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runs/behavior-boxing-books-up-for-storage-i00-standard--grtqedt.json

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+{"slug":"behavior-boxing-books-up-for-storage-i00-standard--grtqedt","task":"behavior-boxing-books-up-for-storage-i00-standard","bench":"behavior","mode":"standard","run":"claude_code-opus_5_5-high","agent":"claude-code","model":"claude-opus-5-5","effort":"high","state":"failed","success":0,"reward":{"success":0,"live_success":0,"replay_success":0,"deterministic":1,"live_matches_replay":1,"finalized":1,"missing_log":0,"n_actions":1389,"sim_steps":1389,"physics_steps":5556,"steps":1389,"elapsed_s":274.7,"video_rendered":1,"gpu_lost":0,"replay_error":0,"instance_ok":1,"task_failure":1,"q_score":0.0,"sim_startups":1,"resumes":0,"resume_state_mismatch":0,"resume_max_tcp_dev_m":0.0,"resume_max_joint_dev":0.0,"gave_up":0,"infra_error":0,"grader_error":0,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0,"peak_memory_gb":0.236,"peak_processes":10,"peak_disk_gb":0.249,"resource_emergency_kills":0},"wall_s":679,"tokens":{"in":1134859,"cached":1090828,"out":12789,"usd":0.83},"task_text":"# BEHAVIOR-1K · boxing_books_up_for_storage — STANDARD MODE (robot as a service, eai-standard/2.2)\n\nYou drive an **R1Pro** mobile bimanual robot around a house **as if it were real hardware**: the simulator (BEHAVIOR-1K\nv3.9.2, the 2026 BEHAVIOR Challenge stack) runs in a service you cannot open. You get one client and one episode.\n**Task:** Box up the books for storage. Six books stand in the four bookcases of the living room, and an empty box stands on the living-room floor; put all six books inside the box. Success means all of the following hold at the same time: (1) every book is inside the box. How the simulator judges them: inside(A, B): the centre of A's axis-aligned bounding box lies within B's bounding box and within B's interior (container) volume. The service checks the goal and the episode ends the moment it holds.\n\n## Rules (real-robot rules)\n- **No reset.** The episode starts when the service comes up and ends on success, when the robot has fallen over, when\n  your time is up, or on a simulator error. Whatever you knock over or push away stays where it ends up.\n- **A fall ends the episode as a failure** (`meta[\"reason\"]` \"failure: the robot fell over\"): the robot has fallen over\n  when its base has been tilted more than 41.4° from upright, or more than 3 cm below the floor, for 10 s of simulated\n  time in a row (OmniGibson's own Falling rule; tilted means the z of the base's up axis is below 0.75, which the\n  proprioception gives as cos(rx)·cos(ry) of `base_footprint_rx_joint` and `base_footprint_ry_joint`).\n- **No privileged state.** You see what the robot's cameras see (RGB; depth on request) plus its own proprioception\n  (joints, base pose, end-effector and fingertip poses, gripper openings). No object poses, no map, no success predicate.\n- There is no step budget; your wall-clock budget is 4 h (14400 s; `meta[\"time_left_s\"]`). Actions and simulated time\n  are reported as cost. Only a runaway guard bounds the episode: it ends at 200,000 control steps (1.85 h of simulated\n  time; `spec[\"max_control_steps\"]`, reason `step_guard`).\n- **A malformed request is refused with a 400 and nothing is executed** (a wrong type or shape, a value out of range,\n  a `dt` that is not a whole number of control periods, `video_fps` outside 1-30): fix it and send it again.\n- There is nothing to hand in: the service records your episode as the trajectory and grades it. Leave your script\n  at `/app/output/gen.py` for the record.\n- **Nothing is put into your context automatically.** Images and videos come back as arrays/bytes in a Python object;\n  what you look at and where you store it is your code's decision.\n- **If the service crashes** (a connection error or a 5xx answer), it restarts and resumes the SAME episode (never a\n  reset) in the state after the last call it completed, which you may not have received: call `r.wait_ready()`, then\n  check `r.status()` (`calls`, `control_steps`) before you continue. Resuming replays the episode so far (minutes \n… (3,502 characters left out) …\ns **xyzw**, gripper\n  1 = open, 0 = closed (switched at the start of the row). Each row is solved by cuRobo inverse kinematics for both end\n  effectors together (the trunk may bend too; no collision checking) and driven to in joint space; `dt` is ignored and the\n  base stands still. If no IK solution exists nothing moves, and `meta[\"plan\"]` says so. The pose is the end-effector frame\n  of the proprio `*_eef_*` entries, so an observed pose is a valid target. At most 50 rows per submit.\n\n### Optional inputs (eai-standard/2.2; nothing changes unless you ask)\n- **Depth**: `depth=True` on `get_obs` / `submit` adds `res.last_depth[cam]`, float32 (224, 224) z-depth in metres (0 = no\n  reading), pixel-aligned with the RGB; `depth=\"frames\"` also returns `res.depth[cam]` (N, 224, 224), one per frame.\n- **Per frame**: `res.frame_step`, `res.frame_time_s` and `res.extrinsic_cv[cam]` (N, 3, 4; world -> camera, OpenCV\n  axes). While the robot moves, a frame shows the scene 2 control steps before its `frame_step`; its `extrinsic_cv` is the\n  pose it was rendered with. Intrinsics `spec[\"cameras\"][cam][\"intrinsic_cv\"]`, mounting `spec[\"cameras\"][cam][\"mount\"]`\n  (parent link + fixed `link_T_cam_cv`).\n- **Robot**: `spec[\"robot_spec\"]`: joint names and real limits, gripper stroke and open/close rule, drive gains, the\n  end-effector frame vs the fingertip centre (TCP, 1.88 cm further along the fingers), the base's per-step and speed\n  limits; `spec[\"world\"]`: frame, units, quaternion order, camera axes.\n- **Proprioception**: named columns `spec[\"proprio_layout\"]`, groups `spec[\"proprio_groups\"]` (joint_pos, joint_vel,\n  joint_effort, gripper_opening, tcp_pose, eef_pose, base_pose, ...): `res.group(\"tcp_pose\")` per frame,\n  `res.group(\"tcp_pose\", now=True)` now.\n- **Kinematics** (stateless: no physics, no time): `r.fk(q)`, `r.ik({\"left_tcp\": pose}, seed=q)`; q =\n  `spec[\"kinematics\"][\"joint_names\"]` (trunk + both arms, all proprio columns); poses in the robot's base frame, or in the\n  world frame with `base_pose=` the 7 base proprio columns.\n\nFor scale: the 2026 challenge's human teleoperators needed 808 s on average (24,228 control steps) for this task, and the simulator runs at ~7-11 control steps/s. Budget your time, drive before you reach, and check `meta[\"done\"]`.\n\n## Resource limits\nLimits for your agent environment, your own container only (the simulator in the `sim` service is the benchmark's and does not count): at most **8 GiB of memory**, **512 processes** and **20 GiB** of new files under `/app`, `/tmp` and `/root`; your container has no GPU. These limits may be enforced (from protocol v1.2 on): when enforcement is on, exceeding one for 60 s within any 2 minutes, or a process killed for lack of memory, ends the trial as a failure (reward 0), whatever the deliverable. A monitor outside your container measures every few seconds; the current values are in `/run/rcb-limits/usage.json`. CPU is capped at 8 cores for your container; the cap only slows you down.\n","replay":"behavior-boxing-books-up-for-storage-i00-standard--grtqedt/replay.mp4","replay_last":"behavior-boxing-books-up-for-storage-i00-standard--grtqedt/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"cd /app; ls -la; ls /app/output /opt/tools; cat /run/rcb-limits/usage.json; ls /logs/agent/sessions/projects/-","code":"cd /app; ls -la; ls /app/output /opt/tools; cat /run/rcb-limits/usage.json; ls /logs/agent/sessions/projects/-app/memory/ 2>/dev/null"},{"kind":"shell","label":"wc -l /opt/tools/rcb_client.py; sed -n 1,200p /opt/tools/rcb_client.py","code":"wc -l /opt/tools/rcb_client.py; sed -n 1,200p /opt/tools/rcb_client.py"}],"out":{"text":"total 12\ndrwxr-xr-x 3 root root 4096 Oct  2 12:51 .\ndrwxr-xr-x 1 root root 4096 Oct 10 20:06 ..\ndrwxr-xr-x 2 root root 4096 Oct  2 12:51 output\n/app/output:\n\n/opt/tools:\nrcb1.py\nrcb_client.py\n{\n \"t\": 1791662925.3,\n \"gpu_memory_gb\": 0.0,\n \"memory_gb\": 0.078,\n \"processes\": 5,\n \"disk_gb\": 0.0,\n \"enforced\": 0,\n \"limits\": {\n  \"max_gpu_memory_gb\": 0.0,\n  \"max_memory_gb\": 8.0,\n  \"max_processes\": 512,\n  \"max_disk_gb\": 20.0,\n  \"sustain_sec\": 60.0,\n  \"window_sec\": 120.0\n },\n \"violations\": [],\n \"emergency_kills\": 0,\n \"last_emergency_kill\": null\n}\n\n[stdout]\ntotal 12\ndrwxr-xr-x 3 root root 4096 Oct  2 12:51 .\ndrwxr-xr-x 1 root root 4096 Oct 10 20:06 ..\ndrwxr-xr-x 2 root root 4096 Oct  2 12:51 output\n/app/output:\n\n/opt/tools:\nrcb1.py\nrcb_client.py\n{\n \"t\": 1791662925.3,\n \"gpu_memory_gb\": 0.0,\n \"memory_gb\": 0.078,\n \"processes\": 5,\n \"disk_gb\": 0.0,\n \"enforced\": 0,\n \"limits\": {\n  \"max_gpu_memory_gb\": 0.0,\n  \"max_memory_gb\": 8.0,\n  \"max_processes\": 512,\n  \"max_disk_gb\": 20.0,\n  \"sustain_sec\": 60.0,\n  \"window_sec\": 120.0\n },\n \"violations\": [],\n \"emergency_kills\": 0,\n \"last_emergency_kill\": null\n}\n211 /opt/tools/rcb_client.py\n\"\"\"eai-standard/2.2 client (formerly rcb-limited/2.x) — the only thing a standard-mode agent gets (installed at\n/opt/tools/rcb_client.py).\n\n    from rcb_client import Robot\n    r = Robot()                                  # finds the service (sim:8000, then localhost:8000), waits for warm-up\n    spec = r.spec()                              # actions, cameras (+ intrinsics, m\n… (24,947 characters left out) …\nready(self, timeout: float = 3600.0) -> dict:\n        \"\"\"After a connection error: wait until the service answers GET /status again (it resumes the same episode after a\n        crash), then return the status. Raises RuntimeError after `timeout` seconds.\"\"\"\n        t0 = time.time(); last = None\n        while time.time() - t0 < timeout:\n            try:\n                return self.status()\n            except requests.exceptions.RequestException as e:\n                last = e\n            time.sleep(5)\n        raise RuntimeError(f\"sim service did not come back within {timeout:.0f} s: {last}\")\n\n    def kinematics(self, body: dict) -> dict:\n        \"\"\"POST /kinematics (stateless: never moves the robot, never advances time). Raises ValueError on a bad request.\"\"\"\n        r = requests.post(self.base + \"/kinematics\", json=body, timeout=(5, 120))\n        if r.status_code >= 400:\n            try: err = r.json()\n            except Exception: err = {\"error\": r.text[:300]}\n            raise ValueError(f\"{r.status_code}: {err.get('error')} {err.get('detail', '')}\".strip())\n        return r.json()\n\n    def fk(self, q, links=None, base_pose=None) -> dict:\n        \"\"\"Forward kinematics: q in spec()['kinematics']['joint_names'] order -> {\"ok\", \"frame\", \"poses\": {link: [x,y,z, quat]}}\n        (quaternion order spec()['world']['quaternion_order']; a mobile robot answers in its base frame unless base_pose is given).\"\"\"\n        body = {\"op\": \"fk\", \"q\": [float(v) for v in np.asarray(q).reshape(-1)]}","exit":[],"pics":[]},"tok":{"in":26915,"cached":19565,"out":217,"think":null,"usd":0.045},"sim":{"submit":0,"reset":0}},{"id":3,"t":3.8,"say":"","calls":[{"kind":"shell","label":"s=r.spec()","code":"cd /app; mkdir -p runs; timeout 1900 python3 -c \"\nimport sys; sys.path.insert(0,'/opt/tools')\nfrom rcb_client import Robot\nimport json\nr=Robot(timeout=1800)\ns=r.spec()\njson.dump(s,open('/app/runs/spec.json','w'),indent=1)\nprint(list(s.keys()))\nprint(r.status())\n\""}],"out":{"text":"Command did not complete within its 120s timeout and was moved to the background (ID: bxipe603q). Output is being written to: /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output. You will be notified when it completes. If it is still running after 10m in the background, it will be stopped and you will be notified. To check interim output, use Read on that file path.\nSession cwd remains /app; directory changes made by the backgrounded command do not apply to subsequent commands.","exit":[],"pics":[]},"tok":{"in":32896,"cached":26913,"out":361,"think":null,"usd":0.0425},"sim":{"submit":0,"reset":0}},{"id":4,"t":126.5,"say":"","calls":[{"kind":"shell","label":"sed -n 200,211p /opt/tools/rcb_client.py; python3 -c \"import cv2, PIL, scipy; print('ok')\"; nproc; free -g","code":"sed -n 200,211p /opt/tools/rcb_client.py; python3 -c \"import cv2, PIL, scipy; print('ok')\"; nproc; free -g"}],"out":{"text":"body = {\"op\": \"fk\", \"q\": [float(v) for v in np.asarray(q).reshape(-1)]}\n        if links is not None: body[\"links\"] = list(links)\n        if base_pose is not None: body[\"base_pose\"] = [float(v) for v in base_pose]\n        return self.kinematics(body)\n\n    def ik(self, targets: dict, seed=None, base_pose=None, **opts) -> dict:\n        \"\"\"Inverse kinematics: {frame: [x,y,z, quat]} (frames from spec()['kinematics']['ik_targets']) and an optional seed q ->\n        {\"ok\", \"q\", \"error\": {frame: {\"pos_m\", \"rot_rad\"}}}. opts: tol_pos_m, tol_rot_rad, max_iters.\"\"\"\n        body = {\"op\": \"ik\", \"targets\": {k: [float(v) for v in p] for k, p in targets.items()}, **opts}\n        if seed is not None: body[\"seed\"] = [float(v) for v in np.asarray(seed).reshape(-1)]\n        if base_pose is not None: body[\"base_pose\"] = [float(v) for v in base_pose]\n        return self.kinematics(body)\nTraceback (most recent call last):\n  File \"<string>\", line 1, in <module>\nModuleNotFoundError: No module named 'cv2'\n8\n               total        used        free      shared  buff/cache   available\nMem:              61          10          23           0          28          51\nSwap:              0           0           0\n\n[stdout]\n        body = {\"op\": \"fk\", \"q\": [float(v) for v in np.asarray(q).reshape(-1)]}\n        if links is not None: body[\"links\"] = list(links)\n        if base_pose is not None: body[\"base_pose\"] = [float(v) for v in base_pose]\n        return self.kinematics(body)\n\n    def ik(self, targets: dict, seed=None, base_pose=None, **opts) -> dict:\n        \"\"\"Inverse kinematics: {frame: [x,y,z, quat]} (frames from spec()['kinematics']['ik_targets']) and an optional seed q ->\n        {\"ok\", \"q\", \"error\": {frame: {\"pos_m\", \"rot_rad\"}}}. opts: tol_pos_m, tol_rot_rad, max_iters.\"\"\"\n        body = {\"op\": \"ik\", \"targets\": {k: [float(v) for v in p] for k, p in targets.items()}, **opts}\n        if seed is not None: body[\"seed\"] = [float(v) for v in np.asarray(seed).reshape(-1)]\n        if base_pose is not None: body[\"base_pose\"] = [float(v) for v in base_pose]\n        return self.kinematics(body)\nTraceback (most recent call last):\n  File \"<string>\", line 1, in <module>\nModuleNotFoundError: No module named 'cv2'\n8\n               total        used        free      shared  buff/cache   available\nMem:              61          10          23           0          28          51\nSwap:              0           0           0","exit":[],"pics":[]},"tok":{"in":33465,"cached":32894,"out":103,"think":null,"usd":0.0115},"sim":{"submit":0,"reset":0}},{"id":5,"t":127.6,"say":"","calls":[{"kind":"shell","label":"python3 -c \"import PIL, scipy; print('ok')\"; pip list 2>/dev/null | head -50","code":"python3 -c \"import PIL, scipy; print('ok')\"; pip list 2>/dev/null | head -50"}],"out":{"text":"ok\nPackage            Version\n------------------ ---------\ncertifi            2026.7.22\ncharset-normalizer 3.5.2\nidna               3.20\nnumpy              2.5.3\npillow             12.3.0\npip                25.0.1\nrequests           2.34.2\nscipy              1.18.1\nurllib3            2.8.0\n\n[stdout]\nok\nPackage            Version\n------------------ ---------\ncertifi            2026.7.22\ncharset-normalizer 3.5.2\nidna               3.20\nnumpy              2.5.3\npillow             12.3.0\npip                25.0.1\nrequests           2.34.2\nscipy              1.18.1\nurllib3            2.8.0","exit":[],"pics":[]},"tok":{"in":34080,"cached":33463,"out":83,"think":null,"usd":0.0114},"sim":{"submit":0,"reset":0}},{"id":6,"t":129.5,"say":"","calls":[{"kind":"shell","label":"sleep 100; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output","code":"sleep 100; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output"}],"out":{"text":"(Bash completed with no output)","exit":[],"pics":[]},"tok":{"in":34299,"cached":34078,"out":107,"think":null,"usd":0.0101},"sim":{"submit":0,"reset":0}},{"id":7,"t":230.6,"say":"Waiting for the simulator to come up (cold start takes a few minutes).","calls":[{"kind":"shell","label":"sleep 110; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output","code":"sleep 110; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output"}],"out":{"text":"(Bash completed with no output)","exit":[],"pics":[]},"tok":{"in":34488,"cached":34297,"out":132,"think":null,"usd":0.0105},"sim":{"submit":0,"reset":0}},{"id":8,"t":342.6,"say":"","calls":[{"kind":"shell","label":"sleep 115; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output","code":"sleep 115; cat /tmp/claude-0/-app/bb394e3b-6be0-4c1b-ae76-dd877add1cef/tasks/bxipe603q.output"}],"out":{"text":"['protocol', 'protocol_compat', 'simulator', 'robot', 'task_text', 'control_hz', 'physics_substeps', 'max_chunk_s', 'max_watch_s', 'max_control_steps', 'cameras', 'default_cameras', 'action_types', 'proprio_layout', 'proprio_groups', 'static', 'world', 'budget', 'episode', 'robot_spec', 'kinematics', 'depth', 'on_service_error', 'max_call_wall_s']\n{'step': 0, 'calls': 0, 'control_steps': 0, 'done': False, 'reason': None, 'elapsed_s': 1.6, 'resumes': 0}\n\n[exited with code 0]\n\n[stdout]\n['protocol', 'protocol_compat', 'simulator', 'robot', 'task_text', 'control_hz', 'physics_substeps', 'max_chunk_s', 'max_watch_s', 'max_control_steps', 'cameras', 'default_cameras', 'action_types', 'proprio_layout', 'proprio_groups', 'static', 'world', 'budget', 'episode', 'robot_spec', 'kinematics', 'depth', 'on_service_error', 'max_call_wall_s']\n{'step': 0, 'calls': 0, 'control_steps': 0, 'done': False, 'reason': None, 'elapsed_s': 1.6, 'resumes': 0}\n\n[exited with code 0]","exit":[],"pics":[]},"tok":{"in":34659,"cached":34486,"out":107,"think":null,"usd":0.0099},"sim":{"submit":0,"reset":0}},{"id":9,"t":459.4,"say":"","calls":[{"kind":"shell","label":"for k in s:","code":"cd /app/runs; python3 -c \"\nimport json; s=json.load(open('spec.json'))\nfor k in s:\n  if k in ('proprio_layout',): print(k, len(s[k]), s[k][:80]); continue\n  print('=====',k); print(json.dumps(s[k],indent=None)[:3000])\n\""}],"out":{"text":"===== protocol\n\"eai-standard/2.2\"\n===== protocol_compat\n[\"rcb-limited/2.0\", \"rcb-limited/2.1\", \"eai-standard/2.1\"]\n===== simulator\n\"behavior-1k 3.9.2 (OmniGibson / Isaac Sim)\"\n===== robot\n\"r1pro\"\n===== task_text\n\"Box up the books for storage. Six books stand in the four bookcases of the living room, and an empty box stands on the living-room floor; put all six books inside the box.\"\n===== control_hz\n30\n===== physics_substeps\n4\n===== max_chunk_s\n10.0\n===== max_watch_s\n30.0\n===== max_control_steps\n200000\n===== cameras\n{\"robot_r1:left_realsense_link:Camera:0\": {\"rgb\": true, \"depth\": true, \"mounted\": \"left wrist\", \"resolution\": [224, 224], \"calibration_in_obs\": true, \"intrinsic_cv\": [[181.37651096845792, 0.0, 112.0], [0.0, 181.37651096845792, 112.0], [0.0, 0.0, 1.0]], \"mount\": {\"type\": \"link\", \"parent_link\": \"left_realsense_link\", \"link_T_cam_cv\": [[0.0, 1.0, 0.0, 0.0], [-1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]]}, \"depth_range_m\": [0.0010000000474974513, 65.535]}, \"robot_r1:right_realsense_link:Camera:0\": {\"rgb\": true, \"depth\": true, \"mounted\": \"right wrist\", \"resolution\": [224, 224], \"calibration_in_obs\": true, \"intrinsic_cv\": [[181.37651096845792, 0.0, 112.0], [0.0, 181.37651096845792, 112.0], [0.0, 0.0, 1.0]], \"mount\": {\"type\": \"link\", \"parent_link\": \"right_realsense_link\", \"link_T_cam_cv\": [[0.0, 1.0, 0.0, 0.0], [-1.0, 0.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]]}, \"depth_range_m\": [0.0010000000474974513, 65.535]}, \"robot_r1:zed_link:Cam\n… (28,255 characters left out) …\nhe other arm keeps its seed values\", \"seed_default\": \"the robot's reset configuration\", \"tol_pos_m\": 0.001, \"tol_rot_rad\": 0.01, \"max_iters\": 200, \"collision_checking\": \"none\", \"joint_limits\": \"enforced\"}, \"stateless\": true, \"note\": \"q = trunk + both arms (joint_names, all proprio columns of measured positions). Poses are in the base frame (base_link, see robot_spec.base) unless the request gives base_pose (x y z qx qy qz qw: the 7 base proprio columns); then they are in the world frame. The model is the simulator's own articulation (its joint frames), so FK of the measured joints gives the measured link poses.\"}\n===== depth\n{\"modes\": [\"none\", \"last\", \"frames\"], \"default\": \"none\", \"kind\": \"z-depth\", \"unit\": \"m\", \"invalid\": 0, \"max_m\": 65.535, \"frames_encoding\": \"uint16 mm, zlib\", \"noise\": \"off\"}\n===== on_service_error\n\"a connection error means the service crashed: it restarts and resumes the SAME episode (never a reset) in the state after the last call it completed, which you may not have received. Wait until GET /status answers again (rcb_client: Robot.wait_ready(); resuming replays the episode so far, which can take minutes in a long episode, and the wall clock keeps running), then check calls and control_steps before you continue. A 500 means the simulator failed: the episode is over (reason \\\"error\\\"). A call that runs longer than max_call_wall_s seconds stops at the next control step and returns what it executed (meta.stopped, executed_rows).\"\n===== max_call_wall_s\n900.0","exit":[],"pics":[]},"tok":{"in":35494,"cached":34657,"out":153,"think":null,"usd":0.0142},"sim":{"submit":0,"reset":0}},{"id":10,"t":461.2,"say":"","calls":[{"kind":"shell","label":"rs=s['robot_spec']","code":"cd /app/runs; python3 -c \"\nimport json; s=json.load(open('spec.json'))\nrs=s['robot_spec']\nfor k in rs:\n  if k=='joints': continue\n  print('==',k, json.dumps(rs[k])[:1500])\nprint(json.dumps(s['action_types']['ee_pose'])[1000:3000])\nprint(s['proprio_layout'][79:])\n\""}],"out":{"text":"== name \"R1Pro\"\n== description \"Galaxea R1 Pro as modelled in BEHAVIOR-1K 3.9.2: a holonomic wheeled base, a 4-joint trunk, two 7-joint arms with parallel-jaw grippers (2 prismatic fingers each), a head camera on the trunk, a wrist camera per arm\"\n== base {\"type\": \"mobile\", \"root_link\": \"base_link\", \"pose_proprio\": [\"base_x\", \"base_y\", \"base_z\", \"base_qx\", \"base_qy\", \"base_qz\", \"base_qw\"], \"frame\": \"base_link: x forward, y left, z up; the kinematics' base frame\", \"joints\": [\"base_footprint_x_joint\", \"base_footprint_y_joint\", \"base_footprint_z_joint\", \"base_footprint_rx_joint\", \"base_footprint_ry_joint\", \"base_footprint_rz_joint\"], \"command\": \"joint_position base_x, base_y, base_yaw: a displacement (m, m, rad) in the robot's own frame, applied at EVERY control step (30 Hz) the row covers: the base controller moves the targets of the virtual joints base_footprint_x_joint, base_footprint_y_joint, base_footprint_rz_joint by it (their stiff drives follow within the step; base_footprint_z_joint, base_footprint_rx_joint, base_footprint_ry_joint are passive). Zeros stand still.\", \"per_step_limits\": {\"x_m\": 0.15, \"y_m\": 0.15, \"yaw_rad\": 0.3}, \"velocity_limits\": {\"x_m_s\": 4.5, \"y_m_s\": 4.5, \"yaw_rad_s\": 9.0, \"note\": \"enforced: the per-step limits at 30 Hz (the virtual base joints themselves have no velocity or effort limit; the stiff drives follow almost the whole step); no rated base speed is known\"}, \"note\": \"the 6 virtual joints are proprio columns (group base_joint_pos) relative to\n… (11,113 characters left out) …\nt_eef_* pose; z along the fingers (approach), y along the finger travel; it lies between the finger pads, where assisted grasping holds objects\"}, \"right_tcp\": {\"parent_link\": \"right_eef_link\", \"link_T_frame\": [[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.018770679831504822], [0.0, 0.0, 0.0, 1.0]], \"definition\": \"the right fingertip centre (TCP): midway between the two fingertips, 1.88 cm along +z of right_eef_link, same orientation; the proprio tcp_po\n\n['left_tcp_x', 'left_tcp_y', 'left_tcp_z', 'left_tcp_qx', 'left_tcp_qy', 'left_tcp_qz', 'left_tcp_qw', 'right_tcp_x', 'right_tcp_y', 'right_tcp_z', 'right_tcp_qx', 'right_tcp_qy', 'right_tcp_qz', 'right_tcp_qw', 'base_footprint_x_joint_effort', 'base_footprint_y_joint_effort', 'base_footprint_z_joint_effort', 'base_footprint_rx_joint_effort', 'base_footprint_ry_joint_effort', 'base_footprint_rz_joint_effort', 'torso_joint1_effort', 'torso_joint2_effort', 'torso_joint3_effort', 'torso_joint4_effort', 'left_arm_joint1_effort', 'right_arm_joint1_effort', 'left_arm_joint2_effort', 'right_arm_joint2_effort', 'left_arm_joint3_effort', 'right_arm_joint3_effort', 'left_arm_joint4_effort', 'right_arm_joint4_effort', 'left_arm_joint5_effort', 'right_arm_joint5_effort', 'left_arm_joint6_effort', 'right_arm_joint6_effort', 'left_arm_joint7_effort', 'right_arm_joint7_effort', 'left_gripper_finger_joint1_effort', 'left_gripper_finger_joint2_effort', 'right_gripper_finger_joint1_effort', 'right_gripper_finger_joint2_effort']","exit":[],"pics":[]},"tok":{"in":43113,"cached":35492,"out":180,"think":null,"usd":0.0488},"sim":{"submit":0,"reset":0}},{"id":11,"t":464.7,"say":"","calls":[{"kind":"robot","label":"mkdir -p /app/output; cat > /app/output/lib.py <<'EOF'","code":"mkdir -p /app/output; cat > /app/output/lib.py <<'EOF'\nimport sys, json, time, os, numpy as np\nsys.path.insert(0, '/opt/tools')\nfrom rcb_client import Robot\nfrom PIL import Image\nfrom scipy.spatial.transform import Rotation as R\n\nHEAD = 'robot_r1:zed_link:Camera:0'\nLW = 'robot_r1:left_realsense_link:Camera:0'\nRW = 'robot_r1:right_realsense_link:Camera:0'\nr = Robot(timeout=1800)\nspec = r.spec()\nL = spec['proprio_layout']\nIDX = {n: i for i, n in enumerate(L)}\nCNT = [0]\nLOG = '/app/runs/log.txt'\n\ndef pv(now, names): return np.array([now[IDX[n]] for n in names])\n\ndef state(m=None):\n    if m is None: m = r.get_obs(cameras=[HEAD], video='none').meta\n    now = m['proprio']['now']\n    return now\n\ndef cur_action(now):\n    \"\"\"25-vector holding the current trunk/arm config, base zero, grippers as currently (open if opening>0.06).\"\"\"\n    a = np.zeros(25)\n    a[3:7] = pv(now, [f'torso_joint{i}' for i in range(1, 5)])\n    a[7:14] = pv(now, [f'left_arm_joint{i}' for i in range(1, 8)])\n    a[16:23] = pv(now, [f'right_arm_joint{i}' for i in range(1, 8)])\n    lo = now[IDX['left_gripper_opening']]; ro = now[IDX['right_gripper_opening']]\n    a[14:16] = 0.07 if lo > 0.07 else 0.0\n    a[23:25] = 0.07 if ro > 0.07 else 0.0\n    return a\n\ndef qkin(now):\n    return pv(now, spec['kinematics']['joint_names'])\n\ndef base_pose(now): return pv(now, ['base_x','base_y','base_z','base_qx','base_qy','base_qz','base_qw'])\n\ndef yaw(now):\n    q = base_pose(now)[3:]\n    return R.from_quat(q).as_euler('xyz')[2]\n\ndef tilt(now):\n    return np.cos(now[IDX['base_footprint_rx_joint']]) * np.cos(now[IDX['base_footprint_ry_joint']])\n\ndef save_imgs(res, tag, cams=None, depth=False):\n    d = f'/app/runs/img'; os.makedirs(d, exist_ok=True)\n    out = []\n    for cam, img in res.last.items():\n        if cams and cam not in cams: continue\n        short = {HEAD: 'head', LW: 'lw', RW: 'rw'}[cam]\n        p = f'{d}/{tag}_{short}.png'\n        Image.fromarray(img).resize((448, 448), Image.NEAREST).save(p); out.append(p)\n    return out\n\ndef summary(now):\n    bp = base_pose(now)\n    s = dict(base=np.round(bp[:3], 3).tolist(), yaw=round(float(yaw(now)), 3), tilt=round(float(tilt(now)), 3),\n             ltcp=np.round(pv(now, ['left_tcp_x','left_tcp_y','left_tcp_z']), 3).tolist(),\n             rtcp=np.round(pv(now, ['right_tcp_x','right_tcp_y','right_tcp_z']), 3).tolist(),\n             grip=np.round(pv(now, ['left_gripper_opening','right_gripper_opening']), 3).tolist())\n    return s\n\ndef submit(A, dt=0.1, **kw):\n    kw.setdefault('video', 'none')\n    res = r.submit('joint_position', np.asarray(A), dt=dt, **kw)\n    with open(LOG, 'a') as f: f.write(json.dumps(dict(t=time.time(), n=len(A), done=res.meta.get('done'), reason=res.meta.get('reason'), clipped=res.meta.get('clipped'), steps=res.meta.get('control_steps_chunk'))) + '\\n')\n    if res.meta.get('done'): print('DONE!!', res.meta.get('reason'))\n    return res\n\ndef drive(dx=0., dy=0., dyaw=0., T=1.0, speed=0.3, now=None, extra=None):\n    \"\"\"Drive in robot frame: total displacement dx,dy (m) and dyaw (rad) over rows dt=0.1 (3 steps each).\"\"\"\n    if now is None: now = state()\n    a = cur_action(now)\n    if extra is not None: a = extra\n    steps_needed = max(abs(dx) / (speed / 30), abs(dy) / (speed / 30), abs(dyaw) / (0.6 / 30), 1)\n    n = int(np.ceil(steps_needed))\n    rows = []\n    per = np.array([dx, dy, dyaw]) / n\n    for i in range(n):\n        row = a.copy(); row[0:3] = per; rows.append(row)\n    stop = a.copy(); stop[0:3] = 0; rows += [stop] * 3\n    return submit(np.array(rows), dt=1/30)\n\ndef look(tag='o', cams=None, depth=False):\n    res = r.get_obs(cameras=cams, video='none', depth=depth)\n    paths = save_imgs(res, tag)\n    return res, paths\nEOF\ncd /app/output && python3 -c \"\nfrom lib import *\nres,p=look('init', depth=True)\nnow=res.meta['proprio']['now']\nprint(summary(now)); print(p)\nprint(cur_action(now).round(3))\nprint(res.meta['cameras'][HEAD])\n\""}],"out":{"text":"{'base': [-1.711, -1.616, 0.005], 'yaw': 0.456, 'tilt': 1.0, 'ltcp': [-1.714, -1.337, 0.425], 'rtcp': [-1.492, -1.79, 0.425], 'grip': [0.1, 0.1]}\n['/app/runs/img/init_head.png', '/app/runs/img/init_lw.png', '/app/runs/img/init_rw.png']\n[ 0.     0.     0.     1.024 -1.448 -0.47  -0.     0.     0.    -0.\n  0.    -0.    -0.    -0.     0.07   0.07   0.     0.    -0.     0.\n -0.    -0.    -0.     0.07   0.07 ]\n{'intrinsic_cv': [[95.2, 0.0, 112.0], [0.0, 95.2, 112.0], [0.0, 0.0, 1.0]], 'extrinsic_cv': [[0.4404412036199115, -0.8977814578149561, 1.254971775356815e-05, -0.6977143605331866], [-0.34575990821670133, -0.16963871380983467, -0.9228611990147398, 0.5166757523051936], [0.8285298015302898, 0.40646175807890816, -0.38513271374369284, 2.390231242326234]], 'cam2world_gl': [[0.4404412036199118, 0.34575990821670144, -0.8285298015302902, -1.494429903385081], [-0.8977814578149564, 0.1696387138098346, -0.4064617580789083, -1.5102843986311871], [1.2549717753583678e-05, 0.92286119901474, 0.38513271374369307, 1.3973850052245727], [0.0, 0.0, 0.0, 1.0000000000000002]], 'image_size': [224, 224]}\n\n[stdout]\n{'base': [-1.711, -1.616, 0.005], 'yaw': 0.456, 'tilt': 1.0, 'ltcp': [-1.714, -1.337, 0.425], 'rtcp': [-1.492, -1.79, 0.425], 'grip': [0.1, 0.1]}\n['/app/runs/img/init_head.png', '/app/runs/img/init_lw.png', '/app/runs/img/init_rw.png']\n[ 0.     0.     0.     1.024 -1.448 -0.47  -0.     0.     0.    -0.\n  0.    -0.    -0.    -0.     0.07   0.07   0.     0.    -0.     0.\n -0.    -0.    -0.     0.07   0.07 ]\n{'intrinsic_cv': [[95.2, 0.0, 112.0], [0.0, 95.2, 112.0], [0.0, 0.0, 1.0]], 'extrinsic_cv': [[0.4404412036199115, -0.8977814578149561, 1.254971775356815e-05, -0.6977143605331866], [-0.34575990821670133, -0.16963871380983467, -0.9228611990147398, 0.5166757523051936], [0.8285298015302898, 0.40646175807890816, -0.38513271374369284, 2.390231242326234]], 'cam2world_gl': [[0.4404412036199118, 0.34575990821670144, -0.8285298015302902, -1.494429903385081], [-0.8977814578149564, 0.1696387138098346, -0.4064617580789083, -1.5102843986311871], [1.2549717753583678e-05, 0.92286119901474, 0.38513271374369307, 1.3973850052245727], [0.0, 0.0, 0.0, 1.0000000000000002]], 'image_size': [224, 224]}","exit":[],"pics":[]},"tok":{"in":46659,"cached":43111,"out":2248,"think":null,"usd":0.0713},"sim":{"submit":0,"reset":0}},{"id":12,"t":480.9,"say":"","calls":[{"kind":"look","label":"init_head.png","code":"/app/runs/img/init_head.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s012_0.jpg"]},"tok":{"in":49583,"cached":46657,"out":60,"think":null,"usd":0.0252},"sim":{"submit":0,"reset":0}},{"id":13,"t":483.3,"say":"Connected. The robot starts at (-1.71, -1.62) in what looks like a hallway, next to a staircase. Next I'll turn the base in a full circle and take head-camera pictures to find the living room.","calls":[{"kind":"robot","label":"for k in range(8):","code":"python3 -c \"\nfrom lib import *\nfor k in range(8):\n    res=drive(dyaw=np.pi/4)\n    res,p=look(f'scan{k}',cams=[HEAD])\n    print(k, summary(res.meta['proprio']['now']))\n\""}],"out":{"text":"0 {'base': [-1.71, -1.616, 0.005], 'yaw': 1.205, 'tilt': 1.0, 'ltcp': [-1.902, -1.414, 0.425], 'rtcp': [-1.432, -1.594, 0.425], 'grip': [0.1, 0.1]}\n1 {'base': [-1.71, -1.616, 0.005], 'yaw': 1.953, 'tilt': 1.0, 'ltcp': [-1.988, -1.599, 0.425], 'rtcp': [-1.521, -1.411, 0.425], 'grip': [0.1, 0.1]}\n2 {'base': [-1.71, -1.616, 0.005], 'yaw': 2.702, 'tilt': 1.0, 'ltcp': [-1.926, -1.793, 0.425], 'rtcp': [-1.711, -1.336, 0.425], 'grip': [0.1, 0.1]}\n3 {'base': [-1.71, -1.615, 0.005], 'yaw': -2.832, 'tilt': 1.0, 'ltcp': [-1.748, -1.892, 0.425], 'rtcp': [-1.901, -1.412, 0.425], 'grip': [0.1, 0.1]}\n4 {'base': [-1.71, -1.615, 0.005], 'yaw': -2.084, 'tilt': 1.0, 'ltcp': [-1.55, -1.843, 0.425], 'rtcp': [-1.989, -1.596, 0.425], 'grip': [0.1, 0.1]}\n5 {'base': [-1.711, -1.615, 0.005], 'yaw': -1.335, 'tilt': 1.0, 'ltcp': [-1.438, -1.673, 0.425], 'rtcp': [-1.928, -1.791, 0.425], 'grip': [0.1, 0.1]}\n6 {'base': [-1.711, -1.616, 0.005], 'yaw': -0.586, 'tilt': 1.0, 'ltcp': [-1.471, -1.472, 0.425], 'rtcp': [-1.75, -1.892, 0.425], 'grip': [0.1, 0.1]}\n7 {'base': [-1.711, -1.616, 0.005], 'yaw': 0.162, 'tilt': 1.0, 'ltcp': [-1.633, -1.348, 0.425], 'rtcp': [-1.551, -1.845, 0.425], 'grip': [0.1, 0.1]}\n\n[stdout]\n0 {'base': [-1.71, -1.616, 0.005], 'yaw': 1.205, 'tilt': 1.0, 'ltcp': [-1.902, -1.414, 0.425], 'rtcp': [-1.432, -1.594, 0.425], 'grip': [0.1, 0.1]}\n1 {'base': [-1.71, -1.616, 0.005], 'yaw': 1.953, 'tilt': 1.0, 'ltcp': [-1.988, -1.599, 0.425], 'rtcp': [-1.521, -1.411, 0.425], 'grip': [0.1, 0.1]}\n2 {'base': [-1.71, -1.616, 0.005], 'yaw': 2.702, 'tilt': 1.0, 'ltcp': [-1.926, -1.793, 0.425], 'rtcp': [-1.711, -1.336, 0.425], 'grip': [0.1, 0.1]}\n3 {'base': [-1.71, -1.615, 0.005], 'yaw': -2.832, 'tilt': 1.0, 'ltcp': [-1.748, -1.892, 0.425], 'rtcp': [-1.901, -1.412, 0.425], 'grip': [0.1, 0.1]}\n4 {'base': [-1.71, -1.615, 0.005], 'yaw': -2.084, 'tilt': 1.0, 'ltcp': [-1.55, -1.843, 0.425], 'rtcp': [-1.989, -1.596, 0.425], 'grip': [0.1, 0.1]}\n5 {'base': [-1.711, -1.615, 0.005], 'yaw': -1.335, 'tilt': 1.0, 'ltcp': [-1.438, -1.673, 0.425], 'rtcp': [-1.928, -1.791, 0.425], 'grip': [0.1, 0.1]}\n6 {'base': [-1.711, -1.616, 0.005], 'yaw': -0.586, 'tilt': 1.0, 'ltcp': [-1.471, -1.472, 0.425], 'rtcp': [-1.75, -1.892, 0.425], 'grip': [0.1, 0.1]}\n7 {'base': [-1.711, -1.616, 0.005], 'yaw': 0.162, 'tilt': 1.0, 'ltcp': [-1.633, -1.348, 0.425], 'rtcp': [-1.551, -1.845, 0.425], 'grip': [0.1, 0.1]}","exit":[],"pics":[]},"tok":{"in":49985,"cached":49581,"out":313,"think":null,"usd":0.0182},"sim":{"submit":8,"reset":0}},{"id":14,"t":520.2,"say":"","calls":[{"kind":"shell","label":"ims=[Image.open(f'scan{k}_head.png').resize((224,224)) for k in range(8)]","code":"cd /app/runs/img; python3 -c \"\nfrom PIL import Image\nims=[Image.open(f'scan{k}_head.png').resize((224,224)) for k in range(8)]\nM=Image.new('RGB',(224*4,224*2))\nfor k,im in enumerate(ims): M.paste(im,((k%4)*224,(k//4)*224))\nM.save('scan_montage.png')\n\""},{"kind":"look","label":"scan_montage.png","code":"/app/runs/img/scan_montage.png"}],"out":{"text":"(Bash completed with no output)\n[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s014_0.jpg"]},"tok":{"in":51175,"cached":49983,"out":282,"think":null,"usd":0.0216},"sim":{"submit":0,"reset":0}},{"id":15,"t":523.2,"say":"","calls":[{"kind":"look","label":"scan3_head.png","code":"/app/runs/img/scan3_head.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s015_0.jpg"]},"tok":{"in":52094,"cached":51173,"out":181,"think":null,"usd":0.0185},"sim":{"submit":0,"reset":0}},{"id":16,"t":527.0,"say":"","calls":[{"kind":"robot","label":"cat >> /app/output/lib.py <<'EOF'","code":"cat >> /app/output/lib.py <<'EOF'\n\nPCD = '/app/runs/pcd'\ndef backproject(rgb, depth, K, ext):\n    H, W = depth.shape\n    v, u = np.mgrid[0:H, 0:W]\n    z = depth\n    m = (z > 0.05) & (z < 8)\n    x = (u - K[0][2]) * z / K[0][0]; y = (v - K[1][2]) * z / K[1][1]\n    Pc = np.stack([x[m], y[m], z[m]], 1)\n    E = np.asarray(ext); Rm, t = E[:, :3], E[:, 3]\n    Pw = (Pc - t) @ Rm\n    return Pw, rgb[m]\n\ndef grab(tag, cams=(HEAD,), store=True):\n    res = r.get_obs(cameras=list(cams), video='none', depth=True)\n    save_imgs(res, tag)\n    if store:\n        os.makedirs(PCD, exist_ok=True)\n        for cam in cams:\n            mc = res.meta['cameras'][cam]\n            P, C = backproject(res.last[cam], res.last_depth[cam], mc['intrinsic_cv'], mc['extrinsic_cv'])\n            short = {HEAD: 'head', LW: 'lw', RW: 'rw'}[cam]\n            np.savez_compressed(f'{PCD}/{tag}_{short}.npz', P=P.astype(np.float32), C=C)\n    return res\n\ndef topdown(out='/app/runs/img/map.png', files=None, res_m=0.02, zmax=2.0, bounds=None, mark=None):\n    import glob\n    files = files or sorted(glob.glob(PCD + '/*.npz'))\n    P = np.concatenate([np.load(f)['P'] for f in files]); C = np.concatenate([np.load(f)['C'] for f in files])\n    k = (P[:, 2] < zmax) & (P[:, 2] > 0.03)\n    P, C = P[k], C[k]\n    if bounds is None: bounds = [P[:, 0].min(), P[:, 0].max(), P[:, 1].min(), P[:, 1].max()]\n    x0, x1, y0, y1 = bounds\n    W = int((x1 - x0) / res_m) + 1; H = int((y1 - y0) / res_m) + 1\n    img = np.full((H, W, 3), 255, np.uint8); zb = np.full((H, W), -1.0)\n    ix = ((P[:, 0] - x0) / res_m).astype(int); iy = ((y1 - P[:, 1]) / res_m).astype(int)\n    ok = (ix >= 0) & (ix < W) & (iy >= 0) & (iy < H)\n    order = np.argsort(P[ok, 2])\n    ix, iy, Cz, z = ix[ok][order], iy[ok][order], C[ok][order], P[ok, 2][order]\n    img[iy, ix] = Cz; zb[iy, ix] = z\n    if mark is not None:\n        for (mx, my) in mark:\n            jx = int((mx - x0) / res_m); jy = int((y1 - my) / res_m)\n            img[max(jy-3,0):jy+4, max(jx-3,0):jx+4] = [255, 0, 0]\n    Image.fromarray(img).save(out)\n    return bounds, zb\nEOF\ncd /app/output && python3 -c \"\nfrom lib import *\nfor k in range(8):\n    res=grab(f's{k}')\n    drive(dyaw=np.pi/4)\nnow=state(); print(summary(now))\nb,zb=topdown(mark=[tuple(base_pose(now)[:2])])\nprint(b)\n\""}],"out":{"text":"{'base': [-1.711, -1.616, 0.005], 'yaw': -0.131, 'tilt': 1.0, 'ltcp': [-1.559, -1.382, 0.425], 'rtcp': [-1.625, -1.881, 0.425], 'grip': [0.1, 0.1]}\n[np.float32(-6.4217157), np.float32(2.3281546), np.float32(-4.74283), np.float32(1.2194897)]\n\n[stdout]\n{'base': [-1.711, -1.616, 0.005], 'yaw': -0.131, 'tilt': 1.0, 'ltcp': [-1.559, -1.382, 0.425], 'rtcp': [-1.625, -1.881, 0.425], 'grip': [0.1, 0.1]}\n[np.float32(-6.4217157), np.float32(2.3281546), np.float32(-4.74283), np.float32(1.2194897)]","exit":[],"pics":[]},"tok":{"in":52574,"cached":52092,"out":1545,"think":null,"usd":0.0437},"sim":{"submit":8,"reset":0}},{"id":17,"t":558.5,"say":"","calls":[{"kind":"look","label":"map.png","code":"/app/runs/img/map.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s017_0.jpg"]},"tok":{"in":54330,"cached":52572,"out":58,"think":null,"usd":0.0205},"sim":{"submit":0,"reset":0}},{"id":18,"t":560.8,"say":"","calls":[{"kind":"shell","label":"cat >> /app/output/lib.py <<'EOF'","code":"cat >> /app/output/lib.py <<'EOF'\n\ndef topdown2(out='/app/runs/img/map.png', bounds=None, res_m=0.025, zmin=0.03, zmax=2.0, mark=None, files=None, scale=2):\n    b, zb = topdown(out, files=files, res_m=res_m, zmax=zmax, bounds=bounds, mark=mark)\n    img = np.array(Image.open(out))\n    x0, x1, y0, y1 = b\n    for gx in np.arange(np.ceil(x0), x1, 1.0):\n        img[:, int((gx - x0) / res_m)] = [0, 160, 0] if gx != 0 else [0, 0, 255]\n    for gy in np.arange(np.ceil(y0), y1, 1.0):\n        img[int((y1 - gy) / res_m), :] = [0, 160, 0] if gy != 0 else [0, 0, 255]\n    Image.fromarray(img).resize((img.shape[1] * scale, img.shape[0] * scale), Image.NEAREST).save(out)\n    return b\nEOF\npython3 -c \"\nfrom lib import *\nnow=state()\nprint(topdown2(mark=[tuple(base_pose(now)[:2])], bounds=[-7,2.5,-5,1.5], zmin=0.03))\n\""}],"out":{"text":"[-7, 2.5, -5, 1.5]\n\n[stdout]\n[-7, 2.5, -5, 1.5]","exit":[],"pics":[]},"tok":{"in":54607,"cached":54328,"out":633,"think":null,"usd":0.0249},"sim":{"submit":0,"reset":0}},{"id":19,"t":565.9,"say":"","calls":[{"kind":"look","label":"map.png","code":"/app/runs/img/map.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s019_0.jpg"]},"tok":{"in":55329,"cached":54605,"out":58,"think":null,"usd":0.0157},"sim":{"submit":0,"reset":0}},{"id":20,"t":579.6,"say":"","calls":[{"kind":"robot","label":"cat >> /app/output/lib.py <<'EOF'","code":"cat >> /app/output/lib.py <<'EOF'\n\ndef wrap(a): return (a + np.pi) % (2 * np.pi) - np.pi\n\ndef goto(x, y, th=None, speed=0.4, tol=0.02, iters=4, arm=None):\n    for it in range(iters):\n        now = state()\n        bp = base_pose(now); cy = yaw(now)\n        dth = 0.0 if th is None else wrap(th - cy)\n        d = np.array([x - bp[0], y - bp[1]])\n        # displacement expressed in the current robot frame (rotation applied simultaneously -> do rotation first)\n        if abs(dth) > 0.03:\n            drive(dyaw=dth, now=now, extra=arm); continue\n        c, s = np.cos(cy), np.sin(cy)\n        dr = np.array([c * d[0] + s * d[1], -s * d[0] + c * d[1]])\n        if np.linalg.norm(dr) < tol: break\n        drive(dx=dr[0], dy=dr[1], speed=speed, now=now, extra=arm)\n    now = state(); print('goto ->', summary(now)); return now\nEOF\npython3 -c \"\nfrom lib import *\ngoto(-4.3,-1.3,np.pi)\n\""}],"out":{"text":"goto -> {'base': [-4.299, -1.301, 0.005], 'yaw': -3.132, 'tilt': 1.0, 'ltcp': [-4.073, -1.551, 0.511], 'rtcp': [-4.078, -1.047, 0.511], 'grip': [0.1, 0.1]}\n\n[stdout]\ngoto -> {'base': [-4.299, -1.301, 0.005], 'yaw': -3.132, 'tilt': 1.0, 'ltcp': [-4.073, -1.551, 0.511], 'rtcp': [-4.078, -1.047, 0.511], 'grip': [0.1, 0.1]}","exit":[],"pics":[]},"tok":{"in":55962,"cached":55327,"out":1481,"think":null,"usd":0.0439},"sim":{"submit":4,"reset":0}},{"id":21,"t":609.3,"say":"","calls":[{"kind":"robot","label":"for k in range(8):","code":"python3 -c \"\nfrom lib import *\nfor k in range(8):\n    res=grab(f'm{k}')\n    drive(dyaw=np.pi/4)\nnow=state(); print(summary(now))\ntopdown2(mark=[tuple(base_pose(now)[:2])], bounds=[-7.5,2.5,-5,1.5])\n\"\ncd /app/runs/img; python3 -c \"\nfrom PIL import Image\nims=[Image.open(f'm{k}_head.png').resize((224,224)) for k in range(8)]\nM=Image.new('RGB',(224*4,224*2))\nfor k,im in enumerate(ims): M.paste(im,((k%4)*224,(k//4)*224))\nM.save('m_montage.png')\n\""},{"kind":"look","label":"m_montage.png","code":"/app/runs/img/m_montage.png"},{"kind":"look","label":"map.png","code":"/app/runs/img/map.png"}],"out":{"text":"DONE!! failure: the robot fell over\n{'base': [-4.287, -1.312, 0.424], 'yaw': 0.47, 'tilt': -0.27, 'ltcp': [-4.916, -0.858, 0.17], 'rtcp': [-4.549, -0.936, 0.536], 'grip': [0.1, 0.1]}\n\n[stdout]\nDONE!! failure: the robot fell over\n{'base': [-4.287, -1.312, 0.424], 'yaw': 0.47, 'tilt': -0.27, 'ltcp': [-4.916, -0.858, 0.17], 'rtcp': [-4.549, -0.936, 0.536], 'grip': [0.1, 0.1]}\n[picture]\n\n[metadata] [picture]}\n[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s021_0.jpg","behavior-boxing-books-up-for-storage-i00-standard--grtqedt/s021_0.jpg"]},"tok":{"in":57580,"cached":55960,"out":606,"think":null,"usd":0.0314},"sim":{"submit":8,"reset":0}},{"id":22,"t":639.8,"say":"","calls":[{"kind":"shell","label":"print(r.status())","code":"cd /app/output; python3 -c \"\nfrom lib import *\nprint(r.status())\n\"; tail -5 /app/runs/log.txt"}],"out":{"text":"{'step': 1389, 'calls': 85, 'control_steps': 1389, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 282.2, 'resumes': 0}\n{\"t\": 1791663551.7927196, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663554.8938396, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663557.454893, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663560.0479074, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663562.3861086, \"n\": 43, \"done\": true, \"reason\": \"failure: the robot fell over\", \"clipped\": [], \"steps\": 30}\n\n[stdout]\n{'step': 1389, 'calls': 85, 'control_steps': 1389, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 282.2, 'resumes': 0}\n{\"t\": 1791663551.7927196, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663554.8938396, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663557.454893, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663560.0479074, \"n\": 43, \"done\": false, \"reason\": null, \"clipped\": [], \"steps\": 43}\n{\"t\": 1791663562.3861086, \"n\": 43, \"done\": true, \"reason\": \"failure: the robot fell over\", \"clipped\": [], \"steps\": 30}","exit":[],"pics":[]},"tok":{"in":59513,"cached":57578,"out":618,"think":null,"usd":0.0335},"sim":{"submit":0,"reset":0}},{"id":23,"t":652.5,"say":"","calls":[{"kind":"robot","label":"try:","code":"cd /app/output; python3 -c \"\nfrom lib import *\ntry:\n    res=r.get_obs(video='none')\n    now=res.meta['proprio']['now']; print(summary(now)); print(cur_action(now).round(3))\nexcept Exception as e: print(type(e).__name__, e)\n\""}],"out":{"text":"{'base': [-4.287, -1.312, 0.424], 'yaw': 0.47, 'tilt': -0.27, 'ltcp': [-4.916, -0.858, 0.17], 'rtcp': [-4.549, -0.936, 0.536], 'grip': [0.1, 0.1]}\n[ 0.000e+00  0.000e+00  0.000e+00 -5.060e-01 -1.645e+00 -4.690e-01\n -1.117e+00 -4.000e-02  8.000e-03  4.000e-03  1.730e-01  5.100e-02\n -1.500e-02  2.400e-02  7.000e-02  7.000e-02 -2.000e-03  1.600e-02\n  2.800e-02 -2.220e-01 -1.100e-02  1.000e-03  7.000e-03  7.000e-02\n  7.000e-02]\n\n[stdout]\n{'base': [-4.287, -1.312, 0.424], 'yaw': 0.47, 'tilt': -0.27, 'ltcp': [-4.916, -0.858, 0.17], 'rtcp': [-4.549, -0.936, 0.536], 'grip': [0.1, 0.1]}\n[ 0.000e+00  0.000e+00  0.000e+00 -5.060e-01 -1.645e+00 -4.690e-01\n -1.117e+00 -4.000e-02  8.000e-03  4.000e-03  1.730e-01  5.100e-02\n -1.500e-02  2.400e-02  7.000e-02  7.000e-02 -2.000e-03  1.600e-02\n  2.800e-02 -2.220e-01 -1.100e-02  1.000e-03  7.000e-03  7.000e-02\n  7.000e-02]","exit":[],"pics":[]},"tok":{"in":60501,"cached":59511,"out":1139,"think":null,"usd":0.0396},"sim":{"submit":0,"reset":0}},{"id":24,"t":659.0,"say":"The episode is over: the robot fell over about 280 s in, and with no reset that means the task failed. Let me save the script for the record and a note about the cause.","calls":[{"kind":"shell","label":"\"\"\"Record of the episode actually run (boxing_books_up_for_storage, eai-standard/2.2).","code":"cd /app/output; cat > gen.py <<'EOF'\n\"\"\"Record of the episode actually run (boxing_books_up_for_storage, eai-standard/2.2).\n\nHelpers live in /app/output/lib.py. Sequence executed:\n  1. connect, take an observation, 360-degree in-place scan at the start pose (8 x 45 deg) with head RGB-D,\n  2. build a top-down point-cloud map (bookcases along the y ~ -0.6 wall, x -6.6..-3.1; sofa, coffee table, desk, stairs),\n  3. drive to (-4.3, -1.3, yaw pi) and start a second scan.\nThe robot fell over at the start of the second scan (episode ended: \"failure: the robot fell over\").\nCause: every base command re-sent the *measured* trunk/arm joints as targets (lib.cur_action), so the trunk sagged\nunder gravity a little each time and the sag accumulated (torso_joint1 1.02 -> -0.51, torso_joint4 0 -> -1.12) until the\ncentre of mass left the base. The fix would be to keep a fixed commanded configuration instead of feeding back\nmeasurements.\n\"\"\"\nimport numpy as np\nfrom lib import *\n\ndef main():\n    for k in range(8):\n        grab(f's{k}'); drive(dyaw=np.pi / 4)\n    topdown2(bounds=[-7, 2.5, -5, 1.5])\n    goto(-4.3, -1.3, np.pi)\n    for k in range(8):\n        grab(f'm{k}'); drive(dyaw=np.pi / 4)\n\nif __name__ == '__main__':\n    main()\nEOF\ncat > /logs/agent/sessions/projects/-app/memory/r1pro-trunk-drift-fall.md <<'EOF'\n---\nname: r1pro-trunk-drift-fall\ndescription: BEHAVIOR R1Pro service: never re-command measured trunk/arm joints as targets — trunk sags cumulatively and the robot tips over\nmetadata:\n  type: feedback\n---\nIn the BEHAVIOR-1K R1Pro robot-as-a-service tasks (joint_position action), building each command from the *measured*\ntrunk/arm joints made the trunk creep under gravity on each call (torso_joint1 1.02 -> -0.51, torso_joint4 0 -> -1.12\nover ~80 base-driving calls) until the robot fell over, which ended the only episode as a failure (2026-10-10, boxing_books_up_for_storage).\n\n**Why:** trunk effort limit is 100 N m; each re-command at the sagged pose lets it sag a bit further — the error ratchets.\n**How to apply:** keep a persistent *commanded* configuration (start from the initial reading once, then change it only\ndeliberately); check tilt and trunk joints against the commanded values after every call and stop if they drift.\nEOF\necho \"- [R1Pro trunk drift fall](r1pro-trunk-drift-fall.md) — never feed measured joints back as targets; trunk sags and robot tips\" >> /logs/agent/sessions/projects/-app/memory/MEMORY.md"}],"out":{"text":"(Bash completed with no output)","exit":[],"pics":[]},"tok":{"in":62008,"cached":60499,"out":1503,"think":null,"usd":0.0497},"sim":{"submit":0,"reset":0}},{"id":25,"t":676.5,"say":"The task failed: the robot fell over about 4.7 minutes in (1,389 control steps), before it had touched a single book. The service ended the episode with `failure: the robot fell over`, and since there's no reset, nothing more can be done in this run.\n\n**What happened**\n- I connected, turned the robot in a full circle at its start point (-1.71, -1.62), and built an overhead map from the head camera's depth images. It shows the living room: bookcases along the wall at y≈-0.6 (x from -6.6 to -3.1), an L-shaped sofa, a coffee table, a desk and the staircase. I hadn't spotted the box yet.\n- I drove to (-4.3, -1.3), facing -x, to scan again. The drive ended with the base still upright, but the first image of the new scan already showed the ceiling. The robot was tipping, and the service stopped the episode during that scan.\n\n**Likely cause (my bug):** every movement command re-sent the trunk and arm joint angles as measured at that moment, rather than a fixed set of target angles. The trunk sags a little under gravity, so each command let it sag further. By the end, `torso_joint1` had gone from 1.02 to -0.51 rad and `torso_joint4` from 0 to -1.12 rad, which moved the centre of mass far enough to tip the robot. The final joint readings and the falling camera view support this, but I had no per-frame recording, so it's an inference rather than something I watched happen. The fix is to keep one fixed set of target angles and check the trunk against it after every call.\n\nThe script is at `/app/output/gen.py`, with its helpers in `/app/output/lib.py`. I also saved a memory note about this so it isn't repeated.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":63550,"cached":62006,"out":621,"think":null,"usd":0.0325},"sim":{"submit":0,"reset":0}}]}