tgI8gbVtkV7bXUgcg5HEZasMF0R6M_TAQV3cyL2MNTlJX3YEWrYRA7X6hJ8W6xPbMgXAH8sN-DCIKI2Gqr3GOJAImVaU4WUe3OKQpPyNcXbEF27nmwUgpW1pkgrpU7Wu2AXGjjAI8ymxURa_0YTPuW8nW12-55T4I-_ojPz6zXAXIIkgRaRM3jeu1w9kSWuVO6XaaNHC_fcJyuFfvduCBUFHvAopzoXvv9iHOoBujjeBVw6jhrcsv-P42TV0MuXAYj372BZwa8yQYEAJA68f-klXhOfWqCQH6ZHLJ2BROu9CuFUdbagvh_wgPuBddcBXIwrmcblH-4ISrLeWCdPflx2SSf-VL1LK2zpYNFOt3Pypd7dO6i0-1EzX8-P2MaotD1W21H_MCXD6cvbQZH4B_9wfd-95xZDYqduo-xN8noWcbK55dBscyR6x4suwJcCWVHP3YmFpvbnNwdYOSJQPRVZ5urz259JZXrUTER8selmvSciYX-7cZt6K0Z5jF2x7-jWY4JNOGnHquS2pM0Oh7VnlQLnffmplme6NWVKnSN8FDawtSsYw9B2SVAgqiXa5eonANbEYMz8t3PZ2P4YLz8SgIgPN8aInttKGLpOaWaZenKah6n3egZnPr63khCnsEh1KpA4Xs7M4CI_WvKdED1db6U_2jEUBaYzCn8jQGfDr49hmQ3ELmo4PUjuwUVnjLbSH06HeCynHDqeNhVMhgFLzdSe0xFLTV_g2QXvQPB6hW4kZ7VMwKLuwsJamaYL8we22PsPjF2bsEzErR-Isx5NoB07MnHcDm2aforUrJYZIxHY5nMiRzJjAbwPY_fbRf8z1qcfq2JmdH6SWwYQPz79hPE97kyX7KNILN4ez0Q_7u65E_iqAEztrskDJbcv-3dWEY-EwUehgFrTyzMXgwhFdeNGL8P-iA46e-fcUGtlXnh6lddch-BmjWT3S4VbHmJ2LQqbE9cGUfxiE4syZhejiwYAmw619kHVrCaQjBIxgRRoJiNwQ66Aj9e3dDKv7wlJP6m5OzQxgyj0MLmF2pNIR9PWqreR4JLh2CLf-j7Z1VwgRwvFCsV1tpsO1RxHEaje3olwc5Qh0CpuH7cinC7IOGhFoxPg4H1IA6yNGUOijKs3P6Xy0saZjztqVUnKVDYtqCVxf5CB411Rx-zFrsZCR7SQB4iNlTnpeTAb3KH0jCPU2uPGQ0caqn1-rQIdLeiuGtEU6czzF-yOfje1FVhCZYPQu6vs94P9QZuZRP2Wg\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "file": ".kinex/tools/cartesian_segment.py",
+ "description": "verify final open gripper positions",
+ "args": {
+ "grips": {
+ "left": 1,
+ "right": 1
+ },
+ "duration_s": 0.4,
+ "cameras": [
+ "head_camera"
+ ]
+ }
+ },
+ "call_id": "call_d7ec557521874c1294202cf117917e7d|fc_0b5218887c37459e016ae2701ca96c819faf99f1455deab1b2"
+ }
+ ]
+ },
+ {
+ "id": "bec6c641",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T21:58:59.921Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793224736.756986163] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"measured\": {\"left_arm\":[-0.23749713599681854,2.10660719871521,1.5987579822540283,-1.06011962890625,-0.017239799723029137,-0.6554496884346008],\"left_gripper\":[1.0018847584724426],\"right_arm\":[-0.09411459416151047,2.0705742835998535,1.4280035495758057,-0.929033637046814,0.001982568996027112,-0.07476842403411865],\"right_gripper\":[0.9748014916073192]},\n \"file\": [\"/tmp/kinex-observation-u51xe342.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/bec6c641-1.png"
+ }
+ ]
+ },
+ {
+ "id": "7b1145bb",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:59:09.908Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Adding motion timing logs**",
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+ "oldText": "states={d:list((await read(io,d+'.joint_state')).position) for d in ['left_arm','left_gripper','right_arm','right_gripper']}",
+ "newText": "states={}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n state=await read(io,d+'.joint_state')\n states[d]={'position':list(state.position),'velocity':list(state.velocity),\n 'stamp_s':state.header.stamp.sec+state.header.stamp.nanosec*1e-9}"
+ }
+ ]
+ },
+ "call_id": "call_3a291b8a1c42424b943bc3cd7928342b|fc_0b5218887c37459e016ae2702b4898819faa7716f28cc4c00f"
+ }
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+ "tool": "edit",
+ "timestamp": "2026-10-28T21:59:09.916Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 1 block(s) in .kinex/tools/cartesian_segment.py."
+ }
+ ]
+ },
+ {
+ "id": "d96ef9da",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T21:59:35.070Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": ".kinex/memos/dual_shoes.md",
+ "content": "# RoboTwin dual shoes\n\n## Interfaces and tools\n- Read refreshed profiles each episode. Stepped world, native 25 Hz (0.04 s/frame), 600 frames. Only world.wait advances time; reads do not.\n- `tools/dual_shoes_policy.py` captures head/left/right RGB in required order, calls helpers.run_policy at 25 Hz, returns fresh head image and measured joint feedback. Current policy returns 16 actions per inference even if max_actions=32. Task instruction embedded; override via args.task.\n- `tools/cartesian_segment.py` makes bounded world-TCP IK/joint segments with optional gripper targets, and returns cameras plus measured positions/velocities/stamps. Inputs: goals.{left,right}.{pose|delta|joints}, grips.{left,right} in native opening units, duration_s, cameras. It does NOT perform collision planning or certify arrival. The TCP offset is 0.12 m along flange +x for these profiles. All goals are planned before publication. Recheck calibration before reuse elsewhere.\n- Both grippers use 0 closed, 1 open; policy uses -1 open/+1 closed and helper converts. Closed empty feedback may bottom at ~0.18, not zero. A shoe can stall grip near .82, but that alone does not establish holding.\n\n## Important limitations\n- Policy achieved initial bilateral pickup but failed first placement: shoe slid toward near/right box edge, then vanished from head view. Continuing inference after loss produced wrist rotation and empty closing, not recovery. Stop and reassess instead of blindly extending policy.\n- Manual recovery was not successful. Depth-based targets require renewed perception after EVERY contact; shoes slide readily. Do not reuse previous attempt's object coordinates.\n- A 0.8–1.2 s trajectory endpoint can still have substantial tracking lag; gripper close while descending can displace the shoe. Inspect velocities and position error before grasping. Verify retention by camera during a small test lift before transport.\n- TCP +x approaches; fingers close along local y. Do not infer safe finger clearance solely from TCP height or simplified URDF geometry.\n- device_stop holds measured gripper opening, which may relax an object grasp; when intentionally holding an object, preserve closing target unless stopping for a fault.\n- Last observed attempt did not place either shoe in box. Arms were held, both grippers commanded open, measured ~1.002 / .975. No success claim or native verdict available.\n"
+ },
+ "call_id": "call_59053b706fc6404abf3467e748120ce4|fc_0b5218887c37459e016ae27030c860819fa45609d2accdf2f0"
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+ "type": "text",
+ "text": "Successfully wrote to .kinex/memos/dual_shoes.md"
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+ "timestamp": "2026-10-28T21:59:43.482Z",
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+ "oldText": "- Last observed attempt did not place either shoe in box. Arms were held, both grippers commanded open, measured ~1.002 / .975. No success claim or native verdict available.\n",
+ "newText": "- Finalization: command both openings to 1, allow settling, and verify feedback. Report placement uncertainty honestly; the world interface exposes no native verdict.\n"
+ }
+ ]
+ },
+ "call_id": "call_150f2ee852e34f54b4bbfcc5e2fd70c2|fc_0b5218887c37459e016ae2704da438819fb542e886d3a11931"
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+ "timestamp": "2026-10-28T21:59:47.604Z",
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+ "text": "Task not completed: the shoes slipped and were not placed in the shoebox. Both arms are held, and both grippers are open.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0b5218887c37459e016ae270529b9c819f8e15f783f04792a2\",\"phase\":\"final_answer\"}"
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new file mode 100644
index 0000000000000000000000000000000000000000..c413fb03148e937374da53c507e34cd2b00f12c3
--- /dev/null
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diff --git a/experiments/robotwin-native/kinex_policy-2/vla-io.json b/experiments/robotwin-native/kinex_policy-2/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..31e40c842fe46c6e8de1213c92350c91f646b0d8
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-2/vla-io.json
@@ -0,0 +1,9915 @@
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
+ "role": "user",
+ "content": [
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "trace_output": "{\n \"output\": \"[INFO] [1793224110.743159302] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.1642390340566635,1.7305915355682373,1.2296197414398193,-0.7650421261787415,-0.0084557319059968,-0.500076949596405],\"velocity\":[-0.12782171368598938,1.6054855585098267,1.0615302324295044,-0.5280291438102722,-0.0035553264897316694,-0.3419665992259979]},\"left_gripper\":{\"position\":[1.0039003437215632],\"velocity\":[-0.005440424535084854]},\"right_arm\":{\"position\":[0.16377829015254974,1.8440415859222412,1.4337947368621826,-0.8591420650482178,0.0009951238753274083,0.2373320609331131],\"velocity\":[0.13659954071044922,1.7306162118911743,1.2370691299438477,-0.5968512892723083,0.00857531651854515,0.10719234496355057]},\"right_gripper\":{\"position\":[0.9957916059277274],\"velocity\":[0.056688948957757515]}},\n \"time_s\": 1.28,\n \"file\": [\"/tmp/kinex-observation-v9kc6wpn.png\"]\n }\n}"
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/911260699f5d40a6b51e2d0c37bc9fa3-1.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/911260699f5d40a6b51e2d0c37bc9fa3-2.png"
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
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+ },
+ {
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+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "description": "lower toward shoe grasps",
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+ "text": "{\n \"output\": \"[INFO] [1793224119.654208670] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.2097044140100479,2.1003403663635254,1.4922027587890625,-0.9227323532104492,-0.012336636893451214,-0.6160438060760498],\"velocity\":[-0.007071767468005419,0.18269474804401398,0.0708129033446312,-0.004062924534082413,-0.0012147556990385056,-0.0011546239256858826]},\"left_gripper\":{\"position\":[1.0023565834218806],\"velocity\":[-0.03414872864430601]},\"right_arm\":{\"position\":[0.18805797398090363,2.2374651432037354,1.7380448579788208,-1.0270179510116577,0.0015673550078645349,0.25923529267311096],\"velocity\":[0.004303688183426857,0.19159452617168427,0.09309601783752441,0.0003027580678462982,-0.0012894750107079744,0.001212606206536293]},\"right_gripper\":{\"position\":[0.9993701875209808],\"velocity\":[0.01965627201240171]}},\n \"time_s\": 1.92,\n \"file\": [\"/tmp/kinex-observation-iacietm2.png\"]\n }\n}"
+ },
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+ "src": "observations/ba86406e-1.png"
+ }
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+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224119.654208670] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.2097044140100479,2.1003403663635254,1.4922027587890625,-0.9227323532104492,-0.012336636893451214,-0.6160438060760498],\"velocity\":[-0.007071767468005419,0.18269474804401398,0.0708129033446312,-0.004062924534082413,-0.0012147556990385056,-0.0011546239256858826]},\"left_gripper\":{\"position\":[1.0023565834218806],\"velocity\":[-0.03414872864430601]},\"right_arm\":{\"position\":[0.18805797398090363,2.2374651432037354,1.7380448579788208,-1.0270179510116577,0.0015673550078645349,0.25923529267311096],\"velocity\":[0.004303688183426857,0.19159452617168427,0.09309601783752441,0.0003027580678462982,-0.0012894750107079744,0.001212606206536293]},\"right_gripper\":{\"position\":[0.9993701875209808],\"velocity\":[0.01965627201240171]}},\n \"time_s\": 1.92,\n \"file\": [\"/tmp/kinex-observation-iacietm2.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 4,
+ "call_id": "dbde23f4b80e4c36a4d1ee1964ce8197",
+ "received_at_ns": 1793224130594217463,
+ "completed_at_ns": 1793224130741606098,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
+ "images": [
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+ ]
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
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+ },
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+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793224130.042645948] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.2132786065340042,2.2452938556671143,1.4555960893630981,-0.7601785659790039,-0.010994759388267994,-0.6320369839668274],\"velocity\":[-0.006282667629420757,0.41175612807273865,-0.1620422899723053,0.4812483489513397,0.005704400595277548,-0.0010892432183027267]},\"left_gripper\":{\"position\":[1.0031733025204053],\"velocity\":[-0.05907964977351102]},\"right_arm\":{\"position\":[0.18439644575119019,2.3707516193389893,1.7036454677581787,-0.8743376731872559,0.0015077369753271341,0.23946310579776764],\"velocity\":[-0.0019623737316578627,0.3756299912929535,-0.1430189311504364,0.43219083547592163,0.0005497047677636147,0.0012198584154248238]},\"right_gripper\":{\"position\":[0.9994854005900297],\"velocity\":[0.010186451783573086]}},\n \"time_s\": 2.56,\n \"file\": [\"/tmp/kinex-observation-bs7tom9w.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224130.042645948] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.2132786065340042,2.2452938556671143,1.4555960893630981,-0.7601785659790039,-0.010994759388267994,-0.6320369839668274],\"velocity\":[-0.006282667629420757,0.41175612807273865,-0.1620422899723053,0.4812483489513397,0.005704400595277548,-0.0010892432183027267]},\"left_gripper\":{\"position\":[1.0031733025204053],\"velocity\":[-0.05907964977351102]},\"right_arm\":{\"position\":[0.18439644575119019,2.3707516193389893,1.7036454677581787,-0.8743376731872559,0.0015077369753271341,0.23946310579776764],\"velocity\":[-0.0019623737316578627,0.3756299912929535,-0.1430189311504364,0.43219083547592163,0.0005497047677636147,0.0012198584154248238]},\"right_gripper\":{\"position\":[0.9994854005900297],\"velocity\":[0.010186451783573086]}},\n \"time_s\": 2.56,\n \"file\": [\"/tmp/kinex-observation-bs7tom9w.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 5,
+ "call_id": "70b302e8a4b246d28eb9f54dacf14892",
+ "received_at_ns": 1793224139030929475,
+ "completed_at_ns": 1793224139381860342,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
+ "images": [
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+ "/logs/agent/policy/70b302e8a4b246d28eb9f54dacf14892-2.png"
+ ]
+ }
+ },
+ "images": [
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+ "recorded_size": [
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+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-2/policy/70b302e8a4b246d28eb9f54dacf14892-2.png",
+ "recorded_size": [
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+ "recorded_sha256": "5e72faa7c9b13b19f352bff6dce9566566ff5e7fb9082fa813291fe3f4d00e4b",
+ "model_image": "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "4fa58949e911dc8cb08a1ad0869edcb6b221f0adf23f72217a79d1ee34a19a48",
+ "model_rgb_sha256": "e5c6d6ea62009b8bf746e23152a994e57a545f84b90be1848f600a381d20f549"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-0.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-1.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-2.png"
+ ],
+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/70b302e8a4b246d28eb9f54dacf14892-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "trace_output": "{\n \"output\": \"[INFO] [1793224149.569556886] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.22005799412727356,2.278794527053833,1.4649302959442139,-0.7562634348869324,-0.0094643235206604,-0.6023668050765991],\"velocity\":[-0.0010886157397180796,-0.41600582003593445,0.30070409178733826,-0.6667615175247192,-0.0043848371133208275,0.001474970020353794]},\"left_gripper\":{\"position\":[0.8442490317604758],\"velocity\":[0.05986423400992697]},\"right_arm\":{\"position\":[0.18073023855686188,2.4141697883605957,1.729750633239746,-0.8848705887794495,0.00425342982634902,0.21443425118923187],\"velocity\":[-0.0021621412597596645,-0.35253795981407166,0.3380318582057953,-0.6683180928230286,0.002519281581044197,-0.0016803189646452665]},\"right_gripper\":{\"position\":[0.8242001289671118],\"velocity\":[-0.007260924162851138]}},\n \"time_s\": 3.84,\n \"file\": [\"/tmp/kinex-observation-pf35xytz.png\"]\n }\n}"
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
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+ "content": [
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "trace_output": "{\n \"output\": \"[INFO] [1793224161.483818059] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.2337704449892044,2.106487512588501,1.5987350940704346,-1.0601452589035034,-0.017284579575061798,-0.655439555644989],\"velocity\":[-0.20414608716964722,-0.0711108148097992,-0.003488592803478241,-0.0486275851726532,-0.0066644977778196335,-0.30675390362739563]},\"left_gripper\":{\"position\":[0.8484432345086879],\"velocity\":[-0.03571745262227275]},\"right_arm\":{\"position\":[0.16433337330818176,2.2665646076202393,1.8794596195220947,-1.1764945983886719,0.0008793658344075084,0.19070172309875488],\"velocity\":[-0.11569812893867493,-0.1641731709241867,-0.04941084608435631,-0.07024315744638443,0.014065418392419815,-0.00043169036507606506]},\"right_gripper\":{\"position\":[0.8275782222097571],\"velocity\":[0.0033681344410235233]}},\n \"time_s\": 4.48,\n \"file\": [\"/tmp/kinex-observation-ys4yasbv.png\"]\n }\n}"
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/6659b26bb6d042ebb3cf7b67845612d6-1.png",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/6659b26bb6d042ebb3cf7b67845612d6-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "description": "rotate shoes toward box orientation",
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+ "text": "{\n \"output\": \"[INFO] [1793224173.489829010] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.5958328247070312,2.0936496257781982,1.5494917631149292,-1.0726386308670044,-0.014319771900773048,-1.5304045677185059],\"velocity\":[-0.8067498207092285,0.005487743765115738,-0.12532629072666168,-0.005442067980766296,0.033786822110414505,-2.0603280067443848]},\"left_gripper\":{\"position\":[0.8458616760644047],\"velocity\":[-0.19374703141775998]},\"right_arm\":{\"position\":[0.04124896600842476,2.116722822189331,1.6913503408432007,-1.1479504108428955,0.00006936372665222734,0.08349316567182541],\"velocity\":[-0.31583401560783386,-0.21932876110076904,-0.32688185572624207,-0.0031804367899894714,-0.017355522140860558,-0.15398237109184265]},\"right_gripper\":{\"position\":[0.8272719356146726],\"velocity\":[-0.14341287314891815]}},\n \"time_s\": 5.12,\n \"file\": [\"/tmp/kinex-observation-1x49af4e.png\"]\n }\n}"
+ },
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+ "src": "observations/6db711be-1.png"
+ }
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+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224173.489829010] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.5958328247070312,2.0936496257781982,1.5494917631149292,-1.0726386308670044,-0.014319771900773048,-1.5304045677185059],\"velocity\":[-0.8067498207092285,0.005487743765115738,-0.12532629072666168,-0.005442067980766296,0.033786822110414505,-2.0603280067443848]},\"left_gripper\":{\"position\":[0.8458616760644047],\"velocity\":[-0.19374703141775998]},\"right_arm\":{\"position\":[0.04124896600842476,2.116722822189331,1.6913503408432007,-1.1479504108428955,0.00006936372665222734,0.08349316567182541],\"velocity\":[-0.31583401560783386,-0.21932876110076904,-0.32688185572624207,-0.0031804367899894714,-0.017355522140860558,-0.15398237109184265]},\"right_gripper\":{\"position\":[0.8272719356146726],\"velocity\":[-0.14341287314891815]}},\n \"time_s\": 5.12,\n \"file\": [\"/tmp/kinex-observation-1x49af4e.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 9,
+ "call_id": "12b44283b5f5451790982b74f722322d",
+ "received_at_ns": 1793224183444508398,
+ "completed_at_ns": 1793224183741139181,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
+ "images": [
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/12b44283b5f5451790982b74f722322d-1.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/12b44283b5f5451790982b74f722322d-2.png"
+ ],
+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
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+ },
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+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793224182.890409604] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n1793224182.892589 [83] dq.builtin: Remote secure participant f8544f26:920a72fd:9ebfedca:1c1 not allowed\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.8931366205215454,2.072211265563965,1.4770663976669312,-0.9812818169593811,0.00011473950144136325,-2.233191967010498],\"velocity\":[-0.3547639846801758,0.018884602934122086,-0.08769574016332626,0.07969250530004501,0.04081038385629654,-0.3869875371456146]},\"left_gripper\":{\"position\":[0.8453784720464187],\"velocity\":[-0.04491062665527517]},\"right_arm\":{\"position\":[-0.08277181535959244,2.0239410400390625,1.5335749387741089,-1.090429425239563,-0.004047530237585306,-0.042060717940330505],\"velocity\":[-0.07115635275840759,-0.04377933591604233,-0.06454810500144958,-0.005736846476793289,-0.0161428265273571,-0.04591057449579239]},\"right_gripper\":{\"position\":[0.8220208341425116],\"velocity\":[-0.06982283666729927]}},\n \"time_s\": 5.76,\n \"file\": [\"/tmp/kinex-observation-xkceikpd.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224182.890409604] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n1793224182.892589 [83] dq.builtin: Remote secure participant f8544f26:920a72fd:9ebfedca:1c1 not allowed\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.8931366205215454,2.072211265563965,1.4770663976669312,-0.9812818169593811,0.00011473950144136325,-2.233191967010498],\"velocity\":[-0.3547639846801758,0.018884602934122086,-0.08769574016332626,0.07969250530004501,0.04081038385629654,-0.3869875371456146]},\"left_gripper\":{\"position\":[0.8453784720464187],\"velocity\":[-0.04491062665527517]},\"right_arm\":{\"position\":[-0.08277181535959244,2.0239410400390625,1.5335749387741089,-1.090429425239563,-0.004047530237585306,-0.042060717940330505],\"velocity\":[-0.07115635275840759,-0.04377933591604233,-0.06454810500144958,-0.005736846476793289,-0.0161428265273571,-0.04591057449579239]},\"right_gripper\":{\"position\":[0.8220208341425116],\"velocity\":[-0.06982283666729927]}},\n \"time_s\": 5.76,\n \"file\": [\"/tmp/kinex-observation-xkceikpd.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 10,
+ "call_id": "2506003b91934da69ee3da3593a385f3",
+ "received_at_ns": 1793224196191056937,
+ "completed_at_ns": 1793224196470318975,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
+ "images": [
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+ "/logs/agent/policy/2506003b91934da69ee3da3593a385f3-1.png",
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+ ]
+ }
+ },
+ "images": [
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+ "camera": "head_camera",
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+ "recorded_sha256": "1aaab896d9729dc563f7199313161869ef900dc761d2bbdc84dac67c6e6c4248",
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+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-2/policy/2506003b91934da69ee3da3593a385f3-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "52fb6007176e62ccd9ac5b2886608e67309421d8e4f643cce4218f473f0ccde5",
+ "model_image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "60dfc389e07b05cfd0328386f661b107aee9cec6adde6dba85a1005cca16ee7f",
+ "model_rgb_sha256": "37d102aefdcf31449e283734e767b16b878735dd12f725d3d00d743912f75ea2"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-0.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-1.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-2.png"
+ ],
+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2506003b91934da69ee3da3593a385f3-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/a662637dc00c4053bce66f6386c9cc67-1.png",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
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+ "type": "image",
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+ {
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+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/08df76e5ee8e44ceb18bf88de100670b-1.png",
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
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+ "content": [
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+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "trace_output": "{\n \"output\": \"[INFO] [1793224225.085355440] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.9609145522117615,2.103285789489746,1.3415217399597168,-0.9416824579238892,0.12990465760231018,0.26933538913726807],\"velocity\":[-0.012519998475909233,0.00815054215490818,-0.06386817991733551,0.14375868439674377,-0.025883832946419716,1.493956208229065]},\"left_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[-0.4523076117038727]},\"right_arm\":{\"position\":[-0.14984078705310822,1.793803095817566,1.2386841773986816,-1.0167691707611084,-0.005433639511466026,-0.09398231655359268],\"velocity\":[-0.0026481677778065205,-0.0341680571436882,-0.0263235941529274,0.00112156942486763,0.0046378737315535545,0.0006861891597509384]},\"right_gripper\":{\"position\":[0.8233322040601211],\"velocity\":[0.006881222361698747]}},\n \"time_s\": 7.68,\n \"file\": [\"/tmp/kinex-observation-79svv1xn.png\"]\n }\n}"
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+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-2/model-inputs/946d9313c464469d979b1b3a0e14f83a-2.png"
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "file": ".kinex/tools/dual_shoes_policy.py",
+ "description": "continue clearing box for second shoe",
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+ "text": "{\n \"output\": \"[INFO] [1793224240.559793638] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.9466960430145264,2.0996274948120117,1.3347556591033936,-0.9375165104866028,0.1452205628156662,0.4871319532394409],\"velocity\":[-0.0024265546817332506,-0.006117640063166618,-0.03794396296143532,0.018360305577516556,0.21688298881053925,-0.12456168234348297]},\"left_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[0.13143813068216498]},\"right_arm\":{\"position\":[-0.16619357466697693,1.7558674812316895,1.1857863664627075,-1.0019826889038086,-0.005586357321590185,-0.12964484095573425],\"velocity\":[-0.0030482755973935127,-0.009106620214879513,-0.005098237190395594,0.0009567426750436425,0.005949969869107008,-0.00099231768399477]},\"right_gripper\":{\"position\":[0.8231995837254958],\"velocity\":[0.002671432924795557]}},\n \"time_s\": 8.32,\n \"file\": [\"/tmp/kinex-observation-k1r8fgfw.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/3fc7db58-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224240.559793638] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.9466960430145264,2.0996274948120117,1.3347556591033936,-0.9375165104866028,0.1452205628156662,0.4871319532394409],\"velocity\":[-0.0024265546817332506,-0.006117640063166618,-0.03794396296143532,0.018360305577516556,0.21688298881053925,-0.12456168234348297]},\"left_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[0.13143813068216498]},\"right_arm\":{\"position\":[-0.16619357466697693,1.7558674812316895,1.1857863664627075,-1.0019826889038086,-0.005586357321590185,-0.12964484095573425],\"velocity\":[-0.0030482755973935127,-0.009106620214879513,-0.005098237190395594,0.0009567426750436425,0.005949969869107008,-0.00099231768399477]},\"right_gripper\":{\"position\":[0.8231995837254958],\"velocity\":[0.002671432924795557]}},\n \"time_s\": 8.32,\n \"file\": [\"/tmp/kinex-observation-k1r8fgfw.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 14,
+ "call_id": "223b71162e1645738a208a04e95f8b80",
+ "received_at_ns": 1793224307808607069,
+ "completed_at_ns": 1793224308095036284,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
+ "images": [
+ "/logs/agent/policy/223b71162e1645738a208a04e95f8b80-0.png",
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+ "/logs/agent/policy/223b71162e1645738a208a04e95f8b80-2.png"
+ ]
+ }
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+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
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+ {
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+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793224307.245751174] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.769152045249939,1.8209655284881592,1.2780230045318604,-0.8482129573822021,0.0019667400047183037,0.5423021912574768],\"velocity\":[1.039013147354126,-1.9829304218292236,-1.5112085342407227,0.9554992914199829,-0.028640955686569214,-0.41967734694480896]},\"left_gripper\":{\"position\":[0.6473405157977885],\"velocity\":[1.9632707942615857]},\"right_arm\":{\"position\":[0.01240176148712635,1.8635932207107544,1.3279516696929932,-1.0523301362991333,-0.002492120722308755,-0.16756686568260193],\"velocity\":[0.9300477504730225,0.4109690189361572,0.5477051734924316,-0.11741548031568527,-0.05728531628847122,-0.034550949931144714]},\"right_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[-0.06072843785990368]}},\n \"time_s\": 10.16,\n \"file\": [\"/tmp/kinex-observation-r9kvl_ew.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793224307.245751174] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.769152045249939,1.8209655284881592,1.2780230045318604,-0.8482129573822021,0.0019667400047183037,0.5423021912574768],\"velocity\":[1.039013147354126,-1.9829304218292236,-1.5112085342407227,0.9554992914199829,-0.028640955686569214,-0.41967734694480896]},\"left_gripper\":{\"position\":[0.6473405157977885],\"velocity\":[1.9632707942615857]},\"right_arm\":{\"position\":[0.01240176148712635,1.8635932207107544,1.3279516696929932,-1.0523301362991333,-0.002492120722308755,-0.16756686568260193],\"velocity\":[0.9300477504730225,0.4109690189361572,0.5477051734924316,-0.11741548031568527,-0.05728531628847122,-0.034550949931144714]},\"right_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[-0.06072843785990368]}},\n \"time_s\": 10.16,\n \"file\": [\"/tmp/kinex-observation-r9kvl_ew.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 15,
+ "call_id": "2a10787408564bdb99411fb4e99c61e0",
+ "received_at_ns": 1793224326560516347,
+ "completed_at_ns": 1793224327637127357,
+ "request": {
+ "task": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open",
+ "obs": {
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+ "recorded_size": [
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+ "recorded_sha256": "b5a6c6d312a1a28b6c92c8eaef1cd2233938d64753b97665e0c51db36e8ec8e0",
+ "model_image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-2.png",
+ "model_size": [
+ 224,
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+ }
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+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-0.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-1.png",
+ "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-2.png"
+ ],
+ "lang": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-2/model-inputs/2a10787408564bdb99411fb4e99c61e0-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use both arms to pick up the two shoes on the table and put them flat in the shoebox, with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. Leave both grippers open Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ ]
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+ "tool": "exec",
+ "arguments": {
+ "file": ".kinex/tools/dual_shoes_policy.py",
+ "description": "recover from lost grasp",
+ "timeout_s": 180
+ },
+ "start_ns": 1.793224324535e+18,
+ "session_event_id": "1b795bda",
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+ "text": "{\n \"output\": \"[INFO] [1793224326.069034591] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.7760891914367676,1.900067925453186,1.2369452714920044,-0.7888695597648621,0.012184467166662216,0.5715698003768921],\"velocity\":[0.5874661803245544,-1.2688400745391846,-1.1548991203308105,0.9930360913276672,-0.058601319789886475,-0.37943756580352783]},\"left_gripper\":{\"position\":[0.23286564004692165],\"velocity\":[3.2529833641919224]},\"right_arm\":{\"position\":[-0.04621698707342148,1.8618661165237427,1.3253315687179565,-1.070886492729187,0.0016111346194520593,-0.17026476562023163],\"velocity\":[0.5801291465759277,0.2907960116863251,0.4152977764606476,-0.12846273183822632,-0.05734775960445404,-0.23737221956253052]},\"right_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[-0.08739067918875]}},\n \"time_s\": 10.8,\n \"file\": [\"/tmp/kinex-observation-2l0llko8.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/9ec9a799-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793224326.069034591] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"actions_submitted\": 16,\n \"duration_s\": 0.64,\n \"ik_failure\": null,\n \"measured\": {\"left_arm\":{\"position\":[-0.7760891914367676,1.900067925453186,1.2369452714920044,-0.7888695597648621,0.012184467166662216,0.5715698003768921],\"velocity\":[0.5874661803245544,-1.2688400745391846,-1.1548991203308105,0.9930360913276672,-0.058601319789886475,-0.37943756580352783]},\"left_gripper\":{\"position\":[0.23286564004692165],\"velocity\":[3.2529833641919224]},\"right_arm\":{\"position\":[-0.04621698707342148,1.8618661165237427,1.3253315687179565,-1.070886492729187,0.0016111346194520593,-0.17026476562023163],\"velocity\":[0.5801291465759277,0.2907960116863251,0.4152977764606476,-0.12846273183822632,-0.05734775960445404,-0.23737221956253052]},\"right_gripper\":{\"position\":[0.18181818181818182],\"velocity\":[-0.08739067918875]}},\n \"time_s\": 10.8,\n \"file\": [\"/tmp/kinex-observation-2l0llko8.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/dual_shoes_policy.py",
+ "content": "\"\"\"Run one bounded, freshly observed RoboTwin policy segment; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nTASK = ('use both arms to pick up the two shoes on the table and put them flat in the shoebox, '\n 'with the shoe tips pointing to the left and the shoe initially on the left nearer the robot. '\n 'Leave both grippers open')\nCAMERAS = ['head_camera', 'left_camera', 'right_camera']\nDEVICES = ['left_arm', 'left_gripper', 'right_arm', 'right_gripper']\n\nasync def read_one(io, op):\n with io.subscribe(op, depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n opts = args()\n async with communication() as io:\n images = await asyncio.gather(*(read_one(io, c+'.image') for c in CAMERAS))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in DEVICES], task=opts.get('task', TASK),\n world='world', action_hz=25, max_actions=opts.get('max_actions', 32))\n states = await asyncio.gather(*(read_one(io, d+'.joint_state') for d in DEVICES))\n image = await read_one(io, 'head_camera.image')\n path = helpers.save_image(image)\n result['measured'] = {d: {'position': list(s.position), 'velocity': list(s.velocity)}\n for d,s in zip(DEVICES,states)}\n result['time_s'] = image.header.stamp.sec + image.header.stamp.nanosec * 1e-9\n finish(result, file=[path])\n\nasyncio.run(main())\n",
+ "sha256": "d890ab3b090f5172a2c3325732b9ad584757be88b50db928366d9e8f1100bf4c",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ }
+ ],
+ "coverage": {
+ "recorded_inputs": 15,
+ "recorded_outputs": 15,
+ "kinex_calls_associated": 15,
+ "original_temporary_image_paths_recorded": false,
+ "normalized_action_tensor_recorded": false,
+ "processor_tensors_recorded": false,
+ "executed_tool_source_at_call_verified": 15
+ },
+ "contract": {
+ "request": "policy.infer(obs, task). obs contains three ordered RGB image files; no joint state or agent conversation is sent to the VLA.",
+ "image_preprocessing": "RGB conversion, then OpenCV INTER_AREA resize to 224 x 224. Model images shown here are reconstructed from retained input pixels with the executed preprocessing.",
+ "request_paths": "The logger replaced temporary input filenames with retained image-copy paths. Original temporary path strings were not retained.",
+ "service_response": "actions, inference_s and call_id are reconstructed exactly from the logged values and the executed handler return. raw_actions is internal diagnostic data and is not returned to Kinex.",
+ "agent_response": "Kinex helpers.run_policy consumes the action array and returns actions_submitted, duration_s and ik_failure. The language agent sees the exec tool result below, including feedback and images selected by its own code.",
+ "output_layout": [
+ "left_joint_1",
+ "left_joint_2",
+ "left_joint_3",
+ "left_joint_4",
+ "left_joint_5",
+ "left_joint_6",
+ "left_gripper",
+ "right_joint_1",
+ "right_joint_2",
+ "right_joint_3",
+ "right_joint_4",
+ "right_joint_5",
+ "right_joint_6",
+ "right_gripper"
+ ],
+ "diagnostic_layout": "Left 6 joints, right 6 joints, left opening, right opening. Gripper conversion: 1 - 2 * clip(opening, 0, 1).",
+ "not_recorded": [
+ "normalized action tensor before denormalization",
+ "backbone processor tensors",
+ "exact original temporary filename strings"
+ ],
+ "backbone_prompt": "Reconstructed from the executed QwenOFT and QWen3 implementations; 16 action query markers are appended by the model, not by Kinex.",
+ "model_metadata": "experiments/robotwin-native/kinex_policy-2/policy/model.json",
+ "executed_sources": "policy-contract/sources.json"
+ }
+}
diff --git a/experiments/robotwin-native/kinex_policy-3/analysis.json b/experiments/robotwin-native/kinex_policy-3/analysis.json
new file mode 100644
index 0000000000000000000000000000000000000000..d09864b52ed0dee95a585f38f692271b82238894
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-3/analysis.json
@@ -0,0 +1,3 @@
+{
+ "observed": "Kinex made 72 policy inferences and wrote its own loop of up to four freshly observed chunks per tool call. When grasping stalled, it measured RGB-D geometry and wrote Cartesian corrections, then resumed the policy. Native success occurred at frame 1,277. Every VLA call retained the full original task instruction; this is observed control recovery, not language subtask rewriting."
+}
diff --git a/experiments/robotwin-native/kinex_policy-3/artifact-index.json b/experiments/robotwin-native/kinex_policy-3/artifact-index.json
new file mode 100644
index 0000000000000000000000000000000000000000..d04c483ad83ae90b7f3f6ec6abcb316538f0ff92
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-3/artifact-index.json
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diff --git a/experiments/robotwin-native/kinex_policy-3/detail.json b/experiments/robotwin-native/kinex_policy-3/detail.json
index ea16645ce908c8b6e07b0f15ada3191419603cf2..ad20d94ec1a30f2aacb60a17129e00a50849fcfc 100644
--- a/experiments/robotwin-native/kinex_policy-3/detail.json
+++ b/experiments/robotwin-native/kinex_policy-3/detail.json
@@ -481,8 +481,14 @@
"usage_source": "provider-raw"
},
"cost_note": "API equivalent sums the native Pi session cost estimates. Subscription billing is not reported.",
- "media_note": "All three native views and every frame retained. Frame timing is unchanged; playback starts at zero.",
+ "media_note": "Three 960 x 720 views side by side; every native sample once at 4x simulation speed.",
"artifacts": [
+ {
+ "name": "analysis.json",
+ "path": "experiments/robotwin-native/kinex_policy-3/analysis.json",
+ "bytes": 403,
+ "sha256": "4f53fd79f4b44e12cd7c057699c7b4889765d5bc0af7058443802c76909dfbd9"
+ },
{
"name": "artifacts.json",
"path": "experiments/robotwin-native/kinex_policy-3/artifacts.json",
@@ -531,6 +537,1302 @@
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"sha256": "e07de64776a6e0d4fe5ed1826bdbe8a070839c6729e14d456b70ea326acbf4a0"
},
+ {
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diff --git a/experiments/robotwin-native/kinex_policy-3/presentation/frame-mapping.json b/experiments/robotwin-native/kinex_policy-3/presentation/frame-mapping.json
new file mode 100644
index 0000000000000000000000000000000000000000..bd8ee1150b7e883b0132b723e890befb9ddb3f0a
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-3/presentation/frame-mapping.json
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+ "passed": true,
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+ "source_fps": 10,
+ "output_fps": 40,
+ "width": 2880,
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+ "native_frames": 512,
+ "published_frames": 512,
+ "source_sample_coverage": 1.0,
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+ "sha256": "e182700df6a1b1b83c33ea1bef6ee088dec66690418ac77fb59dab6b0adb4d67",
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+ "left_wrist.mp4": "40132ed56a64bbbaac618077114b8f34d5f0befdbc1b18291531ad36e88730b9",
+ "right_wrist.mp4": "947a864a65109bd4bcbb11329f06bf31cbed24ad1ea3312ce7ea5e5b9547c94a"
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+ "decode_ok": true,
+ "pts_verified": true,
+ "playback_kind": "simulation_time",
+ "resolution_kind": "independent_720_high",
+ "agent_observation_video": false,
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+ "width": 960,
+ "height": 720,
+ "channel": "spectator"
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+ "channel": "spectator"
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+ ],
+ "coverage_basis": "Every scheduled 10 Hz control-boundary sample, plus the terminal state.",
+ "frame_mapping": "Each captured sample exactly once; no appended or held frames.",
+ "sampling_note": "Samples follow the native simulation clock; model thinking adds no footage.",
+ "scope": "Live owner-only spectator views; no replay, rerender, upscaling or invented frames.",
+ "recording": {
+ "schema": "rosbridge/recording/1",
+ "run_id": "88c15864ae34",
+ "task": "robotwin/put-bottles-dustbin-aloha-agilex",
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+ ],
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+{
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+ "control_frequency_hz": 25,
+ "provider": "rosbridge",
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+}
diff --git a/experiments/robotwin-native/kinex_policy-3/transcript.json b/experiments/robotwin-native/kinex_policy-3/transcript.json
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+++ b/experiments/robotwin-native/kinex_policy-3/transcript.json
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+[
+ {
+ "id": "a9dc6588",
+ "role": "system",
+ "tool": null,
+ "timestamp": "2026-10-28T22:02:44.752Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ""
+ }
+ ]
+ },
+ {
+ "id": "beb46c08",
+ "role": "user",
+ "tool": null,
+ "timestamp": "2026-10-28T22:02:44.753Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "# Task: robotwin/put-bottles-dustbin-aloha-agilex\n\nuse arms to grab the bottles and put them into the dustbin to the left of the table\n\n## Work to do\n\nSolve the task efficiently using the running rosbridge environment. Follow the\ntask instruction above, including its completion requirements. Read `harness.md`\nand the device profiles for public interfaces, units and calibrated frames.\nReuse your saved tools, skills, and memos.\n\n## Limits\n\nYou have 1700 native action frames. The execution mode is `stepped`: physics is\nfrozen while idle. Use `world.wait` with `duration_s` to advance the native clock.\nJoint targets are ROS JointTrajectory messages; gripper targets use the units\ndeclared in their profiles. Reads and command publication do not advance physics.\nWaits are sequential; concurrent waits are rejected. A command or elapsed time\ndoes not prove arrival; inspect measured feedback. Device stop holds the device\nwithout ending the episode. The safety timeout is 28800 seconds.\nDo not launch or reset a simulation.\n\n## Completion\n\nReturn when finished. The owner finalizes the episode and reads its native\nverdict. An interrupted or rejected wait does not establish task success. The\nnative step limit stops physics even if your requested wait is longer.\n\n## Saved resources\n\nMaintain reusable code in `.kinex/tools/`, skills in `.kinex/skills/`, and concise working notes\nin `.kinex/memos/`. Improve existing files in place as you learn, replacing outdated\ncontent. Create a new file only when no existing resource fits; do not create\nper-attempt reflections or numbered copies. These files persist across fresh\nconversations. Update them before finishing your response.\n\n## Robot and device access\n\nUse Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place."
+ }
+ ]
+ },
+ {
+ "id": "f72ff3cf",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:02:48.559Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "ls",
+ "input": {
+ "path": "/workspace"
+ },
+ "call_id": "call_47c9c952efdf4279a8822d76ebaf0c0e|fc_0f3762851f8b7f2d016ae27107e970819fa14ce7b5606ac5ff"
+ }
+ ]
+ },
+ {
+ "id": "bf6a347f",
+ "role": "toolResult",
+ "tool": "ls",
+ "timestamp": "2026-10-28T22:02:48.569Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": ".kinex/\nharness.md\ninstruction.md"
+ }
+ ]
+ },
+ {
+ "id": "387b5e26",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:02:53.483Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/workspace/harness.md",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_0cbc3b6a32f84bb1af490d136e4ec1d1|fc_0f3762851f8b7f2d016ae2710c9a20819f823cc0ebbeec4bf4"
+ }
+ ]
+ },
+ {
+ "id": "c1dd1011",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T22:02:53.490Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Use Kinex's ROS device profiles in `.kinex/devices/` and the robot\nspecification in `.kinex/workspace.yaml`. The adapter refreshes them each episode.\nUse `kinex.communication` for typed topic publication, subscriptions and service\nrequests. Inspect operation schemas before acting. Load the provided devices;\nthey borrow the running simulator. Stop holds motion; it does not reset the world.\nImprove existing tools, skills, and memos in place.\n"
+ }
+ ]
+ },
+ {
+ "id": "1409771c",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:02:57.560Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "find",
+ "input": {
+ "pattern": "**/*",
+ "path": "/workspace/.kinex",
+ "limit": 200
+ },
+ "call_id": "call_f184be06388c4343939766bf1314b391|fc_0f3762851f8b7f2d016ae271113bc8819fa0bb16bcd5c8ead6"
+ }
+ ]
+ },
+ {
+ "id": "255aea4f",
+ "role": "toolResult",
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+ "timestamp": "2026-10-28T22:03:05.228Z",
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+ "text": "identity:\n id: robotwin-aloha-agilex\n name: RoboTwin ALOHA AgileX\n kind: arm\n model: ALOHA AgileX (dual ARX5)\n source: user\ndevices:\n source: user\nsafety:\n source: user\n max_joint_velocity: null\n max_cartesian_velocity: null\n keep_out_zones: []\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\n"
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+ "timestamp": "2026-10-28T22:03:05.228Z",
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+ "text": "name: world\nruntime:\n domain_id: 83\n observation: time\n nodes: []\n ready_timeout_s: 30\noperations:\n time:\n description: Authoritative world clock\n transport: topic\n direction: output\n endpoint: /clock\n type: rosgraph_msgs/msg/Clock\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n wait:\n description: Advance or await duration_s of world time (finite and nonnegative).\n Zero is an observation barrier. Waits are sequential; one requested while another\n is pending is rejected. A terminal episode rejects further progression without\n exposing benchmark results.\n transport: service\n direction: input\n endpoint: /world/wait\n type: kinex_interfaces/srv/Wait\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 120\n stop:\n description: Cancel the pending wait.\n transport: service\n direction: input\n endpoint: /world/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: world\ndescription: Scene reference and authoritative world clock of the RoboTwin 2.0 table.\n Kinex supplies frame transforms independently. This device exposes no task instructions\n or evaluator results.\nsource: default\ncalibrated_at: null\nmethod: unknown\nbounds: null\nsurfaces: []\nframes:\n base:\n parent: null\n translation_m: null\n rotation_xyzw: null\n"
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+ {
+ "type": "text",
+ "text": "name: left_arm\nruntime:\n domain_id: 83\n nodes:\n - entry: links.py\n factory: create\n ready_timeout_s: 30\noperations:\n joint_state:\n description: Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4,\n fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition\n stamp; do not infer motion completion from a sent command.\n transport: topic\n direction: output\n endpoint: /left_arm/joint_state\n type: sensor_msgs/msg/JointState\n qos:\n depth: 1\n reliability: reliable\n durability: transient_local\n timeout_s: 10\n joint_target:\n description: Joint trajectory over all 6 arm joints in radians, timed from receipt\n by strictly increasing time_from_start and finishing within 120 seconds; velocities,\n accelerations and effort must be empty. A zero header stamp selects now; a nonzero\n stamp must not start in the past. Points are absolute native joint positions,\n linearly interpolated at the native control period. Replacement clears pending\n references; invalid trajectories are ignored, so verify measured joint_state.\n transport: topic\n direction: input\n endpoint: /left_arm/joint_target\n type: trajectory_msgs/msg/JointTrajectory\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\n stop:\n description: Stop arm motion and hold the measured posture.\n transport: service\n direction: input\n endpoint: /left_arm/stop\n type: std_srvs/srv/Trigger\n qos:\n depth: 1\n reliability: reliable\n durability: volatile\n timeout_s: 10\nloaded: false\nmeta:\n created_at: '2026-10-24T00:00:00Z'\n updated_at: '2026-10-24T00:00:00Z'\ntype: joint\ndescription: ARX5 six-joint left arm of the RoboTwin ALOHA AgileX. Geometry is the\n sibling arm.urdf with flange (fl_link6) as the tip link; measured links are on TF\n as left_arm/\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 3, in \\n File \\\"/opt/kinex/packages/core/assets/python/kinex/runtime.py\\\", line 28, in describe\\n raise ValueError(\\\"operation must be device.operation\\\")\\nValueError: operation must be device.operation\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "4f40d7ee",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:03:27.441Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "inspect operation schemas",
+ "python": "from kinex import runtime,finish\nfinish({'operations':runtime.operations('left_arm'),'schemas':{n:runtime.describe(n) for n in ['left_arm.joint_target','left_gripper.target','head_camera.image','world.wait','policy.infer']}})"
+ },
+ "call_id": "call_fb8e753668db4805b8125a7566d3153f|fc_0f3762851f8b7f2d016ae2712e396c819f9b76c4480f733cb8"
+ }
+ ]
+ },
+ {
+ "id": "9528c567",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:03:29.025Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"\",\n \"result\": {\n \"operations\": {\"joint_state\":{\"description\":\"Measured positions of fl_joint1, fl_joint2, fl_joint3, fl_joint4, fl_joint5, fl_joint6 in radians with velocities and the world-clock acquisition stamp; do not infer motion completion from a sent command.\",\"transport\":\"topic\",\"direction\":\"output\",\"endpoint\":\"/left_arm/joint_state\",\"type\":\"sensor_msgs/msg/JointState\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"transient_local\"},\"timeout_s\":10},\"joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10},\"stop\":{\"description\":\"Stop arm motion and hold the measured posture.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/left_arm/stop\",\"type\":\"std_srvs/srv/Trigger\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10}},\n \"schemas\": {\"left_arm.joint_target\":{\"description\":\"Joint trajectory over all 6 arm joints in radians, timed from receipt by strictly increasing time_from_start and finishing within 120 seconds; velocities, accelerations and effort must be empty. A zero header stamp selects now; a nonzero stamp must not start in the past. Points are absolute native joint positions, linearly interpolated at the native control period. Replacement clears pending references; invalid trajectories are ignored, so verify measured joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_arm/joint_target\",\"type\":\"trajectory_msgs/msg/JointTrajectory\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"joint_names\":\"sequence\",\"points\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"},\"trajectory_msgs/msg/JointTrajectoryPoint\":{\"positions\":\"sequence\",\"velocities\":\"sequence\",\"accelerations\":\"sequence\",\"effort\":\"sequence\",\"time_from_start\":\"builtin_interfaces/Duration\"},\"builtin_interfaces/msg/Duration\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"left_gripper.target\":{\"description\":\"Native normalized opening (data) from 0 (closed) to 1 (open), the gripper entry of upstream's 14-D qpos action. The native setter runs on every 250 Hz substep and moves the drive target at most 0.1 per call toward it. A target persists until replaced or stopped; out-of-range targets are ignored, so verify joint_state.\",\"transport\":\"topic\",\"direction\":\"input\",\"endpoint\":\"/left_gripper/target\",\"type\":\"std_msgs/msg/Float64\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"data\":\"double\"},\"definitions\":{}},\"head_camera.image\":{\"description\":\"RGB image measurements with encoding, dimensions, row stride and acquisition timestamp in the Image header. The frame_id identifies the calibrated optical frame; use its stamp for tf2 lookup. A new subscriber receives the current frame at once, also while the world is paused, then one per camera sample; reading never advances world time.\",\"transport\":\"topic\",\"direction\":\"output\",\"endpoint\":\"/head_camera/image\",\"type\":\"sensor_msgs/msg/Image\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":10,\"message\":{\"header\":\"std_msgs/Header\",\"height\":\"uint32\",\"width\":\"uint32\",\"encoding\":\"string\",\"is_bigendian\":\"uint8\",\"step\":\"uint32\",\"data\":\"sequence\"},\"definitions\":{\"std_msgs/msg/Header\":{\"stamp\":\"builtin_interfaces/Time\",\"frame_id\":\"string\"},\"builtin_interfaces/msg/Time\":{\"sec\":\"int32\",\"nanosec\":\"uint32\"}}},\"world.wait\":{\"description\":\"Advance or await duration_s of world time (finite and nonnegative). Zero is an observation barrier. Waits are sequential; one requested while another is pending is rejected. A terminal episode rejects further progression without exposing benchmark results.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/world/wait\",\"type\":\"kinex_interfaces/srv/Wait\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"duration_s\":\"double\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"time_s\":\"double\",\"waited_s\":\"double\"},\"definitions\":{}},\"policy.infer\":{\"description\":\"Input: obs={images:[head RGB path,left wrist RGB path,right wrist RGB path]}, task: nonempty language. Output: actions[T,14] in left arm (6 radians), left grip (1), right arm (6 radians), right grip (1) order. Grip -1 releases; +1 closes. Also returns call_id and inference_s. All paths refer to this workspace.\",\"transport\":\"service\",\"direction\":\"input\",\"endpoint\":\"/kinex/policy/infer\",\"type\":\"kinex_interfaces/srv/Json\",\"qos\":{\"depth\":1,\"reliability\":\"reliable\",\"durability\":\"volatile\"},\"timeout_s\":120,\"request\":{\"request\":\"string\"},\"response\":{\"success\":\"boolean\",\"message\":\"string\",\"response\":\"string\"},\"definitions\":{}}}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "6e8a9890",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:03:34.406Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "devices",
+ "input": {
+ "calls": [
+ {
+ "deviceID": "world",
+ "action": "load"
+ },
+ {
+ "deviceID": "left_arm",
+ "action": "load"
+ },
+ {
+ "deviceID": "right_arm",
+ "action": "load"
+ },
+ {
+ "deviceID": "left_gripper",
+ "action": "load"
+ },
+ {
+ "deviceID": "right_gripper",
+ "action": "load"
+ },
+ {
+ "deviceID": "head_camera",
+ "action": "load"
+ },
+ {
+ "deviceID": "left_camera",
+ "action": "load"
+ },
+ {
+ "deviceID": "right_camera",
+ "action": "load"
+ },
+ {
+ "deviceID": "policy",
+ "action": "load"
+ }
+ ]
+ },
+ "call_id": "call_d6f9a12737fd4384a02d32e3fecb16e1|fc_0f3762851f8b7f2d016ae27135246c819f885d65be817da8a2"
+ }
+ ]
+ },
+ {
+ "id": "9f1cf7e7",
+ "role": "toolResult",
+ "tool": "devices",
+ "timestamp": "2026-10-28T22:04:23.811Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"world\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"left_arm\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"right_arm\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"left_gripper\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"right_gripper\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"head_camera\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"left_camera\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"right_camera\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}},\n {\"deviceID\":\"policy\",\"action\":\"load\",\"ok\":true,\"data\":{\"ready\":true}}\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "c0d3e301",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:04:27.466Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "device",
+ "input": {
+ "deviceID": "head_camera",
+ "action": "image"
+ },
+ "call_id": "call_08a2c45087ef49d7af70c4aeb1a6e046|fc_0f3762851f8b7f2d016ae2716b2b18819f83dcb3e0377cece5"
+ }
+ ]
+ },
+ {
+ "id": "a39bc7a3",
+ "role": "toolResult",
+ "tool": "device",
+ "timestamp": "2026-10-28T22:04:27.713Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"deviceID\": \"head_camera\",\n \"timestamp\": 0,\n \"frame_id\": \"head_camera/base\",\n \"width\": 320,\n \"height\": 240,\n \"file\": \"/tmp/kinex-observation-f8bbelvm.png\"\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/a39bc7a3-1.png"
+ }
+ ]
+ },
+ {
+ "id": "5d77fa9b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:04:30.616Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/policy.py",
+ "offset": 1,
+ "limit": 250
+ },
+ "call_id": "call_15ffac42fbe64903b44e51af6cfdf811|fc_0f3762851f8b7f2d016ae2716e1c8c819f9e899b8d8851cc84"
+ }
+ ]
+ },
+ {
+ "id": "46683f1a",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T22:04:30.622Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Policy execution: one inference turned into validated device commands.\"\"\"\n\nimport math\n\nfrom kinex import profile\nfrom kinex.lib.geometry import compose_rt, number, vector, xyzq_to_rt\nfrom kinex.lib.joints import JointModel, command as joint_command, measured_positions\n\nEND_EFFECTORS = {\"gripper\", \"suction\"}\n\n\nasync def run_policy(io, model, observation, command, task=None, world=\"world\", action_hz=10,\n max_actions=None, inference_args=None):\n \"\"\"Infer once and submit the valid action prefix to every commanded device.\n\n model serves a Json \"infer\" operation taking obs (and task) and returning\n actions or action. command lists {\"device\", \"space\", \"frame\", \"target_frame\"}\n entries in flat-vector split order; named action maps use device names.\n space \"device\" takes absolute joint values in URDF order, or end-effector\n values in [-1, 1] that release at -1 and grip at +1; \"pose\" (xyz + xyzw) and\n \"pose_delta\" (xyz + axis-angle) solve URDF IK for joint devices with a\n tip_link, frozen at the observation stamp. max_actions caps the horizon and\n action_hz paces actions on the world clock. Joint trajectories submit\n asynchronously; end-effector targets are paced by world waits before\n returning. Returns actions_submitted, duration_s and ik_failure\n (device, action_index, error) or None.\n\n Example: await helpers.run_policy(io, \"policy\", obs, [{\"device\": \"arm\"}, {\"device\": \"gripper\"}])\n \"\"\"\n import asyncio\n from kinex.communication import duration\n from kinex.helpers.frames import IDENTITY, transform_pose\n from kinex.lib.geometry import invert_rt, rt_to_pose\n plans = [_commanded(entry) for entry in command]\n if len({entry[\"name\"] for entry in plans}) != len(plans):\n raise ValueError(\"command must name each device once\")\n wait = f\"{world}.wait\"\n if any(entry[\"model\"] is None for entry in plans) and wait not in io.catalog:\n raise ValueError(\"end-effector policy sequences require a loaded world wait operation\")\n options = inference_args or {}\n if set(options) & {\"obs\", \"task\"}:\n raise ValueError(\"inference_args cannot override obs or task\")\n data = await io.request(f\"{model}.infer\", **options, obs=observation, **({\"task\": task} if task else {}))\n actions = data.get(\"actions\", [data[\"action\"]] if \"action\" in data else None)\n if not actions:\n raise ValueError(\"infer must return nonempty actions\")\n actions = actions[:max_actions or len(actions)]\n split = [_share(action, plans) for action in actions]\n count, failure, sequences = len(split), None, {}\n for entry in plans:\n name, spec = entry[\"name\"], entry[\"spec\"]\n samples = [item[name] for item in split[:count]]\n if spec.get(\"space\", \"device\") != \"device\":\n stream = io.subscribe(f\"{name}.joint_state\", depth=1)\n try:\n state = await stream.next(timeout_s=10)\n finally:\n stream.close()\n joints = entry[\"model\"]\n seed = measured_positions(state, joints.joints)\n base = f\"{name}/base\"\n ik_frame = f\"{name}/{joints.tip}\"\n target_frame = spec.get(\"target_frame\", ik_frame)\n reference = spec.get(\"frame\", base)\n # target_frame is an attached tool frame. Freeze its offset at the\n # observation stamp while resolving the policy's Cartesian chunk;\n # URDF FK of the measured joints places the tip.\n offset = await transform_pose(io, IDENTITY, ik_frame, target_frame, state.header.stamp)\n tool = rt_to_pose(compose_rt(xyzq_to_rt(joints.fk(seed)), invert_rt(xyzq_to_rt(offset))))\n current = await transform_pose(io, tool[\"translation\"] + tool[\"rotation\"], base, reference, state.header.stamp)\n converted = []\n for sample in samples:\n if spec[\"space\"] == \"pose_delta\":\n value = rt_to_pose(_delta_pose(xyzq_to_rt(current), sample))\n current = value[\"translation\"] + value[\"rotation\"]\n else:\n current = sample\n ik = rt_to_pose(compose_rt(xyzq_to_rt(current), xyzq_to_rt(offset)))\n goal = await transform_pose(io, ik[\"translation\"] + ik[\"rotation\"], reference, base, state.header.stamp)\n try:\n seed = joints.ik(goal, seed)\n except ValueError as error:\n failure = {\"device\": name, \"action_index\": len(converted), \"error\": str(error)}\n break\n converted.append(seed)\n samples = converted\n count = min(count, len(samples))\n sequences[name] = samples\n if count == 0:\n return {\"actions_submitted\": 0, \"duration_s\": 0, \"ik_failure\": failure}\n seconds = count / number(action_hz, \"action_hz\")\n prepared, scalars = [], []\n for entry in plans:\n name, prof = entry[\"name\"], entry[\"profile\"]\n samples = sequences[name][:count]\n if entry[\"model\"]:\n joint_command(prof, samples, entry[\"model\"].joints)\n fields = {\"joint_names\": entry[\"model\"].names,\n \"points\": [{\"positions\": value, \"time_from_start\": duration((index + 1) * seconds / count)}\n for index, value in enumerate(samples)]}\n operation = f\"{name}.joint_target\"\n else:\n target = _grip if prof[\"type\"] == \"gripper\" else _vacuum\n targets = [target(prof, value[0]) for value in samples]\n fields, operation = {\"data\": targets[0]}, f\"{name}.target\"\n scalars.append((operation, targets))\n prepared.append((operation, fields))\n\n await asyncio.gather(*(io.publish(operation, fields) for operation, fields in prepared))\n # End-effector targets persist. Timing belongs to this workflow and the world,\n # never a device-side duration or a background worker.\n if scalars:\n for index in range(count):\n if index:\n await asyncio.gather(*(io.publish(operation, {\"data\": values[index]})\n for operation, values in scalars))\n await io.request(wait, duration_s=seconds / count)\n return {\"actions_submitted\": count, \"duration_s\": seconds, \"ik_failure\": failure}\n\n\ndef _commanded(entry):\n \"\"\"One commanded device: its profile, joint model and share of an action vector.\"\"\"\n name = entry[\"device\"]\n prof = profile(name)\n kind = prof.get(\"type\")\n if kind not in END_EFFECTORS | {\"joint\"}:\n raise ValueError(f\"{name} is {kind}; run_policy commands joint, gripper or suction devices\")\n model = None if kind in END_EFFECTORS else JointModel(prof)\n # A gripper or suction tool takes one command value whatever it reports back.\n width = _cartesian_width(entry, prof)\n return {\"name\": name, \"profile\": prof, \"model\": model, \"spec\": entry,\n \"width\": width or (1 if kind in END_EFFECTORS else len(model.joints))}\n\n\ndef _share(action, plan):\n \"\"\"One action, split across the commanded devices in order.\"\"\"\n if isinstance(action, dict):\n missing = [e[\"name\"] for e in plan if e[\"name\"] not in action]\n if missing:\n raise ValueError(f\"action names no value for {', '.join(missing)}\")\n return {e[\"name\"]: vector(action[e[\"name\"]], e[\"width\"], f\"action for {e['name']}\") for e in plan}\n vector(action, sum(e[\"width\"] for e in plan), \"policy action\")\n shares, cursor = {}, 0\n for entry in plan:\n shares[entry[\"name\"]] = list(action[cursor:cursor + entry[\"width\"]])\n cursor += entry[\"width\"]\n return shares\n\n\ndef _cartesian_width(entry, prof):\n space = entry.get(\"space\", \"device\")\n if space not in {\"device\", \"pose\", \"pose_delta\"}:\n raise ValueError(f\"unknown policy space: {space}\")\n if space == \"device\":\n if \"frame\" in entry or \"target_frame\" in entry:\n raise ValueError(\"frame and target_frame require Cartesian policy actions\")\n return None\n if prof[\"type\"] != \"joint\" or not prof[\"model\"][\"tip_link\"]:\n raise ValueError(\"Cartesian policy actions require a joint device with a model tip_link\")\n return 7 if space == \"pose\" else 6\n\n\ndef _delta_pose(current, action):\n \"\"\"Translation and rotation increments use fixed reference-frame axes.\"\"\"\n action = vector(action, 6, \"pose_delta\")\n angle = math.hypot(*action[3:])\n scale = math.sin(angle / 2) / angle if angle else 0.5\n rotation = xyzq_to_rt([0, 0, 0, *[v * scale for v in action[3:]], math.cos(angle / 2)])\n return compose_rt(rotation, (current[0], [0, 0, 0]))[0], [a + b for a, b in zip(current[1], action[:3])]\n\n\ndef _action(value):\n value = number(value, \"action\")\n if not -1 <= value <= 1:\n raise ValueError(\"end-effector actions must be in [-1, 1]: -1 releases, +1 grips\")\n return value\n\n\ndef _grip(profile, value):\n \"\"\"Interpolate the grip joint from open to closed.\"\"\"\n grip = profile[\"grip\"]\n if not isinstance(grip, dict):\n raise ValueError(\"the gripper has no declared grip joint\")\n return grip[\"open\"] + (_action(value) + 1) / 2 * (grip[\"closed\"] - grip[\"open\"])\n\n\ndef _vacuum(profile, value):\n \"\"\"A vacuum level from release (0) to full vacuum (1); binary devices switch on above 0.\"\"\"\n value = _action(value)\n if profile[\"vacuum\"] == \"binary\":\n return 1.0 if value > 0 else 0.0\n if profile[\"vacuum\"] != \"proportional\":\n raise ValueError(\"the suction device declares no vacuum control\")\n return (value + 1) / 2\n"
+ }
+ ]
+ },
+ {
+ "id": "4d36eacd",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:04:39.786Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": "/workspace/.kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n"
+ },
+ "call_id": "call_4d7fed8cc7414eab8ba1033290e94354|fc_0f3762851f8b7f2d016ae2717123f4819fadd6e8b290d02cf8"
+ }
+ ]
+ },
+ {
+ "id": "2da2b6a2",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T22:04:39.790Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to /workspace/.kinex/tools/bottle_policy.py"
+ }
+ ]
+ },
+ {
+ "id": "b3441aa6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:04:43.547Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "approach bottles with policy",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
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+ "timestamp": "2026-10-28T22:06:49.542Z",
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+ "parts": [
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+ "type": "thinking",
+ "thinking": "**Preparing frame batches**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae271f36400819f88e651c7f7ae26bc\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Preparing frame batches**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nH2x4M_kDVUQ03C37ga7xZlWUrWfchQ34cJI4v3VNPDQVlzAO943FE2yUciDmsGk6hAx-sD87qgh9ESq1CMTGsmJNrWeLqnCS60Oia7khICi1Vps3O4TGyqxwn0CeH6xGQt3Uu2pK6v4YIm3Mo5PmklZ1feAviwr0q_RlX_mnamuio5ZejP5iGP7Vm6WOwC1EVCLpp4wR-FFQRxIea2Azr49I95TrFohhPqivBAKPdPaxW50jNmpKLtz334huLUGIa6jYTSvz6vnlJSuQcsiOL1SONYZv4oXT6Md-cHjIYOsCZD2qrIlBZUaD8p2rLoEcrytprOUNHTIRFJdXp2upG2N3u8Aq7eGApikjFWjp-vtpyvXn_2thM2AdM1pZCiOYkevCe-vdtRorulV6sdRJTMXXLVznvhMWdoyLsiKre5XXCm2KLBy0ocUfldcIDNqC71QA9IM2UXMDyMZe0hJt8GWb623-LhpRowAbzAVBEMq2wh_THKiPbyQjGsBPcsxrz9H72X2D9qbstnChfY-O0FJL99mmgzYTHpdl323SFMBKs4NthGGMLa2Hl_dYg0R2EIu7Y2BH_9lqOpaFugbQwqciNYQyDKcg9s3J3jiK4H8CopgljswIX3i_p3DmXwxTa-cI5IxgNMQRT9nNRhzvr-w6n8EBsj-InjRcr3CRqG5PlO739SfJlWMWE-_LkzrsW2XbuZRyljqkLooeQdym40_wABbqB4srzG0GCGIocd1Zsm0rr4PKvHRd6EEWpWTxfxJhtQuBflGx4rx9LEYLxHshuMycVUwHVkTiT60pqZDjHNEzbrG3wRvJoGzLeMGVE0_IeGche5UWZsbIO34v9C0D8kcgwiGCVHXXE805jNJ12AJf36RIKnT1ru1TzjUqr1C2OQVCvFOEMm8cRyZTMxyla9dWhqov5qX0hmFSesLu_WAmWtf-s3er2bcIJIPiPQ-qzomgn3r1w7zCdPMGPOMHYCorHdsljPYdmMZUjIfzjzKAefEujKrDLTMXx3lKHmZTz4veqETDRYpFoG_hv1cioVmOBf4YFAk3EufM5RhVytv2keD2ZGABwYe-tG9S4-3woAx169-HJ8Z_iqAQO_vK1wRehn_ZOceKSNwkYEBF9SdW8JbUsNvsigwv70-hBf9uAnWf-57j8a6k6BA30o9lucD6W51ZnOnijb-j3v8yHKDt4KD6kbzVk-BPBQxkUyiF1UebXpbeddsTWdCWEmaKiGMrdyujWEocVZzDyJItsQtlMrG10wtv47WJs49BS3avNr7NZNYXR12ko2VhsajMI54qLCH13N-tPShgLpCJSXQjQAkWDqv2YgmZwPaA647sXGGb6dzXrMgeFwHPBKWDPKN6urmztTVxXpJfG5Y1mLUBTFoLhcY0gBfmgsqSFi0PhdtXkVZ6Q0l2VDB6WK5VEhQNn4nOl2pBBDvHItbMizigCmxVqd3xruL5yCEcbGk_t7oDm_8rnK_TRqV0P4l1YNFWbXp_Q08Xro7Qfl6CIrLZEn0bCfWVXRVUFSmgfih1YiXfJD0VeBh2FDHYTtJgTMzXwsY6qJoJCKmEsRDirqQX-JFBgnjfsuWW9rw_8uGRXRfmH_RDKIc-3dA1NL5yZ-7H0nKjR6DUcYe7g_dSoFBRJldq9oXGPP3zRfzgtUhaxZ7LIcwWdZeQwVqQ1_v9xfxuHTutU8bSt8Sqvb2UQoHWg8JA2UmTFl_11jEXRUcNIgoETw9jLuFG0RQ5F_EkhicpIBLd1ZxKHKz2makQnDm9sJhLSRpQNAAOVsnIxd3DXBHeE5cVxW3O-7Ohh7wZS0Fj8w9vmbYUaWvMh8V7V57NJoFsICVXfvuI1vQJrv5YENLApTip-NsTTjx6TnfTvReuMJ28RVNTlNhZ9ivoM=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "edit",
+ "input": {
+ "path": "/workspace/.kinex/tools/bottle_policy.py",
+ "edits": [
+ {
+ "oldText": " images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))",
+ "newText": " results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)"
+ },
+ {
+ "oldText": "finish({'execution':result,'measured':measured},file=[out])",
+ "newText": "finish({'execution':results,'measured':measured},file=[out])"
+ }
+ ]
+ },
+ "call_id": "call_3fc7c51d338249b2ba9f726920fbc2f1|fc_0f3762851f8b7f2d016ae271f4a4a0819f981afe500847bca3"
+ }
+ ]
+ },
+ {
+ "id": "84f801fa",
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+ "tool": "edit",
+ "timestamp": "2026-10-28T22:06:49.554Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully replaced 2 block(s) in /workspace/.kinex/tools/bottle_policy.py."
+ }
+ ]
+ },
+ {
+ "id": "d8ff6e6b",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:06:56.770Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "The first bottle has been released into the left-hand bin. I’m moving on to the remaining two.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0f3762851f8b7f2d016ae271ff67ac819f8f99b74d1c43a621\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "approach second bottle",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 3
+ },
+ "timeout_s": 300
+ },
+ "call_id": "call_9604d6d5b58a426f9354f286cd550597|fc_0f3762851f8b7f2d016ae2720024bc819f83c29ac3793756cd"
+ }
+ ]
+ },
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+ "timestamp": "2026-10-28T22:07:08.571Z",
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+ "text": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
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+ "error": false,
+ "parts": [
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+ "type": "tool",
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+ "description": "grasp second bottle",
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+ },
+ "timeout_s": 300
+ },
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+ "timestamp": "2026-10-28T22:07:23.431Z",
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+ "text": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
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+ }
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+ "type": "tool",
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+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
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+ "timeout_s": 300
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+ {
+ "deviceID": "left_camera",
+ "action": "image"
+ }
+ ]
+ },
+ "call_id": "call_6ae8d23d62db471290fc5cc83c445d41|fc_0f3762851f8b7f2d016ae272782830819fa29cb90a965c3045"
+ }
+ ]
+ },
+ {
+ "id": "c5bb466a",
+ "role": "toolResult",
+ "tool": "devices",
+ "timestamp": "2026-10-28T22:08:58.894Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"right_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":23.04,\"frame_id\":\"right_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-d2hgo5gx.png\"},\n {\"deviceID\":\"left_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":23.04,\"frame_id\":\"left_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-540pfsj7.png\"}\n ]\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/c5bb466a-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/c5bb466a-2.png"
+ }
+ ]
+ },
+ {
+ "id": "925c05b6",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:09:06.047Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Needs helper documentation**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae2727e12bc819f888ab87e1c953a88\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Needs helper documentation**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nKBs5lizqFJ6HQMXH4Dpvr2XmAKoOS_HvN9Jh4gdmh8tgkBv_-HEmSAtCiE9o2dn7w9uyC4tjvGuoYYCqNQLkXC8yyEioxrjR8skw07klbPMVW08r7zcHS9U5hbjbpbm6xnCZEscu59PYnwbcuwbjofv2DPaz11NNQaaEXrwdRoJSyKqJEmDHbcH_tEI2jNPej24oMfvNQqppyDt6vm-pfuZYqY9VkH84u5UoFNQfGRA2UycsBTqvW_J0AGUCc4SCbcqABeVennNXUDnVidF5EXT67ieXL6PNezj7gyngu7g7dzLPExbW9zVPT13zBCfQeRbfJ5rVtNFXn7nyGXtm3_-pM_G4oMlYonI5YGKU-n6dHGfByKxVYn3IvoutJ_vgLzA0mWUWjlrltmfWNOlUoeuWQUNTAdcmKt-jSN7-eI1lipBoe0grISWS_B7tPPqwBA4vK9LDkMS-uWX3uY5QTAsDyAbusT_9thnYDmMkUiaKazpFTgXvvbETg347lqJlFbeMs_xVdEZ-6y6Lp0-OnBXAoSG-us9ofhBQBnNwCHAiKrbgCjbjgmunXrLC4BoXie1AmnDjpPEVZ0w1EXSwEkQpcqbZF8RgoQcHVqT9qIDFnHKwTKUnTXQD1nWNvFcXGk3xHU1pDng383qJvYO2PyUY2bTNunMUW4cWRozUo7BCUqZgxvLhe2U4XaZHnd7i914qm5uaqoJyUenKRoNQ15CwINZrPqQRWV98HRhRBeew-EfVZq6zVpiyQttNtlqWAWwDcEA6O_skcMRpttNGcO-Wat_k9xq12AfyCvTycs19XAnD2OkYn6kUVth5OAiIV8h9o_CMtofIJlNvB67rOrDAryw_U1BvQ9mJoPUXDaKUDxZFaUobZo9F37o40U6AbKJTRjJj6cggE7CPgHV1VRTb65N8kz2BkqO5XSqbkDth4CL9TCmvPBzIZ1FFBnEhQW_UoxyR_ktjeckuqeZ55OJbdpcN69hjgAMU2UeihnSkozlnb9jgATa60_VP1nqe6xgr3wOe0eZBkA4amjCDlsvsbX_XXxun4jfjNEeEraFnXpV8WYO_c1RqymhtrqlQnuAy7Bey612PD6e563_xv5x_8FwCcpzbe6JwPD4W3d098_XvGT-d1dTq_6ViOb1tvCKMveTuUKxZalfY-47NqXwbPlPU_m0N_cYeGJCGqogQuxwisazYEGxZdvMlAZDsCzDMWf6Zz9UHh8cJZjlodYHVASXvDifAb4TW95OnDfQHEC5gRpaxFyXhaEywhqgfiwPpBFGbIUkKD9jnbnTUwmeEAGYEHdGen7_ITuI_ytKPASAgXMuyd7WB7Bwcg03ZT-HiNeOsZ4Xk67g91bKXrAIqCUmrpYZE5D1ep01j8nmAyNuqSOAp0Ml45X4M49gdxSYh0IRrr6FEFuDCSUJmTUtwaKGM2kc5Z2a6maCWiZRcm97l_b0SM7qMbZUhMjI7XnaMJMXKAFM0XcKBd6mwTyvqjfJfJeiAQGt_WEK-BgGG-NUpLcgstD0qgKHxE7kOshDzr4rOxEx1K2xN81U_h5BNq-brzMy8IQCwHQx1MwitfdqYPcIS71WQ2m-HJdUkGK78C5oRGwKfqLfOWLLTHb6z0EnzM2pkJ7UxeRUAjwkAOw3chYSHpRrO3adpTxdV_tPU1Ws3ERxtHD64CDTdEnhOOP7-V5WNDv5mLzpP8TYuleMPP3TAMU2oHK_Odvv5f1gD6fSJRpUmvLX8KQG9CMNw==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/kinematics.py",
+ "offset": null,
+ "limit": null
+ },
+ "call_id": "call_1cecb62505c14f3786436348c18f27c2|fc_0f3762851f8b7f2d016ae27281d32c819f8adb85d0856b526e"
+ }
+ ]
+ },
+ {
+ "id": "be00e418",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T22:09:06.053Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Joint device kinematics from the device's resolved URDF.\"\"\"\n\nfrom kinex import profile\nfrom kinex.lib.joints import JointModel\n\n\ndef joint_model(device):\n \"\"\"Load a joint device's model without device I/O.\n\n joints lists the commanded joints in URDF document order with limits and\n rate limits; names holds their names. fk(positions, link=None) returns the\n link pose [x, y, z, qx, qy, qz, qw] in /base. ik(pose, seed,\n link=None, **options) returns commanded positions nearest the seed, or\n raises ValueError when no verified solution is found. link defaults to the\n model's tip_link. Measured links are also on TF as /\\\", line 198, in _run_module_as_main\\n File \\\"\\\", line 88, in _run_code\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 51, in \\n script()\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/host/run.py\\\", line 44, in script\\n exec(compile(_request[\\\"source\\\"], \\\"\\\", \\\"exec\\\"), module.__dict__)\\n File \\\"\\\", line 8, in \\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 195, in run\\n return runner.run(main)\\n ^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/runners.py\\\", line 118, in run\\n return self._loop.run_until_complete(task)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/workspace/.kinex/python/.pixi/envs/default/lib/python3.12/asyncio/base_events.py\\\", line 691, in run_until_complete\\n return future.result()\\n ^^^^^^^^^^^^^^^\\n File \\\"\\\", line 7, in main\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/__init__.py\\\", line 98, in finish\\n result = plain(result)\\n ^^^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 12, in plain\\n return {key: plain(item) for key, item in value.items()}\\n ^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 14, in plain\\n return [plain(item) for item in value]\\n ^^^^^^^^^^^\\n File \\\"/opt/kinex/packages/core/assets/python/kinex/lib/plain.py\\\", line 19, in plain\\n raise TypeError(\\\"images are not data; return them with finish(file=helpers.save_image(image))\\\")\\nTypeError: images are not data; return them with finish(file=helpers.save_image(image))\"\n}"
+ }
+ ]
+ },
+ {
+ "id": "8b84ca37",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:09:21.305Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "relative_pose",
+ "input": {
+ "child": {
+ "frame": "right_gripper:tcp"
+ },
+ "parent": {
+ "frame": "world:base"
+ }
+ },
+ "call_id": "call_cc7c16013b1b44baa451e49d73278b05|fc_0f3762851f8b7f2d016ae27290f89c819f983e5197662e6385"
+ }
+ ]
+ },
+ {
+ "id": "67392a33",
+ "role": "toolResult",
+ "tool": "relative_pose",
+ "timestamp": "2026-10-28T22:09:23.152Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"pose\": [\n 0.17734460057370624,\n 0.11554968976402508,\n 0.935607829738841,\n -0.03755450245693826,\n 0.01603563675270159,\n 0.9241871174268519,\n 0.3797508257810557\n ],\n \"timestamp\": 23.04\n}"
+ }
+ ]
+ },
+ {
+ "id": "8b6e8f12",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:09:31.463Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Closing on bottle neck**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae27297adcc819fb1c28cd697257c09\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Closing on bottle neck**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nKbvB845XXN65W8PYLJGiRWsps-RUZEiExW6y93ag4tBYaJ7lfpseK4RsRX5Qz8hK8i7wGsyHiuyaEluWyFKc4pPZqAB8wBXlqG04I87KYpo509YXd8aYgVKh9slOdKW7UuXWZOu8IY2pWd2QDxAt3UwRsmcNke_LbfhHrknabsbVZBBvWSBmOUu1qAU6hzBtaiv8y5NFcMjmsBVjfr8ShHXCbyVdNzEVQg4o6q5DEYT7jP5Ew33PGYVoQxkF2z3fegfb0TTr5J46coUuqthVBtkXjGaoLEYK-6zDJ529doCzUKD_P5tvhgU_RdDzAX73b0rvlZVzx7vJ5WQ8bSz7mMmx3keEizXo_BYARX-BAvu9UFHYRsgi1A7Xpx6UdHuV_gtdCQQIhaPs2xLb5p0D0fTNtm0eYYXMSXoc2VvkGFOTnweSR0XkaJ0UjcUQuP8corfu-_chd3HvDkD8w1b_WXJW-3bu7GfhIjOlDOw86GcQ3Y6jo7BwFz7gyk3RnrfMbqzmzhOco-BhGwgZuljqHKZFfONqE6vFCFBpJ1KMw5FpXWtzgAzMh22oyRojcoq02_00dt4A4dXrGJO5I_mj5y7BPwB2UGCYmZceRKf8HJpEOIdWLaUbANgP0x2l09EV4_iMg4PNdYwXOBwGJFJ_xa6MFObwFZfsUg4LKVc4yd9-JdbJyOiRTQiKNb6v75Nby2yarMhg_d0tP4tKpqRmZtKqWyiRhGL4k_gtJxTV-jfnklbY36DI2i5d8_LJ9ek8j2O9Gt3Qq9NGQlbhYdRkxZOYRN7RO2h93UEVu9mwwQu59YpF43j2Fo5Kwt6rBsTDAHHRvSluIu8Lg0Wh-Wu63_OClpPBDHhG_3VFD1sdHweUvRQIPWb-0zQF6XIqT3b75Hc4xszVG5F7ocKokv4q1rtaW2r44oTcooSTg7WWA6oT1-BVldEFOYGaXbcaO76elLwiw1TmFoW-yuftqarfkTjYr2qqRdOYJOE742umpNGTVh-umRKdT3HDWFVcO4WCKi2jT235WIskw3CCTALOh-J_aeRVBcrk3HJhKRlDxQx1CE0tY81NlGlWW2QRCuvGo7ULxGfG4YTqjs9LX1Q8FuAHadH5-igYNfbbz1xKD_OA6oDlzFxdkFxlA5f6bANToL5lB2TFWlCYe9BitsqJGlPRJzyiE8m-Sv-yWn8tSQeYYcmxwlmZraaMvrkruQoVCz7TrFnzyJ23dRlgmuftLbBwQcyEpTtnMZgP0ZyqNguQcggpZl7PHHfoXmSTu6f7mo3AXF3n2GhTi0xULzRuYSBCvaVlTQS2ZZmXoX-_ReR8-oiHhwgB2If3m9juo-ayakAva7mdB_1gZiLznYEl42xjTY6PlncpXHuAHtRk-uzum7NsAFe384oW5OaOGlc-MVZbh1Vwpym33ElCnkaVAXpqoiWJ2A1Jbpr9kF4RhPMriC2nQq5X14o_UG33cIoeX6wp9Tk_562XW9N1oFMBcntLZVj2c0TvnwmexD6NRtQSYof6LAVzYudJQdbUHGpSNPjEX0ZPera8xrE4LCwcsQOybu8hzJk3z0RpVpUp-fpeMpTI9ZuiPWqX2Enphx2B60uuqXASuwmtX4U5uGxEc30EDRg1Iyd8IyCMv89pAQwRHvTJ3PVD88BVBWOexubdS2l9dWexVaIOUFmUKk0ntg4YKy8XkwwIoF3j6Gtra_0JesCKvUfeMQkTDI_Id_Ic8G4C0ffVcU74AmahqotdVYuyqG4H-SACRLp0ppdLEP7zq2ypYuHoqc1yzNIwh0AenLxlUbYQdOta3uJp6WSQw_TyHfINjoK-ZgaYioo_xIlkhWL80vD7KK-wkRTHiH3EY3\"}"
+ },
+ {
+ "type": "text",
+ "text": "The policy is repeatedly readjusting around the second bottle without lifting it. I’ll check the grasp geometry and make a small corrective move.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0f3762851f8b7f2d016ae27298cc88819f9803eb19155c6de0\",\"phase\":\"commentary\"}"
+ },
+ {
+ "type": "tool",
+ "name": "read",
+ "input": {
+ "path": "/opt/kinex/packages/core/assets/python/kinex/helpers/images.py",
+ "offset": 1,
+ "limit": 120
+ },
+ "call_id": "call_f7ab5090a08e45f88c1e3ee3f46ec197|fc_0f3762851f8b7f2d016ae2729b5270819f8541eb2ac778215b"
+ }
+ ]
+ },
+ {
+ "id": "7c49d60e",
+ "role": "toolResult",
+ "tool": "read",
+ "timestamp": "2026-10-28T22:09:31.467Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "\"\"\"Camera images: current frames, pixel arrays for computation and files for finish().\"\"\"\n\nfrom kinex.lib.camera import array, frame, save\n\n\nasync def camera_frame(io, camera, timeout_s=None):\n \"\"\"The camera's current image and, for an rgbd camera, its depth (else None).\n\n Both come from one acquisition (equal stamps); reading never advances world time.\n\n Example: image, depth = await helpers.camera_frame(io, \"camera\")\n \"\"\"\n return await frame(io, camera, timeout_s=timeout_s)\n\n\ndef image_array(image):\n \"\"\"Native-order pixels of a sensor_msgs/Image as numpy: HxWx3 RGB or HxW mono8/16UC1.\n\n Example: pixels = helpers.image_array((await helpers.camera_frame(io, \"camera\"))[0])\n \"\"\"\n return array(image)\n\n\ndef save_image(image):\n \"\"\"Write a sensor_msgs/Image as a PNG, keeping 16-bit depth, and return its path.\n\n Example: finish({\"stamp\": stamp}, file=helpers.save_image(image))\n \"\"\"\n return save(image)\n"
+ }
+ ]
+ },
+ {
+ "id": "b76070dd",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:09:38.488Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "measure bottle surface points",
+ "python": "import asyncio,numpy as np\nfrom kinex import communication,helpers,finish\nasync def main():\n async with communication() as io:\n im,dep=await helpers.camera_frame(io,'head_camera'); d=helpers.image_array(dep)\n points=[]\n for u,v in [(255,40),(251,60),(252,75),(264,16),(196,30)]:\n z=float(np.median(d[v-2:v+3,u-2:u+3]))*.001\n p=[(u-159.5)*z/358.64218,(v-119.5)*z/358.64218,z,0,0,0,1]\n w=await helpers.transform_pose(io,p,'head_camera/base','world/base',im.header.stamp)\n points.append({'pixel':[u,v],'world':w})\n finish(points)\nasyncio.run(main())"
+ },
+ "call_id": "call_1c2b9d31790545ab85e7f86b1dac9c2b|fc_0f3762851f8b7f2d016ae2729f0e08819fb3434184063bad36"
+ }
+ ]
+ },
+ {
+ "id": "c31e83ed",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:09:41.009Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225380.251276711] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": [\n {\"pixel\":[255,40],\"world\":[0.15439748245692653,0.09413488315051766,0.8831011782276004,-0.9486832972651138,0,0,0.3162277683730379]},\n {\"pixel\":[251,60],\"world\":[0.15781593145252432,0.09514578947679242,0.8288593577752513,-0.9486832972651138,0,0,0.3162277683730379]},\n {\"pixel\":[252,75],\"world\":[0.16633835343869452,0.0877334788712053,0.7920501246471097,-0.9486832972651138,0,0,0.3162277683730379]},\n {\"pixel\":[264,16],\"world\":[0.16089142023078234,0.10003647064224619,0.9350273690691617,-0.9486832972651138,0,0,0.3162277683730379]},\n {\"pixel\":[196,30],\"world\":[0.04890933268045573,0.18571531116707019,0.833036499508408,-0.9486832972651138,0,0,0.3162277683730379]}\n ]\n}"
+ }
+ ]
+ },
+ {
+ "id": "fb50836a",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:09:56.101Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Lowering bottle for grasp**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae272a8fcd8819f91871bb9fc5739f1\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Lowering bottle for grasp**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nKt9nJdHFgj0vrWD0kS7laqBqkwd85Ta0wGtRxDNs-gNbaECRfAS3ibjG7MPl8D8PVYr0x46hvMlZT5LDLBT4dUcBMAJPMlWP2sQlaUk_ENtpmYdOE2tWYFulIk-BX8cfsA0S_2tjWcfwUvoxshsZ8rvymwneoLPawwg2kBBvkII3Dps8nQTRbFcFZAWgLrgsFyIX3O6DIIbpFXiyxYVPnpgsDTVNNWyLXVRNcCTirKYH3iyODtfbHd2f746jNG2UY-yzalJus4_AswF2lxMZUYMFI-4VEi6cfAch2flKKed9Zd5ZQ9lOap_EDedLCoGBtz9ISx5f_1-D8BAcDAXxwUES7YVtt5VMJy4OfI5H2PTy_Uc4uVRjPNemcMYxz0ukxxxAvRQhu5LzV-Wbf5sbyTeHy8fuHKfEspsWzLqM90JJ30Qa_UWr8GDHMAWq-IHW4H5dANt2V8RsZEfPXKdbCgnYB77SztsRcyqms2IE9NFVP2_vEj-wYU7Kc3R3bCIidZwAlGVkPC0Q-PZZOpIVW3dheHM-tW--YaZGSu2i2V8JnNT1GjVTxHqwDHZT8VnUyCmAPcNOhZfToB00nX0N4kEuRMURy3SwVUTmawAAlWxKkxaJM_1fNOQmI4xrSvhnkSsWKozPsGCVJjOWPjSeWP5mAoE00NCtUtP4yEFwllnD2fb5y3GiBFRbNRZFnJHxGL0fNaxIaEyq53k7gYsXRmKbq5--JibwKB4M8eCkfKxBY1Yt4DDnZJB2BYJs3jXCAJrIKOENxVE5VPXREawNqz6uVajYPqMAsPoi35VNEKgRf5VkP1na-Ho_CM8t29Nt6RxbWLuQQonBTPDix97OKCaNOBsSnC1penonwzgxh9dsRWoNH0dbAYzOcaluMj1B7Cqgz8Xik9Sm-R4KB9QGcdBBwDSebzmLFOzkRQWqNxLlDVZ2NaNLAwbdNNRaP9kolZhnH8emZx8SfNlObMgUBBgkT7xuzyDzPJSTp0aPknXd03TPitdIEIgoL5BMa7DBADH5JMIudzz7m1j0p-z9PHyjf5VsMZKBboVTx5o2I9vX-qaMhcilc3Oe1TkUAobVy-XshceB3uCPD2YV4ms3sCnbrvxtf2Ahipsv2_p86gp4mnDonbLb1VRQIiUDu0O1yLjkqX9Wh9RhcUn50PxotYJFI-O8tJ_FU4byhT7XRJ6HrAWfh3arwBZ7iwk9QRC9i2Xx25aGx3QAlknZzRtCyviqNqRGDuD4zrZJ9Ms7OpCV6sif7vUuBOt_Ur9h60qfr9sirt3Mo-MCcC-u0sNUm3Z8aWanrAb6xi-NDgVU5OOil0KXv_y1uNSRdem_5HmN_v5WXRTteoH02IpO4n3zfMsrvFmC-czu1-HYq3Im2APnw1x6A04KR87dzgu0Ay0LclT9AAZo7h60rqW6sj6Lk4CVDCpOANDJNL8C_VEmjObaacUw-W7tVywJynxFO80Pd26Kh_HvfLy67PazdPsNOyM1LMSFlIAzIR8iJQl4TOuMfgAQPxyqtGmYn3BjMiiinku-RNvQCpvFESa87Ty3K8fByBxTy0_iKXYmie-cUhqk7wy0rbsNOV3HL471SK6I5UcCUI6b4EB4Zxfe9ksN9W0nb78jzpU2mTAbZB7EVqaDDSaUS9Whey1A1aKZjhpOHP83tAltg8g4L2q1WcXECo0JP1DMDwJMhZ1WN02tcpdtrd0gnIqf_L3PccTSuWXqmPIyyMysk-gXgjbo5uTDL1chzPwmgnjq4gDojstW_CF9-MibiBBi3firATdlhke7PHRcroutzzSMteTTrWCwCICZdVf6dV2MHQ5djUAz44dPcLutS84aX4GBrM421lQYzPiSv_Z8sU4yCSB6y30PFl-tVrx8Dr8OWslEmGycF1Kto_OK9V0tN0O2QeBtkl7iziGp6yRG98u4_OYCilP1GQA88mnsdeXo-XouMGfNUYKsFAXxZgHoSv0qUCY4n_8S0gDrdKxSTlafzEh5yokeL57PftmaTSEYzd60yo36YYMYa_dloR0rAIzD9vuW40HBkvWzHrzwqo-taRIrMlASM2fBqU4o10vo72nCtR7Bo8UkKsi6EdgfPo5FnVsOxpSEwqi72xs_l_YWDIugjmUu6udbCmmwOJZgcWKQopiBNU64j-8umg1HgXY2oO7B41NkAHM8ZsGrfStV1C9bOdM8KAmg==\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": "/workspace/.kinex/tools/cartesian_adjust.py",
+ "content": "\"\"\"Small measured-seed Cartesian adjustment in world axes, with feedback.\"\"\"\nimport asyncio\nimport numpy as np\nfrom kinex import args,communication,helpers,finish\nfrom kinex.communication import duration\n\nasync def main():\n a=args(); arm=a.get('arm','right_arm'); grip=arm.replace('arm','gripper')\n async with communication() as io:\n with io.subscribe(arm+'.joint_state',depth=1) as s: state=await s.next(timeout_s=10)\n model=helpers.joint_model(arm); seed=list(state.position)\n source=arm+'/base'\n p=await helpers.transform_pose(io,model.fk(seed),source,'world/base',state.header.stamp)\n delta=a.get('delta',[0,0,0]); seconds=a.get('duration_s',1.0)\n points=[]; q=seed\n for k in range(1,21):\n target=list(p)\n for j in range(3): target[j]+=delta[j]*k/20\n local=await helpers.transform_pose(io,target,'world/base',source,state.header.stamp)\n q=model.ik(local,q)\n points.append({'positions':q,'time_from_start':duration(seconds*k/20)})\n if 'opening' in a: await io.publish(grip+'.target',{'data':a['opening']})\n await io.publish(arm+'.joint_target',{'joint_names':model.names,'points':points})\n await io.request('world.wait',duration_s=seconds)\n with io.subscribe(arm+'.joint_state',depth=1) as s: after=await s.next(timeout_s=10)\n with io.subscribe(grip+'.joint_state',depth=1) as s: gs=await s.next(timeout_s=10)\n im,_=await helpers.camera_frame(io,'head_camera'); path=helpers.save_image(im)\n finish({'joint_error_max':float(np.max(np.abs(np.array(after.position)-q))),'gripper':list(gs.position),'stamp':after.header.stamp},file=[path])\nasyncio.run(main())\n"
+ },
+ "call_id": "call_65952fe7f18d4210bdd8b30be321c82a|fc_0f3762851f8b7f2d016ae272ad437c819f8032b8cff8300d28"
+ }
+ ]
+ },
+ {
+ "id": "f8b4c666",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T22:09:56.105Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to /workspace/.kinex/tools/cartesian_adjust.py"
+ }
+ ]
+ },
+ {
+ "id": "a6e272e5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:10:02.379Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "lower right grasp onto bottle body",
+ "file": "/workspace/.kinex/tools/cartesian_adjust.py",
+ "args": {
+ "delta": [
+ 0,
+ 0,
+ -0.055
+ ],
+ "opening": 1,
+ "duration_s": 1.2
+ },
+ "timeout_s": 120
+ },
+ "call_id": "call_6b4cbeef40114d06a6a60bc209f29534|fc_0f3762851f8b7f2d016ae272b974c0819f85e60cb0aa753485"
+ }
+ ]
+ },
+ {
+ "id": "6d700e8b",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:10:09.527Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225403.850941899] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"joint_error_max\": 0.029814015667712357,\n \"gripper\": [1.0002539618448778],\n \"stamp\": {\"sec\":24,\"nanosec\":240000000},\n \"file\": [\"/tmp/kinex-observation-dpjfn7tq.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/6d700e8b-1.png"
+ }
+ ]
+ },
+ {
+ "id": "d98774b5",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:10:15.587Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "close right fingers around bottle body",
+ "file": "/workspace/.kinex/tools/cartesian_adjust.py",
+ "args": {
+ "opening": 0,
+ "duration_s": 0.64
+ },
+ "timeout_s": 120
+ },
+ "call_id": "call_9d95a73deae643ffa6efe1e6547cb34f|fc_0f3762851f8b7f2d016ae272c69690819faf5e90278d06a1d2"
+ }
+ ]
+ },
+ {
+ "id": "9e391af7",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:10:20.342Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225417.240176975] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"joint_error_max\": 0.0017054080963134766,\n \"gripper\": [0.7702317129481923],\n \"stamp\": {\"sec\":24,\"nanosec\":880000000},\n \"file\": [\"/tmp/kinex-observation-t9nje39b.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/9e391af7-1.png"
+ }
+ ]
+ },
+ {
+ "id": "a6342c68",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:10:24.017Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "verify second bottle lift",
+ "file": "/workspace/.kinex/tools/cartesian_adjust.py",
+ "args": {
+ "delta": [
+ 0,
+ 0,
+ 0.15
+ ],
+ "opening": 0,
+ "duration_s": 1.6
+ },
+ "timeout_s": 120
+ },
+ "call_id": "call_f71ba0d481a04f03b88317b94a56b309|fc_0f3762851f8b7f2d016ae272cf15e0819faf2fbf848dd2f83a"
+ }
+ ]
+ },
+ {
+ "id": "82bb4d8a",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:10:32.760Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225425.554537817] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"joint_error_max\": 0.06591878883004976,\n \"gripper\": [0.7720903618769213],\n \"stamp\": {\"sec\":26,\"nanosec\":480000000},\n \"file\": [\"/tmp/kinex-observation-iia0btox.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/82bb4d8a-1.png"
+ }
+ ]
+ },
+ {
+ "id": "b26c29ad",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:10:37.775Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "resume policy carrying second bottle",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 3
+ },
+ "timeout_s": 300
+ },
+ "call_id": "call_8905bc81ff3f4adabdc5ebe79cfb8c35|fc_0f3762851f8b7f2d016ae272dd22ec819fa90a5d72b55ec137"
+ }
+ ]
+ },
+ {
+ "id": "e8c5e432",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:10:49.481Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225439.446542299] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.42659056186676025,1.5380027294158936,0.42500537633895874,1.1043425798416138,0.28371018171310425,0.0038743172772228718],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[1.0026397732171146],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_arm\":{\"position\":[0.5330829620361328,1.7219411134719849,1.112260341644287,0.5872642397880554,-0.2544354200363159,-0.004977565724402666],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[0.7736253846775402],\"stamp\":{\"sec\":28,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-fdww3hao.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/e8c5e432-1.png"
+ }
+ ]
+ },
+ {
+ "id": "cee63ddf",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:10:54.325Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Checking second-left handoff**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae272ecdeb4819f9f3955350291c74a\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Checking second-left handoff**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nLuOkEsoseca6SC6LjMwEDS03gKtoeUJc12NJ-hN0aeW1XcnFBHdDVoWmqPXNAAhjuAsAvBPZPhk7LxHdkhyXt7SH7UjTaHNy_t9yEty9G1AQyYdDIWesdkck1Jm-2oqV7KBPnRiXerYPxtd4k-cv4c7qGlN2JN-I1JZNDdwHO0DZD72ftmer5mtFMRm_jwafQo8MC3a-rlwZGa2_CsW2ibUzJngYGOkjr8t-kgOzDcGOoBWBhyozLUMjrWxG3xxPVXvkYnJQ0JwHMU_dmZWnVah05fKE4yx6LoUa3I4Oo5P0IdAjQmZYUZu1T7_16i2PIJZtoeY-WQU7UJWGyKPhUMx0aa4gFoJaeBJJYu-04slLZBwXstLIlIBxgjU62yu2OHTM_ee3jBcEzYBcfBIrx-CBairz2-LiVsQtMj2zSwYr77sAyV5I1F7EEA0v8JyYUlLVGxWEqdS7LDK5riRYNVkng9gznv7mNFiF68Nd4TAk1RTCBnvg7AJ-TCgaCR5bBQPXvqb4ObVcfgbqQ7bVfmi_cTqjlrh0FnapFe0nW_GDw9jjgozeFoKuPmowSTSfjzIrd2V1x2AEkoY5MAruAyh-FXQkXMFJnab8ZvMhNLEriDFNEPjX-ojC-omN-FhiwnEY-WtVKj_eF8i9zGu4NeivGB7tT2e5Q7SbKrJQawOMwjdmK64G2fE3pnUNQeB9wL-aDivNuaPWCTNbClDF2XwdwfAXVYp_TK-n_2sSI0Scgxg6laIjsOtzHGm2yNZsFmCLgAAaQD9LqzqGQnkina2hZmeYN_ZLHJ4TJN4biSnEO51Cl7NhTgtFRa1c4AZEQfYUomtZ_PuqKdsZkD59EeCtsYqCTluIkeJD5qH7fMsSoTzhlXoLcASdA0jFpVEMCBJ_LBj3mnu2G0dS-SoUymY3VgDqWnEQZts0LQh4cw9DAF1Ip4xbxfSDAG14Hbbaa8xpdSoXkjj-B6vy7NqLP-38zQ8tne68MkODKblew_h-OibRQRyeFfEaVzxOQeG3n4cg7jQNX4AqRe4J7N3cClxHQXeSmERlkOCTbYOBEQm03SCf55enBbhvSHEIw1Ss8G4NCYUA22buGBsH6rX57ZdNxILx1vKBbpVwEF3ZHN6r29mbST0KLcY_utnL1qQQN0HLabuje1MYS_Jd6jAZmYs_sda5zkmn9al98n5IEapmXtlgoeQqgsBxQu8ajIbnKE5UfUD1RDXOLA2ZLF2Lln7xHRvlGCh-tl0kgyPi7O15nGyJmZR_K0bPSOo9T0AAHGaHUTBlj8_w-BIMH880oe6md_fZylkuWBxFAY6KF9QQR82_kw9fb6DP5_-ftr3GjTpUeI9ZuxSvlfvHFng4Y2Vdrp0dsB-JTwolSAWg2cfbcPyp6Vpcs1LbCHBt0sKmGhN8rdHtj6RORsPff73vqKQhK_gvMJ_716ZjdTXhRupYZZEGPdKv2PTt0aFscBTWfRIJctbV1ZXmsAAl-JqY6sqNBTH-zhtnM6sCxXv5wsQ6uxofZfPNVgINP0QkG1G-ljTfFQ96QWl4-BXoSy--XOTaaQu4y46xKDAJ3SadkRcDtNSMVlcTY7nNxdt7a3UtDARqdD5rfwL8BR-CVU2FbRhcgL4aH73PdtvQ2cjprbeY8=\"}"
+ },
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "coordinate bottle handoff",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 3
+ },
+ "timeout_s": 300
+ },
+ "call_id": "call_513968480e624903b64b7d32bd5ecd86|fc_0f3762851f8b7f2d016ae272ee2b38819f85402b3fbe0201e5"
+ }
+ ]
+ },
+ {
+ "id": "b2b427a8",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:11:06.044Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/b2b427a8-1.png"
+ }
+ ]
+ },
+ {
+ "id": "0c217e97",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:11:11.202Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "transfer second bottle to left arm",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 3
+ },
+ "timeout_s": 300
+ },
+ "call_id": "call_209942d314814af0a3935ff1969a37f8|fc_0f3762851f8b7f2d016ae272febd9c819fa24f33191bacfdda"
+ }
+ ]
+ },
+ {
+ "id": "7d1d9cc1",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:11:22.631Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225472.808813156] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.026490675285458565,1.736082911491394,0.7977779507637024,0.2831766903400421,0.1480584293603897,0.09788993000984192],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"left_gripper\":{\"position\":[0.7953653660687534],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_arm\":{\"position\":[0.10040103644132614,0.27128010988235474,0.19429327547550201,0.10107256472110748,-0.04703330993652344,0.006739610340446234],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_gripper\":{\"position\":[1.0037052739750256],\"stamp\":{\"sec\":32,\"nanosec\":240000000}}},\n \"file\": [\"/tmp/kinex-observation-a5hr5x4l.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/7d1d9cc1-1.png"
+ }
+ ]
+ },
+ {
+ "id": "e1c06199",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:11:27.973Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
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+ "timestamp": "2026-10-28T22:13:23.686Z",
+ "error": false,
+ "parts": [
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+ "type": "tool",
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+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 3
+ },
+ "timeout_s": 300
+ },
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+ }
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+ "timestamp": "2026-10-28T22:13:35.485Z",
+ "error": false,
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+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225605.287234952] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.565096914768219,1.9312561750411987,0.87837815284729,1.0531731843948364,0.2447700798511505,0.007962971925735474],\"stamp\":{\"sec\":47,\"nanosec\":280000000}},\"left_gripper\":{\"position\":[0.7343613329258832],\"stamp\":{\"sec\":47,\"nanosec\":280000000}},\"right_arm\":{\"position\":[0.5399152636528015,1.7094563245773315,1.1502386331558228,0.5641782283782959,-0.23741570115089417,0.016025565564632416],\"stamp\":{\"sec\":47,\"nanosec\":280000000}},\"right_gripper\":{\"position\":[0.7687718055465005],\"stamp\":{\"sec\":47,\"nanosec\":280000000}}},\n \"file\": [\"/tmp/kinex-observation-mrdkei1p.png\"]\n }\n}"
+ },
+ {
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+ }
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+ "file": "/workspace/.kinex/tools/bottle_policy.py",
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+ },
+ "timeout_s": 300
+ },
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+ "timestamp": "2026-10-28T22:13:52.264Z",
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+ },
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+ "src": "observations/b03aa410-1.png"
+ }
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+ },
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+ "id": "d373292a",
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+ "timestamp": "2026-10-28T22:13:59.389Z",
+ "error": false,
+ "parts": [
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+ "type": "tool",
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+ "input": {
+ "description": "release final bottle",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 2
+ },
+ "timeout_s": 300
+ },
+ "call_id": "call_5a45f91fa9284070a2f6703a914cff6e|fc_0f3762851f8b7f2d016ae273a6dd58819f9b611ba80442e0c2"
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+ "id": "173a92e8",
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+ "timestamp": "2026-10-28T22:14:08.177Z",
+ "error": false,
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+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225641.046960338] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.15262874960899353,1.6592247486114502,0.7895840406417847,0.1263832002878189,0.1300281286239624,0.11624398082494736],\"stamp\":{\"sec\":50,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.8292378729039973],\"stamp\":{\"sec\":50,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.004760715179145336,-0.0002186848287237808,0.007882915437221527,-0.0019864942878484726,-0.0006721738609485328,-0.0028068600222468376],\"stamp\":{\"sec\":50,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.9988697117025203],\"stamp\":{\"sec\":50,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-rrl4vh80.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/173a92e8-1.png"
+ }
+ ]
+ },
+ {
+ "id": "30f12063",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:14:13.247Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "exec",
+ "input": {
+ "description": "verify final bottle drop",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 1
+ },
+ "timeout_s": 180
+ },
+ "call_id": "call_3f898bf910f94d9ab627f231c69fbd0f|fc_0f3762851f8b7f2d016ae273b4b728819f816259eaeb97a555"
+ }
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+ "id": "117e96e8",
+ "role": "toolResult",
+ "tool": "exec",
+ "timestamp": "2026-10-28T22:14:18.724Z",
+ "error": true,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225654.926962489] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"error\": \"episode is done; call reset\",\n \"code\": \"operation_rejected\",\n \"details\": {\n \"operation\": \"world.wait\",\n \"type\": \"kinex_interfaces/srv/Wait\",\n \"response\": {\"success\":false,\"message\":\"episode is done; call reset\",\"time_s\":51.08,\"waited_s\":0}\n }\n}"
+ }
+ ]
+ },
+ {
+ "id": "35d4d768",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:14:23.424Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "device_stop",
+ "input": {
+ "reason": "Episode terminal during final bottle release; hold all motion."
+ },
+ "call_id": "call_0ffcc95b01634d5ba3c5d34705ff3111|fc_0f3762851f8b7f2d016ae273be0cc8819fb50b2fc5abe5b6c2"
+ }
+ ]
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+ {
+ "id": "55c6833b",
+ "role": "toolResult",
+ "tool": "device_stop",
+ "timestamp": "2026-10-28T22:14:23.509Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "left_arm: stopped (hold; affects left_arm)\nleft_gripper: stopped (hold; affects left_gripper)\nright_arm: stopped (hold; affects right_arm)\nright_gripper: stopped (hold; affects right_gripper)\nworld: stopped"
+ }
+ ]
+ },
+ {
+ "id": "bac6e89f",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:14:27.682Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "tool",
+ "name": "devices",
+ "input": {
+ "calls": [
+ {
+ "deviceID": "head_camera",
+ "action": "image"
+ },
+ {
+ "deviceID": "left_camera",
+ "action": "image"
+ },
+ {
+ "deviceID": "left_gripper",
+ "action": "joint_state"
+ }
+ ]
+ },
+ "call_id": "call_f8d80c20372e48c0bd0f4b01f1bda5ed|fc_0f3762851f8b7f2d016ae273c30650819f9739d5d718ba5171"
+ }
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+ },
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+ "id": "36fe7431",
+ "role": "toolResult",
+ "tool": "devices",
+ "timestamp": "2026-10-28T22:14:27.959Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"results\": [\n {\"deviceID\":\"head_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":51.08,\"frame_id\":\"head_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-uvvn9i6l.png\"},\n {\"deviceID\":\"left_camera\",\"action\":\"image\",\"ok\":true,\"data\":{\"timestamp\":51.08,\"frame_id\":\"left_camera/base\",\"width\":320,\"height\":240},\"file\":\"/tmp/kinex-observation-x2hsimsc.png\"},\n {\"deviceID\":\"left_gripper\",\"action\":\"joint_state\",\"ok\":true,\"data\":{\"positions\":[0.8879922032356262],\"velocities\":[0.5232531577348709],\"joint_names\":[\"left_gripper\"],\"timestamp\":51.08}}\n ]\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/36fe7431-1.png"
+ },
+ {
+ "type": "image",
+ "src": "observations/36fe7431-2.png"
+ }
+ ]
+ },
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+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:14:49.468Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "thinking",
+ "thinking": "**Saving learned cautions**",
+ "thinkingSignature": "{\"type\":\"reasoning\",\"id\":\"rs_0f3762851f8b7f2d016ae273c6bfec819f95423e5d1138e56a\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Saving learned cautions**\"}],\"content\":[],\"encrypted_content\":\"gAAAAABq4nPMdu-QfwBlXOuXkV5EmwryOQYLFVyhjhBn9w-pJo9a4fu8jUva33yE3vwxBrHY5k-dBD8G0KxYvBJmke6vk9dNyNoJZ1Hl-G66zC00S2315TaXLjn4lP3R1QetRr2MNbM4mmh3KwUGzseti4c3pkhFJeb8gnFgCNpQIlkNS0U6L3eMo-ybUEugyaqQ5ZwjgDlc8XNL21WO2ChVYqf5Y82b4N48FmD4idlC75RF84lU_hCy5Q5TYVrExztAAKgJOrAhU6rFSYk8XvtjoKvaG92689OxatL2XaXhAhZHRdT0Ve2-IlUWnrZhDku3V41NdxW8-1HSOCaVPVkHwu6Y3WioOhTLHWLUA6H03XopvtVXEGMbDW2u_3ZKRO2WTNQAzLDgNw5ofiBLuq2gPBmH1LPLT-4lOtqnkA1NbPPPHl91LDandm_EOQrM7FlS93b25QtZrV0N5sMQWcnH-1Tp_4HKq3n9h6vCmmGbiaOIOo8noKp0Vn6ULKhwErAhymAYoFnB_ovrbX1rOhOgmdbz8e6ENbzZ3Hh619fk9ONv1sTroE2xr7bnvsN2qmmnQ4yPPjgF16ffaOSIfML8wzdGEj7KVRnlZJM6KyF_AulKWKXtIFbEtVQzrftGW0u10xdu3zH5fb-LI_zBmKeTzNAQtfUYc7cIcurkf7Pz0Hw20X2XBTX2GJRDwkz0M7FxZleCArCuOSJtvDJrp0K1KdKgwmjUVMKhNQcDMldbQ6lsZtmKfTCRDpd6qjTK2x-jpHsHlJ5-vyEsSNiirUnn2zzDgY5EBzQx_RFUHqpF0HCEotgnbCsl-kE8F5yvjkf0SPbumGHPJ-BUmS7uwE0XtLQVB_aQyRodyHQisGbnXevRsF_E38aQXlZQ-bzk54Kqn_-ezlhXsDbfW5w3TeoMjjDJUQDqSIPWUNEQj140fWFzG37Hk5Yq5mMGK-oA5pr4HXKu8VWODECLMooLPGD-EsQFqm_rK3cjI5CkGEECp9HH-ckZZ46LeXcTni9fgmqYQnR2v07LLrTC2UFHUG1rxdWETWJynq6_MHhogoNvpqdhj0VppWAqRf002L-rpeMhDQyseYGIB3XA_3r6ncS5WzjOtVuxMp29GnR7N5SZWg7RejSctYBr6bVR5H5mPqljPzu7LFhr2KY0HiIrhSQPDxXm5vW9WFAgkdwOulZB2I8kYoJeIzMdPVeh_ugpMo39irUNNF8o5mwlcY2nz7NSsvMG8aQAVMsmdN_LktA0-RCjQICfnELzxNFN0SOg5wDDYO0kfaKRF9CFQF7m3ABGpiuavlOqCXuodk2qJn5jHvL3mTqJyQM_q_3JCq2zXHtn1RhA5BgBPdWXI9tqWyHTuF-XvAkIAY_8DoM0PifTSD_WBmUC827RzuFlxzvkH4Ws_iFYTnnYZJIXS0m8h8dlKbT66e6PcLktphIAmBOqOd4WuIVlUwxq1NbPRU68FD1fA4XAqTuODonvmhPAQQFDstftu6UQTXbFySMlEepCQvHWW8dbdZ0JDnmdc1R5Ocqziq0-XooJDUXR8fx_HBeTlkrfo_m4Pq4NEnp_0l_zHC5rKov-_JZN4_EPa2RsycNTim5nA9InzPfqNPEm2OYenZVxunOD09KSC3_LAttXDnzKxJwbrgAbHhqWhWy-ANYfk_Rw1qphxDjvGJ7if8y3m3rxQXqN4XcTaV-L_3M5wFidZ_s-7jztE-YcQWvjLQT8CULRI2BDtEgKaH9Opv_liBHH6kO7jqfRC2-Y6g3zNHwXn8PYt4DhuHEnRJAoErRtZPbpA0KMB62bVHOvBDxwxZNqYJzfxppUhc3CZyK1uNYKGlyuRKmZrc7VAlg1i_YOSJfyQq7xiYiPFJSQLhBuY_nhx9f004TWOtS6Hq4_OVwFS1pO2izX1cz849LHlX3mimMHyaygB2YK9jhraQEHUHHM7_WimPlScq_lO5S5HOCd8wmc9LJb7n3As8q2wJmKLkh2wuIUBbanpv7vch2XR4_j9LsPqINDmnHy67APDGLl-HRlw0cDb7KwvgLL4rmaWN9cUQLz\"}"
+ },
+ {
+ "type": "tool",
+ "name": "write",
+ "input": {
+ "path": "/workspace/.kinex/memos/put-bottles-dustbin.md",
+ "content": "# RoboTwin put-bottles-dustbin / ALOHA AgileX\n\n- Read refreshed profiles and harness each episode; load world, both arms/grippers, three cameras and policy. Borrow existing runtime, never reset.\n- `.kinex/tools/bottle_policy.py` takes `chunks` (1–4), `max_actions` (default 16), optional task. Fresh head/left/right RGB before every inference; uses helpers.run_policy with left_arm,left_gripper,right_arm,right_gripper at 25 Hz. Policy currently returns 16 actions per inference. Inspect returned image and measured feedback between batches.\n- Task language: `use arms to grab the bottles and put them into the dustbin to the left of the table`.\n- Observed strategy: left arm picks left water bottle and releases over bin; right picks the other bottles, transfers to left at table center; left deposits. Keep original instruction through handoffs.\n- Policy can stall cycling grasp adjustments near bottle neck. In this episode, measured head RGB-D and world TCP showed right grip at z≈0.936 m near cola neck. Opening then lowering 0.055 m, closing, and lifting 0.15 m made a verified grasp. These offsets are episode-specific, not universal geometry.\n- `.kinex/tools/cartesian_adjust.py` makes measured-seed interpolated IK adjustments in world axes. Args: arm (default right_arm), delta xyz metres, opening native 0 closed/1 open, duration_s. Plans all IK before publication, sequential world wait, returns joint error and image. Verify workspace clearance and object position before use.\n- For yellow bottle, stalled grip measured ≈0.764 opening; a 0.14 m upward correction with closed target lifted it visibly. Policy then completed handoff and bin transfer. Stalled fingers alone are not grasp evidence.\n- Final episode became terminal at world time 51.08 s (~1277/1700 frames), while last bottle fell into bin. Stop called; final head/wrist images showed clear tabletop and all three bottles in bin. Native verdict remains owner-only. A rejected wait alone is not success; no reset or further progression after terminal.\n"
+ },
+ "call_id": "call_d522a49336ac425e83b1247c6099038b|fc_0f3762851f8b7f2d016ae273c963f0819fa2e9ff45194ab43a"
+ }
+ ]
+ },
+ {
+ "id": "560fcc17",
+ "role": "toolResult",
+ "tool": "write",
+ "timestamp": "2026-10-28T22:14:49.471Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "Successfully wrote to /workspace/.kinex/memos/put-bottles-dustbin.md"
+ }
+ ]
+ },
+ {
+ "id": "4e3366dd",
+ "role": "assistant",
+ "tool": null,
+ "timestamp": "2026-10-28T22:14:54.719Z",
+ "error": false,
+ "parts": [
+ {
+ "type": "text",
+ "text": "All three bottles were moved into the left-hand dustbin. Final images show the table cleared. The episode ended and motion is stopped; the owner can read the native verdict.",
+ "textSignature": "{\"v\":1,\"id\":\"msg_0f3762851f8b7f2d016ae273dd2a40819f9bf02b93e2ddd81b\",\"phase\":\"final_answer\"}"
+ }
+ ]
+ }
+]
diff --git a/experiments/robotwin-native/kinex_policy-3/usage.json b/experiments/robotwin-native/kinex_policy-3/usage.json
new file mode 100644
index 0000000000000000000000000000000000000000..3348ac0082887a1971fa9f2360433fd0c38519aa
--- /dev/null
+++ b/experiments/robotwin-native/kinex_policy-3/usage.json
@@ -0,0 +1,470 @@
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diff --git a/experiments/robotwin-native/kinex_policy-3/vla-io.json b/experiments/robotwin-native/kinex_policy-3/vla-io.json
new file mode 100644
index 0000000000000000000000000000000000000000..579a64e27554e66ad22230fda4f7d922fe420319
--- /dev/null
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@@ -0,0 +1,47597 @@
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "image": [
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/7bc41563eaec49cbb4c8ba97482c6f03-1.png",
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/7bc41563eaec49cbb4c8ba97482c6f03-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225098.604469104] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.17091518640518188,1.6350430250167847,0.4255444407463074,1.179149866104126,0.7648664712905884,-0.008647430688142776],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"left_gripper\":{\"position\":[0.9978668635541743],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_arm\":{\"position\":[-0.0027706155087798834,0.044405095279216766,0.03004288487136364,-0.00893399678170681,-0.00360268447548151,-0.01240626722574234],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_gripper\":{\"position\":[0.9989379861138084],\"stamp\":{\"sec\":1,\"nanosec\":280000000}}},\n \"file\": [\"/tmp/kinex-observation-6vp60afz.png\"]\n }\n}"
+ },
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+ }
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225098.604469104] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.17091518640518188,1.6350430250167847,0.4255444407463074,1.179149866104126,0.7648664712905884,-0.008647430688142776],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"left_gripper\":{\"position\":[0.9978668635541743],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_arm\":{\"position\":[-0.0027706155087798834,0.044405095279216766,0.03004288487136364,-0.00893399678170681,-0.00360268447548151,-0.01240626722574234],\"stamp\":{\"sec\":1,\"nanosec\":280000000}},\"right_gripper\":{\"position\":[0.9989379861138084],\"stamp\":{\"sec\":1,\"nanosec\":280000000}}},\n \"file\": [\"/tmp/kinex-observation-6vp60afz.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
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+ ]
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+ "model_rgb_sha256": "dbeda1ec3e255f382bbea9f852b2b51646fb7a3343d7515d45782fe9d1286b04"
+ },
+ {
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+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/e1d9f7e8c3174c428ab7ab64fe89a302-2.png",
+ "recorded_size": [
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+ "recorded_sha256": "5d139e9e97f2cd7005860dddc97d183fe8c69a3ae326c249c1ca8063901725b9",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-2.png",
+ "model_size": [
+ 224,
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+ "model_sha256": "7868812e473c391f12ee02c8b98c6aed84c55d99057b93ee350ca5afc3bfe902",
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+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/e1d9f7e8c3174c428ab7ab64fe89a302-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
+ }
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+ "description": "grasp first bottle",
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+ "text": "{\n \"output\": \"[INFO] [1793225108.241901417] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.2326071709394455,2.19775128364563,0.6003415584564209,1.5847251415252686,1.0130494832992554,-0.008827410638332367],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9976785670627247],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_arm\":{\"position\":[-0.0006189350970089436,0.02812829613685608,0.026011895388364792,-0.01322526577860117,-0.0036317170597612858,-0.013324604369699955],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.9994191581552679],\"stamp\":{\"sec\":1,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-j_fa5gej.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/fd4209ee-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225108.241901417] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.2326071709394455,2.19775128364563,0.6003415584564209,1.5847251415252686,1.0130494832992554,-0.008827410638332367],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9976785670627247],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_arm\":{\"position\":[-0.0006189350970089436,0.02812829613685608,0.026011895388364792,-0.01322526577860117,-0.0036317170597612858,-0.013324604369699955],\"stamp\":{\"sec\":1,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.9994191581552679],\"stamp\":{\"sec\":1,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-j_fa5gej.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "d1c8383488e9dd29707f1cfbe07ee4483af5bbb9372e2f9ca22616691726948d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 4,
+ "call_id": "c877e2a4fe584ef8ae8582aff2c42ff9",
+ "received_at_ns": 1793225117969802065,
+ "completed_at_ns": 1793225118194269493,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
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+ "/logs/agent/policy/c877e2a4fe584ef8ae8582aff2c42ff9-1.png",
+ "/logs/agent/policy/c877e2a4fe584ef8ae8582aff2c42ff9-2.png"
+ ]
+ }
+ },
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+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/c877e2a4fe584ef8ae8582aff2c42ff9-0.png",
+ "recorded_size": [
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+ "recorded_sha256": "a6727235c24a498ed20e43cbc792f9cf7a02ba9e8f861977597f934f0fe113b4",
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225117.440113886] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.16130757331848145,2.3021020889282227,0.6999467015266418,1.596453070640564,0.9746558666229248,-0.008491234853863716],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"left_gripper\":{\"position\":[0.9969899979504673],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_arm\":{\"position\":[0.0009079572046175599,0.0105008939281106,0.012661953456699848,-0.005467085167765617,-0.0024430479388684034,-0.004466819576919079],\"stamp\":{\"sec\":2,\"nanosec\":560000000}},\"right_gripper\":{\"position\":[0.9996547996997833],\"stamp\":{\"sec\":2,\"nanosec\":560000000}}},\n \"file\": [\"/tmp/kinex-observation-qua6o2r9.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "d1c8383488e9dd29707f1cfbe07ee4483af5bbb9372e2f9ca22616691726948d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 5,
+ "call_id": "d0b99cb88ced45e181c421bd153899b6",
+ "received_at_ns": 1793225127631195172,
+ "completed_at_ns": 1793225127897656374,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
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+ }
+ },
+ "images": [
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+ "camera": "head_camera",
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+ "recorded_sha256": "3130d2af6a3cb834a1d392b8c5ddf1fd9895b4cb586f68dd380699ea73bb55e0",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-1.png",
+ "model_size": [
+ 224,
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+ "model_sha256": "583c56ba3b77a4d95f9160cf2b431a483442423c6f2427652c834e7ea288c145",
+ "model_rgb_sha256": "5c74871b6283cf2aa1e198f418c7d7db332b240af1753819220f7fe4968cae97"
+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/d0b99cb88ced45e181c421bd153899b6-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "0f6100d8465c97da6a44393caed8cd985bfbe3ba7e24a3aa136d2599de35ae0b",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-2.png",
+ "model_size": [
+ 224,
+ 224
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+ "model_sha256": "a7747df0c65fcde218bd591dd92fb80916423c162b7f6cf551408959bd46be82",
+ "model_rgb_sha256": "1fc63e98819bf66ad621dce440668ba1fa0ceb7da214671bd00e4c629df1a557"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/d0b99cb88ced45e181c421bd153899b6-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
+ }
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
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+ "content": [
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+ "type": "image",
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/51cadaa767f149959eaf85935a0e47a7-0.png"
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225147.844119024] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.033281002193689346,2.1960554122924805,0.8281853199005127,1.339977502822876,0.8343932032585144,0.011353131383657455],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.7190690501169725],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"right_arm\":{\"position\":[-0.007424312178045511,-0.0003993757418356836,0.004544554278254509,-0.004379557445645332,-0.0014686515787616372,-0.0007548821740783751],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.9998474310744893],\"stamp\":{\"sec\":4,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-t3n8uhxl.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225147.844119024] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.033281002193689346,2.1960554122924805,0.8281853199005127,1.339977502822876,0.8343932032585144,0.011353131383657455],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.7190690501169725],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"right_arm\":{\"position\":[-0.007424312178045511,-0.0003993757418356836,0.004544554278254509,-0.004379557445645332,-0.0014686515787616372,-0.0007548821740783751],\"stamp\":{\"sec\":4,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.9998474310744893],\"stamp\":{\"sec\":4,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-t3n8uhxl.png\"]\n }\n}"
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+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/90d7119982ce4c0b92176305d09b931c-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225156.730609796] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.046208642423152924,1.9962632656097412,0.8336367607116699,1.1062297821044922,0.8027006387710571,0.033829692751169205],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"left_gripper\":{\"position\":[0.7186871739951047],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"right_arm\":{\"position\":[-0.006255677435547113,-0.0012278046924620867,0.004855142906308174,-0.003364852862432599,-0.0009206954855471849,0.00035223999293521047],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"right_gripper\":{\"position\":[0.9999183470552618],\"stamp\":{\"sec\":5,\"nanosec\":120000000}}},\n \"file\": [\"/tmp/kinex-observation-pynpk0x1.png\"]\n }\n}"
+ },
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+ }
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+ "is_error": false
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225156.730609796] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.046208642423152924,1.9962632656097412,0.8336367607116699,1.1062297821044922,0.8027006387710571,0.033829692751169205],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"left_gripper\":{\"position\":[0.7186871739951047],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"right_arm\":{\"position\":[-0.006255677435547113,-0.0012278046924620867,0.004855142906308174,-0.003364852862432599,-0.0009206954855471849,0.00035223999293521047],\"stamp\":{\"sec\":5,\"nanosec\":120000000}},\"right_gripper\":{\"position\":[0.9999183470552618],\"stamp\":{\"sec\":5,\"nanosec\":120000000}}},\n \"file\": [\"/tmp/kinex-observation-pynpk0x1.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
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+ "model_size": [
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+ },
+ {
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+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/8c62c26ec68a46afa87e0f42656b6796-2.png",
+ "recorded_size": [
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+ ],
+ "recorded_sha256": "616406ee4b546b85ea81adb9bf9aeda2ca9742a1ab845cafd21a91f3abd01d1c",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-2.png",
+ "model_size": [
+ 224,
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+ "model_sha256": "8e996d5070cad85e5a3a66f3be9aebce107dca6cc7a163c1df6a11faf3f48cee",
+ "model_rgb_sha256": "126243c103da48a0d01e8a96574876d3e90f99ba4bc90944782fbd3460242017"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/8c62c26ec68a46afa87e0f42656b6796-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "description": "transfer first bottle toward bin",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
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+ "parts": [
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+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225165.927323670] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.11342136561870575,1.8159968852996826,0.8143070936203003,0.5716375708580017,0.44105952978134155,0.07969070971012115],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"left_gripper\":{\"position\":[0.7133738940412349],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"right_arm\":{\"position\":[-0.0034179254435002804,-0.0024828969035297632,0.004087744280695915,-0.0026405593380331993,-0.0003792409843299538,-0.0020172230433672667],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"right_gripper\":{\"position\":[0.9999658953059803],\"stamp\":{\"sec\":5,\"nanosec\":760000000}}},\n \"file\": [\"/tmp/kinex-observation-k5rx3d1g.png\"]\n }\n}"
+ },
+ {
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+ "src": "observations/44263e03-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225165.927323670] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.11342136561870575,1.8159968852996826,0.8143070936203003,0.5716375708580017,0.44105952978134155,0.07969070971012115],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"left_gripper\":{\"position\":[0.7133738940412349],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"right_arm\":{\"position\":[-0.0034179254435002804,-0.0024828969035297632,0.004087744280695915,-0.0026405593380331993,-0.0003792409843299538,-0.0020172230433672667],\"stamp\":{\"sec\":5,\"nanosec\":760000000}},\"right_gripper\":{\"position\":[0.9999658953059803],\"stamp\":{\"sec\":5,\"nanosec\":760000000}}},\n \"file\": [\"/tmp/kinex-observation-k5rx3d1g.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "d1c8383488e9dd29707f1cfbe07ee4483af5bbb9372e2f9ca22616691726948d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 10,
+ "call_id": "75f25b5f0a2f4156a355a812471a487e",
+ "received_at_ns": 1793225176113839189,
+ "completed_at_ns": 1793225176396505867,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
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+ "/logs/agent/policy/75f25b5f0a2f4156a355a812471a487e-1.png",
+ "/logs/agent/policy/75f25b5f0a2f4156a355a812471a487e-2.png"
+ ]
+ }
+ },
+ "images": [
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+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/75f25b5f0a2f4156a355a812471a487e-0.png",
+ "recorded_size": [
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+ "recorded_sha256": "e9bd6f864f17b2b63650b9d394ec110416c4d66e5236af9ba80d26fe2973e97f",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/75f25b5f0a2f4156a355a812471a487e-0.png",
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225175.616342519] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.1484338641166687,1.6762067079544067,0.7964164614677429,0.15847697854042053,0.1515682190656662,0.11758046597242355],\"stamp\":{\"sec\":6,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[0.7170237302780151],\"stamp\":{\"sec\":6,\"nanosec\":400000000}},\"right_arm\":{\"position\":[-0.001542679383419454,-0.0022959120105952024,0.00516652874648571,-0.0017881353851407766,0.0002944661246147007,-0.0008495801594108343],\"stamp\":{\"sec\":6,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[1.0000016580928457],\"stamp\":{\"sec\":6,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-qqprq0ql.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "d1c8383488e9dd29707f1cfbe07ee4483af5bbb9372e2f9ca22616691726948d",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 11,
+ "call_id": "5c344a17f03a4c9b9d8c5e1ef492af60",
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+ "request": {
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+ "obs": {
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+ }
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+ "model_size": [
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+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/5c344a17f03a4c9b9d8c5e1ef492af60-2.png",
+ "recorded_size": [
+ 320,
+ 240
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+ "recorded_sha256": "ec6b0647eb3032caf5500f84a3bd873cdec19f84acb85343c9afa76f9b10afb2",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-2.png",
+ "model_size": [
+ 224,
+ 224
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+ "model_sha256": "f905dcff4235d5d5e97f660c998152adec0eb74c599033229a9c91b1e64122cf",
+ "model_rgb_sha256": "579a58298d6eacbdded4cb2a5ac68fa151cd897cb17e019b4ce2f62e200bef4f"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5c344a17f03a4c9b9d8c5e1ef492af60-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ ]
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+ "text": "{\n \"output\": \"[INFO] [1793225184.430775369] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.15426401793956757,1.6606262922286987,0.789548933506012,0.12428984045982361,0.13109342753887177,0.11743898689746857],\"stamp\":{\"sec\":7,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[0.8476309180259705],\"stamp\":{\"sec\":7,\"nanosec\":40000000}},\"right_arm\":{\"position\":[-0.001419293461367488,-0.00308085884898901,0.004825655836611986,-0.0024849448818713427,-0.0005740482010878623,-0.0024490084033459425],\"stamp\":{\"sec\":7,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[1.0000210973349484],\"stamp\":{\"sec\":7,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-u53shv3d.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ "type": "image",
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225196.423772412] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.15918698906898499,1.5625288486480713,0.7481035590171814,0.12273091822862625,0.12563808262348175,0.10194754600524902],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"left_gripper\":{\"position\":[0.985747749155218],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"right_arm\":{\"position\":[-0.010863862931728363,0.1244146078824997,0.0808754563331604,0.05205961689352989,-0.06128688156604767,-0.004925197921693325],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"right_gripper\":{\"position\":[0.9989961683750153],\"stamp\":{\"sec\":7,\"nanosec\":680000000}}},\n \"file\": [\"/tmp/kinex-observation-__s713rt.png\"]\n }\n}"
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+ }
+ ],
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225196.423772412] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": {\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},\n \"measured\": {\"left_arm\":{\"position\":[0.15918698906898499,1.5625288486480713,0.7481035590171814,0.12273091822862625,0.12563808262348175,0.10194754600524902],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"left_gripper\":{\"position\":[0.985747749155218],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"right_arm\":{\"position\":[-0.010863862931728363,0.1244146078824997,0.0808754563331604,0.05205961689352989,-0.06128688156604767,-0.004925197921693325],\"stamp\":{\"sec\":7,\"nanosec\":680000000}},\"right_gripper\":{\"position\":[0.9989961683750153],\"stamp\":{\"sec\":7,\"nanosec\":680000000}}},\n \"file\": [\"/tmp/kinex-observation-__s713rt.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',32))\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':result,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "recorded_size": [
+ 320,
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+ "recorded_sha256": "63b87ded735ed49f22c11c0bf10775cf0f73a067c697d2efb059545f3cd39092",
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+ }
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+ "model_example": {
+ "image": [
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/1805a7d360714e9789288b4203492570-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/1805a7d360714e9789288b4203492570-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
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+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/1805a7d360714e9789288b4203492570-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/1805a7d360714e9789288b4203492570-1.png"
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+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/1805a7d360714e9789288b4203492570-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/8822e76006d0413282fabbbbd4e24fac-1.png",
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
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+ "role": "user",
+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/8822e76006d0413282fabbbbd4e24fac-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
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+ "recorded_sha256": "6b3e6870076ff504f62e8e38a326833acfafadc5977cfa1b1ae0a7daac071355",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5cabe37a64584ea088a212d489090720-2.png",
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+ }
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+ "image": [
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/5cabe37a64584ea088a212d489090720-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/5cabe37a64584ea088a212d489090720-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5cabe37a64584ea088a212d489090720-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/5cabe37a64584ea088a212d489090720-1.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "text": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
+ {
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+ "src": "observations/935284a6-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225218.410486806] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.019980965182185173,0.01616850309073925,0.012618893757462502,0.0018397312378510833,-0.004102572798728943,-0.00012995369615964592],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"left_gripper\":{\"position\":[0.9999324354258451],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_arm\":{\"position\":[-0.11386385560035706,1.989914059638977,1.0380632877349854,0.8410269618034363,-0.8812076449394226,-0.06790809333324432],\"stamp\":{\"sec\":9,\"nanosec\":600000000}},\"right_gripper\":{\"position\":[1.0032671121033756],\"stamp\":{\"sec\":9,\"nanosec\":600000000}}},\n \"file\": [\"/tmp/kinex-observation-_5npuoba.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
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+ "call_id": "660685f45a0342a9af0070ad9043ff82",
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+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
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+ ]
+ }
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+ "text": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
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+ "call_id": "a1731b672e5247718af3cead24eaa75d",
+ "received_at_ns": 1793225237299643922,
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+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
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+ }
+ },
+ "images": [
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+ "recorded_sha256": "2d78d780ad0975da0de61fe1918203a1174ed9969eaddc0a99ba0fdc1ce895b6",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-1.png",
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+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/a1731b672e5247718af3cead24eaa75d-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "5dd28860a4004534cf4430320e2ec50a9906dbac82807776e793510a9041fb4a",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "f1df1887e368ed9d702de2eeed49732e3a04bcdd5048e644b006083113a1564c",
+ "model_rgb_sha256": "8d491f99839ef29ff556db73d4ab998e17f39039a27d7c7d73af0ea1a49e29d2"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a1731b672e5247718af3cead24eaa75d-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ ]
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+ "text": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225233.922919641] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.02180369943380356,0.006689541041851044,0.005710085853934288,0.0008508901228196919,-0.003423374844714999,-0.001021994510665536],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"left_gripper\":{\"position\":[0.9999742941422897],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_arm\":{\"position\":[-0.01968967355787754,2.0941779613494873,1.1946473121643066,0.8117249011993408,-0.7913854122161865,-0.05755968391895294],\"stamp\":{\"sec\":11,\"nanosec\":520000000}},\"right_gripper\":{\"position\":[0.9810416915199973],\"stamp\":{\"sec\":11,\"nanosec\":520000000}}},\n \"file\": [\"/tmp/kinex-observation-nugmy13r.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ {
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225249.105752606] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.020384546369314194,0.005946859251707792,0.0056259846314787865,0.0014855503104627132,-0.0038541618268936872,-0.0016520870849490166],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"left_gripper\":{\"position\":[1.0000660040161826],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_arm\":{\"position\":[0.030804969370365143,2.1672568321228027,1.3008943796157837,0.7695925831794739,-0.7232820391654968,-0.05120856314897537],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_gripper\":{\"position\":[0.8359024172479457],\"stamp\":{\"sec\":13,\"nanosec\":440000000}}},\n \"file\": [\"/tmp/kinex-observation-aubqgo0c.png\"]\n }\n}"
+ },
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225249.105752606] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.020384546369314194,0.005946859251707792,0.0056259846314787865,0.0014855503104627132,-0.0038541618268936872,-0.0016520870849490166],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"left_gripper\":{\"position\":[1.0000660040161826],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_arm\":{\"position\":[0.030804969370365143,2.1672568321228027,1.3008943796157837,0.7695925831794739,-0.7232820391654968,-0.05120856314897537],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_gripper\":{\"position\":[0.8359024172479457],\"stamp\":{\"sec\":13,\"nanosec\":440000000}}},\n \"file\": [\"/tmp/kinex-observation-aubqgo0c.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
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+ "recorded_size": [
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/b652dedf55254de0ba15a349fb664918-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/b652dedf55254de0ba15a349fb664918-2.png"
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/b652dedf55254de0ba15a349fb664918-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/b652dedf55254de0ba15a349fb664918-1.png"
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
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+ "text": "{\n \"output\": \"[INFO] [1793225249.105752606] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.020384546369314194,0.005946859251707792,0.0056259846314787865,0.0014855503104627132,-0.0038541618268936872,-0.0016520870849490166],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"left_gripper\":{\"position\":[1.0000660040161826],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_arm\":{\"position\":[0.030804969370365143,2.1672568321228027,1.3008943796157837,0.7695925831794739,-0.7232820391654968,-0.05120856314897537],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_gripper\":{\"position\":[0.8359024172479457],\"stamp\":{\"sec\":13,\"nanosec\":440000000}}},\n \"file\": [\"/tmp/kinex-observation-aubqgo0c.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225249.105752606] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.020384546369314194,0.005946859251707792,0.0056259846314787865,0.0014855503104627132,-0.0038541618268936872,-0.0016520870849490166],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"left_gripper\":{\"position\":[1.0000660040161826],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_arm\":{\"position\":[0.030804969370365143,2.1672568321228027,1.3008943796157837,0.7695925831794739,-0.7232820391654968,-0.05120856314897537],\"stamp\":{\"sec\":13,\"nanosec\":440000000}},\"right_gripper\":{\"position\":[0.8359024172479457],\"stamp\":{\"sec\":13,\"nanosec\":440000000}}},\n \"file\": [\"/tmp/kinex-observation-aubqgo0c.png\"]\n }\n}"
+ },
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
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+ "call_id": "ad6567c479b04e7dbd0cf37e2181db01",
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+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
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+ "recorded_sha256": "159972cad096a0d98c03dc338125d222d51185b662db97954a97ebf0b143f745",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-1.png",
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+ },
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+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/ad6567c479b04e7dbd0cf37e2181db01-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "49523e795fed82ca6e851c2ebcfbd4877dbb71a89ba68066f959adaec3d388e1",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "2b41cd012b25925f58e0f2701b5ab71f9bedd1bce0b1fd20178afe32bfdeb5a2",
+ "model_rgb_sha256": "e30ba883a8e8cf0e36cfb720eb5f9c41872b16023b7b0023e6c883027da5a68f"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/ad6567c479b04e7dbd0cf37e2181db01-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ ]
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+ "text": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
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+ "content": [
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/3ebe5221c88d47a2b1a3cbfc43de9ad5-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/3ebe5221c88d47a2b1a3cbfc43de9ad5-2.png"
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
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+ "content": [
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+ "type": "image",
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225265.211309068] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01863095536828041,0.007643602322787046,0.005502762272953987,0.0006983476341702044,-0.003859712975099683,-0.0016588179860264063],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"left_gripper\":{\"position\":[0.9998576586896724],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_arm\":{\"position\":[-0.012142442166805267,2.0882678031921387,1.1918913125991821,0.7973539233207703,-0.7836735844612122,-0.06346789002418518],\"stamp\":{\"sec\":15,\"nanosec\":360000000}},\"right_gripper\":{\"position\":[0.9794340594248339],\"stamp\":{\"sec\":15,\"nanosec\":360000000}}},\n \"file\": [\"/tmp/kinex-observation-_occj18r.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/dbac81f719c94186be3df9e5ff3ad117-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/dbac81f719c94186be3df9e5ff3ad117-2.png"
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/dbac81f719c94186be3df9e5ff3ad117-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6f904ff6c2f54bcb945ad10502913f04-2.png"
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "tool": "exec",
+ "arguments": {
+ "description": "refine second bottle grasp",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
+ "chunks": 4
+ },
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+ "session_event_id": "ba87585e",
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+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/ba87585e-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 27,
+ "call_id": "9ae8a6b8d3c74be4b9203e7d1c4d2460",
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+ "text": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
+ },
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+ "src": "observations/ba87585e-1.png"
+ }
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+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
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+ "recorded_size": [
+ 320,
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+ "recorded_sha256": "f36b5a8544dadb39f79f06218730d4d257b4061b7fb0573ac63818588060bca6",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/2d641f30d3764897a12ebcfb27b570d2-2.png",
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+ }
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+ "image": [
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/2d641f30d3764897a12ebcfb27b570d2-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/2d641f30d3764897a12ebcfb27b570d2-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/2d641f30d3764897a12ebcfb27b570d2-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/2d641f30d3764897a12ebcfb27b570d2-1.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225282.327360556] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.01917050965130329,0.0007784098270349205,0.004933945368975401,0.0029006940312683582,-0.0043197814375162125,-0.0026382887735962868],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"left_gripper\":{\"position\":[0.9999774098396301],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_arm\":{\"position\":[0.03394973650574684,2.11479115486145,1.2287675142288208,0.7988498210906982,-0.726144552230835,-0.05787000432610512],\"stamp\":{\"sec\":17,\"nanosec\":920000000}},\"right_gripper\":{\"position\":[0.7493105842308565],\"stamp\":{\"sec\":17,\"nanosec\":920000000}}},\n \"file\": [\"/tmp/kinex-observation-ecrm42u6.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/a6b79a8aa9534cb59b8cf26a9422e718-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/a6b79a8aa9534cb59b8cf26a9422e718-2.png"
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/a6b79a8aa9534cb59b8cf26a9422e718-0.png"
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
+ },
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/78d1cd82bdb242bc98097da06af0adc1-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/78d1cd82bdb242bc98097da06af0adc1-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/78d1cd82bdb242bc98097da06af0adc1-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/78d1cd82bdb242bc98097da06af0adc1-0.png"
+ },
+ {
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+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/78d1cd82bdb242bc98097da06af0adc1-1.png"
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "description": "lift grasped second bottle",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
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+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/27bf832e-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 32,
+ "call_id": "7e2e326e5fa94fdd88a5cb0771dd090c",
+ "received_at_ns": 1793225310331407400,
+ "completed_at_ns": 1793225310581545588,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
+ "/logs/agent/policy/7e2e326e5fa94fdd88a5cb0771dd090c-0.png",
+ "/logs/agent/policy/7e2e326e5fa94fdd88a5cb0771dd090c-1.png",
+ "/logs/agent/policy/7e2e326e5fa94fdd88a5cb0771dd090c-2.png"
+ ]
+ }
+ },
+ "images": [
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+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/7e2e326e5fa94fdd88a5cb0771dd090c-0.png",
+ "recorded_size": [
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+ "model_size": [
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+ "text": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225300.819127286] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.014373707585036755,0.010032521560788155,0.012640900909900665,-0.004937315825372934,-0.0066292136907577515,-0.009011742658913136],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"left_gripper\":{\"position\":[0.9999928528612311],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_arm\":{\"position\":[0.015467030927538872,2.0244693756103516,1.1675255298614502,0.7890125513076782,-0.7371123433113098,-0.03935727849602699],\"stamp\":{\"sec\":20,\"nanosec\":480000000}},\"right_gripper\":{\"position\":[0.5937852006066929],\"stamp\":{\"sec\":20,\"nanosec\":480000000}}},\n \"file\": [\"/tmp/kinex-observation-_5gbiysh.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
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+ "request": {
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+ "obs": {
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+ }
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+ "recorded_sha256": "56424b53f39de8e3716e3d5d1526e1468dc6bf0eb042011136607316dc434ea4",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-1.png",
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+ },
+ {
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+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/16db82ce7b3d4bf69b705f9ea521a6be-2.png",
+ "recorded_size": [
+ 320,
+ 240
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+ "recorded_sha256": "9ac7596a8acbbbf8406c51d054196fefa5cc3cb48f92b7ed11940ffaea40828c",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-2.png",
+ "model_size": [
+ 224,
+ 224
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+ "model_sha256": "d5cc8c73ecc2193e387c07ac4b86b3dceaeb6a42e14881d4d6f2b69074d5ae78",
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+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/16db82ce7b3d4bf69b705f9ea521a6be-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/660d8328e61e45249232bdb95e1dcad4-1.png",
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+ "content": [
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+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/660d8328e61e45249232bdb95e1dcad4-0.png"
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+ {
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225320.615005054] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.022220058366656303,0.00550552923232317,0.005602061748504639,0.000018043174350168556,-0.004020639229565859,-0.002054163720458746],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"left_gripper\":{\"position\":[1.000095467675816],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_arm\":{\"position\":[0.03237162530422211,2.107151508331299,1.217344880104065,0.7917813062667847,-0.7230378985404968,-0.05491897463798523],\"stamp\":{\"sec\":23,\"nanosec\":40000000}},\"right_gripper\":{\"position\":[0.9994532276283611],\"stamp\":{\"sec\":23,\"nanosec\":40000000}}},\n \"file\": [\"/tmp/kinex-observation-eehl06w8.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
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+ "text": "{\n \"output\": \"[INFO] [1793225439.446542299] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.42659056186676025,1.5380027294158936,0.42500537633895874,1.1043425798416138,0.28371018171310425,0.0038743172772228718],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[1.0026397732171146],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_arm\":{\"position\":[0.5330829620361328,1.7219411134719849,1.112260341644287,0.5872642397880554,-0.2544354200363159,-0.004977565724402666],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[0.7736253846775402],\"stamp\":{\"sec\":28,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-fdww3hao.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225439.446542299] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.42659056186676025,1.5380027294158936,0.42500537633895874,1.1043425798416138,0.28371018171310425,0.0038743172772228718],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[1.0026397732171146],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_arm\":{\"position\":[0.5330829620361328,1.7219411134719849,1.112260341644287,0.5872642397880554,-0.2544354200363159,-0.004977565724402666],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[0.7736253846775402],\"stamp\":{\"sec\":28,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-fdww3hao.png\"]\n }\n}"
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+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 38,
+ "call_id": "6108881cfa49436d87d02fb349dac3eb",
+ "received_at_ns": 1793225443238274385,
+ "completed_at_ns": 1793225443485346193,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
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+ "/logs/agent/policy/6108881cfa49436d87d02fb349dac3eb-1.png",
+ "/logs/agent/policy/6108881cfa49436d87d02fb349dac3eb-2.png"
+ ]
+ }
+ },
+ "images": [
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+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/6108881cfa49436d87d02fb349dac3eb-0.png",
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+ "model_size": [
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+ },
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+ "camera": "left_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/6108881cfa49436d87d02fb349dac3eb-1.png",
+ "recorded_size": [
+ 320,
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+ "recorded_sha256": "4bb99fd6b28f70cbe8402b0c52ac227366ffcc769e3bf470d5852d97f8a71028",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-1.png",
+ "model_size": [
+ 224,
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+ "model_sha256": "170b7dd8dc91658ec3a6be84ef88b2ff4e6978bd80d3b50eb6925d3013484863",
+ "model_rgb_sha256": "410aaa4eec47c806eb8f0bc82f7f41c5a523d07bccdbcd633b4439a2bde4d044"
+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/6108881cfa49436d87d02fb349dac3eb-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "1ebcda4f57c6f42b2dc9d014268e0290316af7ab8dd39534ec4bb468808a9b98",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "787b6943a1eec4b08cfabb8456d1d74948b7ffd0979aba55f460acd73c7e2d6e",
+ "model_rgb_sha256": "ab8e286a48c94cc0a6bbb355e55c36ad7a04dcab34f814063518aee23e3226eb"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/6108881cfa49436d87d02fb349dac3eb-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
+ ]
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+ "text": "{\n \"output\": \"[INFO] [1793225439.446542299] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.42659056186676025,1.5380027294158936,0.42500537633895874,1.1043425798416138,0.28371018171310425,0.0038743172772228718],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[1.0026397732171146],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_arm\":{\"position\":[0.5330829620361328,1.7219411134719849,1.112260341644287,0.5872642397880554,-0.2544354200363159,-0.004977565724402666],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[0.7736253846775402],\"stamp\":{\"sec\":28,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-fdww3hao.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225439.446542299] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.42659056186676025,1.5380027294158936,0.42500537633895874,1.1043425798416138,0.28371018171310425,0.0038743172772228718],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"left_gripper\":{\"position\":[1.0026397732171146],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_arm\":{\"position\":[0.5330829620361328,1.7219411134719849,1.112260341644287,0.5872642397880554,-0.2544354200363159,-0.004977565724402666],\"stamp\":{\"sec\":28,\"nanosec\":400000000}},\"right_gripper\":{\"position\":[0.7736253846775402],\"stamp\":{\"sec\":28,\"nanosec\":400000000}}},\n \"file\": [\"/tmp/kinex-observation-fdww3hao.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "content": [
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+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "text": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
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+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
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+ "recorded_sha256": "273fb2072f6f131233d54ef58e8215dac02f652139d51853ba2ff3671e3f27b0",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/b295b18d1621446aa14a863ad89c56a2-1.png",
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+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/b295b18d1621446aa14a863ad89c56a2-0.png"
+ },
+ {
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+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/b295b18d1621446aa14a863ad89c56a2-1.png"
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+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
+ }
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+ "text": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
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+ "trace_output": "{\n \"output\": \"[INFO] [1793225455.909526198] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[-0.5693696737289429,1.91524076461792,0.8664708733558655,1.0522302389144897,0.23840513825416565,0.008700541220605373],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"left_gripper\":{\"position\":[0.7765454026785764],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_arm\":{\"position\":[0.5431060194969177,1.7058240175247192,1.1579121351242065,0.5416489243507385,-0.2270985096693039,0.015886971727013588],\"stamp\":{\"sec\":30,\"nanosec\":320000000}},\"right_gripper\":{\"position\":[0.7791389497843656],\"stamp\":{\"sec\":30,\"nanosec\":320000000}}},\n \"file\": [\"/tmp/kinex-observation-jkpurtwa.png\"]\n }\n}"
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+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
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+ "experiments/robotwin-native/kinex_policy-3/model-inputs/25b3016e74ac4dc48c88956f9a61603d-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/25b3016e74ac4dc48c88956f9a61603d-2.png"
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+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
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+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍."
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+ "tool": "exec",
+ "arguments": {
+ "description": "transfer second bottle to left arm",
+ "file": "/workspace/.kinex/tools/bottle_policy.py",
+ "args": {
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+ "parts": [
+ {
+ "type": "text",
+ "text": "{\n \"output\": \"[INFO] [1793225472.808813156] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.026490675285458565,1.736082911491394,0.7977779507637024,0.2831766903400421,0.1480584293603897,0.09788993000984192],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"left_gripper\":{\"position\":[0.7953653660687534],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_arm\":{\"position\":[0.10040103644132614,0.27128010988235474,0.19429327547550201,0.10107256472110748,-0.04703330993652344,0.006739610340446234],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_gripper\":{\"position\":[1.0037052739750256],\"stamp\":{\"sec\":32,\"nanosec\":240000000}}},\n \"file\": [\"/tmp/kinex-observation-a5hr5x4l.png\"]\n }\n}"
+ },
+ {
+ "type": "image",
+ "src": "observations/7d1d9cc1-1.png"
+ }
+ ],
+ "is_error": false
+ },
+ "association": "Unique exec interval contains both model input and output timestamps. Native toolCallId joins the assistant call and tool result.",
+ "trace_output": "{\n \"output\": \"[INFO] [1793225472.808813156] [rcl]: Found security directory: /run/rlebench/public/security/enclaves/agent\\n\",\n \"result\": {\n \"execution\": [{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null},{\"actions_submitted\":16,\"duration_s\":0.64,\"ik_failure\":null}],\n \"measured\": {\"left_arm\":{\"position\":[0.026490675285458565,1.736082911491394,0.7977779507637024,0.2831766903400421,0.1480584293603897,0.09788993000984192],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"left_gripper\":{\"position\":[0.7953653660687534],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_arm\":{\"position\":[0.10040103644132614,0.27128010988235474,0.19429327547550201,0.10107256472110748,-0.04703330993652344,0.006739610340446234],\"stamp\":{\"sec\":32,\"nanosec\":240000000}},\"right_gripper\":{\"position\":[1.0037052739750256],\"stamp\":{\"sec\":32,\"nanosec\":240000000}}},\n \"file\": [\"/tmp/kinex-observation-a5hr5x4l.png\"]\n }\n}"
+ },
+ "executed_tool_source": {
+ "path": ".kinex/tools/bottle_policy.py",
+ "content": "\"\"\"Run a bounded, freshly observed RoboTwin policy chunk; no lifecycle changes.\"\"\"\nimport asyncio\nfrom kinex import args, communication, finish, helpers\n\nasync def image(io, camera):\n with io.subscribe(camera + '.image', depth=1) as stream:\n return await stream.next(timeout_s=10)\n\nasync def main():\n a = args()\n async with communication() as io:\n results = []\n for _ in range(min(a.get('chunks',1),4)):\n images = await asyncio.gather(*(image(io, c) for c in ['head_camera','left_camera','right_camera']))\n paths = [helpers.save_image(im) for im in images]\n result = await helpers.run_policy(io, 'policy', {'images': paths},\n [{'device': d} for d in ['left_arm','left_gripper','right_arm','right_gripper']],\n task=a.get('task','use arms to grab the bottles and put them into the dustbin to the left of the table'),\n action_hz=25, max_actions=a.get('max_actions',16))\n results.append(result)\n measured = {}\n for d in ['left_arm','left_gripper','right_arm','right_gripper']:\n with io.subscribe(d+'.joint_state', depth=1) as stream:\n state = await stream.next(timeout_s=10)\n measured[d] = {'position':list(state.position), 'stamp':state.header.stamp}\n after = await image(io,'head_camera')\n out = helpers.save_image(after)\n finish({'execution':results,'measured':measured},file=[out])\n\nasyncio.run(main())\n",
+ "sha256": "2a820bdc28e55ac8a3baf41a8c73f6bb8a98a6cd04e333292f83583113bcaf6f",
+ "basis": "Replayed successful write/edit tool results before this exec; final workspace checked."
+ }
+ },
+ {
+ "index": 44,
+ "call_id": "9fd54c96376e4dc7a848e2ffc2ebf393",
+ "received_at_ns": 1793225475952631184,
+ "completed_at_ns": 1793225476158316114,
+ "request": {
+ "task": "use arms to grab the bottles and put them into the dustbin to the left of the table",
+ "obs": {
+ "images": [
+ "/logs/agent/policy/9fd54c96376e4dc7a848e2ffc2ebf393-0.png",
+ "/logs/agent/policy/9fd54c96376e4dc7a848e2ffc2ebf393-1.png",
+ "/logs/agent/policy/9fd54c96376e4dc7a848e2ffc2ebf393-2.png"
+ ]
+ }
+ },
+ "images": [
+ {
+ "camera": "head_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/9fd54c96376e4dc7a848e2ffc2ebf393-0.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "f0641644e9c32c69e4930d38188f4299c7fcb1b98656dc51bd509dd8e36d134c",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-0.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "9da4db8f7d65392b70eef05873f86b8639b19a2313f261ca1aa194104a54740c",
+ "model_rgb_sha256": "bc5f0c403359271545ba9f2f84fdecd157c002b422617828bb8fbdb7e7fc8bc5"
+ },
+ {
+ "camera": "left_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/9fd54c96376e4dc7a848e2ffc2ebf393-1.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "db018ff7d28489cf6cf9c2c696369d3f84754a554c30878a19224485f09786fe",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-1.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "5737759ff78d607c746f8c74917c0cecf1b0b0068b11541131c2f7d3893014df",
+ "model_rgb_sha256": "22448fca7db16f18cd7a066f4bcc8d4147764c544938ca86df2a4168816dfa1b"
+ },
+ {
+ "camera": "right_camera",
+ "recorded": "experiments/robotwin-native/kinex_policy-3/policy/9fd54c96376e4dc7a848e2ffc2ebf393-2.png",
+ "recorded_size": [
+ 320,
+ 240
+ ],
+ "recorded_sha256": "bbc830463dd889423d0b21a40ff7108acbebc251265a46c34aa0891d5f3fdf6d",
+ "model_image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-2.png",
+ "model_size": [
+ 224,
+ 224
+ ],
+ "model_sha256": "dc213d866f7b1a35fa022d9b23db1dae1e1f7c00b6ec7dc22b182736d9ce8f89",
+ "model_rgb_sha256": "f0e43b62b48eb539a5fcff7412e98d479b56a25590500dc0ebff17b981dd409a"
+ }
+ ],
+ "model_example": {
+ "image": [
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-0.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-1.png",
+ "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-2.png"
+ ],
+ "lang": "use arms to grab the bottles and put them into the dustbin to the left of the table"
+ },
+ "backbone_messages": [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-0.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-1.png"
+ },
+ {
+ "type": "image",
+ "image": "experiments/robotwin-native/kinex_policy-3/model-inputs/9fd54c96376e4dc7a848e2ffc2ebf393-2.png"
+ },
+ {
+ "type": "text",
+ "text": "use arms to grab the bottles and put them into the dustbin to the left of the table Please predict the next 16 robot actions: 🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍🔍 
`;
+function stats(es) {
+ return UsageMetrics.stats(es);
+}
+window.benchmarkStats = stats;
+const tokens = e => e && Number.isFinite(e.usage?.input_tokens) && Number.isFinite(e.usage?.output_tokens) ? e.usage.input_tokens+e.usage.output_tokens : null;
+function metric(value,label,detail='',attrs='') {return `