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runs/behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u.json

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+{"slug":"behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u","task":"behavior-cleaning-up-plates-and-food-i00-standard","bench":"behavior","mode":"standard","run":"claude_code-qwen3_8_max-high","agent":"claude-code","model":"qwen3.8-max","effort":"high","state":"failed","success":0,"reward":{"success":0,"live_success":0,"graded_by_live":1,"replays":0,"finalized":1,"missing_log":0,"n_actions":427,"sim_steps":427,"physics_steps":1708,"steps":317,"elapsed_s":1264.1,"video_rendered":1,"video_live":1,"video_pending":0,"settled_success":0,"settle_steps":0,"sim_breakdown":0,"instance_ok":1,"task_failure":1,"sim_error":0,"sim_crashed_on_call":0,"q_score":0.0,"goal_first_step":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":1,"peak_gpu_memory_gb":0.0,"peak_memory_gb":0.0,"peak_processes":0.0,"peak_disk_gb":0.0,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":2141,"tokens":{"in":1983130,"cached":1893608,"out":50964,"usd":2.78},"task_text":"# BEHAVIOR-1K · cleaning_up_plates_and_food — 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:** Clean up after the meal in the kitchen. On the breakfast table stand two plates, each with a pizza on it, and two bowls. Put both pizzas, each still on its own plate, into the same refrigerator, put both bowls into the same sink, and leave every kitchen refrigerator closed. Success means all of the following hold at the same time: (1) each pizza is on top of a different plate; (2) both pizzas are inside the same refrigerator; (3) both bowls are inside the same sink; (4) every kitchen refrigerator is closed. 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. ontop(A, B): A touches B and B is directly below A (and not above it). open(A): at least one of A's openable joints (door, drawer, lid) is more than 5% of the way from closed to fully open; closed (not open) means every such joint is within 5% of closed. The service checks the goal; it counts once it has held for 1 s, released and at rest (Rules).\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, on a simulator error or breakdown, or at the runaway guard. Whatever you knock over or push away stays where it ends up.\n- **Success is a settled scene**: the goal has held for 1 s of simulated time in a row (30 control steps) with no goal\n  object in a gripper (assisted grasping lets go only when both fingers are commanded open) and every goal object at\n  rest (slower than 0.05 m/s); then the episode ends (`meta[\"reason\"]` \"success\"). An object still in the hand, or a\n  goal that holds for one frame, is not success. Open the gripper, move clear and let the robot stand (e.g.\n  `r.get_obs(seconds=2.0)`). The goal objects are every object the goal names, a tool or appliance it names (even\n  inside a `not`) included. When your episode is still running at the end of your time (you stopped early, or your\n  time ran out), the service holds the robot still (your last command, the\n  base at 0) for up to 5 s more on the same simulator, and a goal that settles there counts; the service judges the\n  episode itself, nothing is replayed.\n- A simulator breakdown (a non-finite or runaway robot or goal-object state, e.g. after the robot tumbles; reason\n  \"failure: simulator breakdown\") ends the episode as a failure.\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  tim\n… (7,137 characters left out) …\nll 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 457 s on average (13,696 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## External material\nYou may install packages you need (pip, apt), and you may read anything installed in your container, the simulator's and this benchmark's own source code included. Please solve the task yourself: do not search the web for, or download, a ready-made solution to it, such as published or reference solutions, recorded demonstrations, or policies trained for it. This is an honour rule; trials are reviewed. The network reaches your model's API and the package registries (PyPI, Debian / Ubuntu archives) only.\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\n## Time limit\nYou have 7200 seconds to complete this task. Do not cheat by using online solutions or hints specific to this task.\n\nThis is wall-clock time from the start of your session; the time you wait for the simulator service counts. When it is up you are stopped without warning and the episode is graded as it stands at that moment. The service's `time_left_s` counts the same limit from your first request to the service, so it never runs out before your time does: your real time left is `time_left_s` minus the time you spent before that request. Plan by it. Your session started when you received this task. `/run/rcb-limits/usage.json`, rewritten every few seconds, gives the time left on this limit (`time_left_s`) and its end (`deadline_utc`), counted from a little before your session started, so it never gives you more time than you have: read it (or run `date`) before you decide that time is short, never guess. Waiting counts too: a tool call that sends input to a process that keeps running (an interactive interpreter, a simulator loop, a server) can wait for the whole wait or yield time you give it (for example Codex's `yield_time_ms`) even when the answer is printed at once, so give such calls a short wait and poll again if the output is not complete, or run one-shot scripts that exit when they are done. Installing packages is not cheating (`## External material` above).\n","step_times":"recorded","sim_total":{"submit":19,"reset":0},"replay":null,"replay_last":null,"steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"Check time budget and directory layout","code":"date -u; cat /run/rcb-limits/usage.json 2>/dev/null; echo; ls /app /app/output /opt/tools 2>&1"},{"kind":"shell","label":"Check client size and installed packages","code":"wc -l /opt/tools/rcb_client.py; python3 -c \"import sys; print(sys.version)\"; pip list 2>/dev/null | grep -Ei 'numpy|opencv|scipy|torch' "}],"out":{"text":"Fri Oct 23 11:58:35 UTC 2026\n{\n \"t\": 1792756714.77,\n \"measured\": false,\n \"why\": \"this runner cannot run the resource monitor (its container runtime refuses `pid: host`): usage is not measured and the limits are not enforced; the clock is kept\",\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 \"elapsed_s\": 80.0,\n \"time_limit_s\": 7200,\n \"time_left_s\": 7120.0,\n \"deadline_utc\": \"2026-10-23T13:57:14Z\"\n}\n/app:\noutput\n\n/app/output:\n\n/opt/tools:\nrcb1.py\nrcb_client.py\n\n[stdout]\nFri Oct 23 11:58:35 UTC 2026\n{\n \"t\": 1792756714.77,\n \"measured\": false,\n \"why\": \"this runner cannot run the resource monitor (its container runtime refuses `pid: host`): usage is not measured and the limits are not enforced; the clock is kept\",\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 \"elapsed_s\": 80.0,\n \"time_limit_s\": 7200,\n \"time_left_s\": 7120.0,\n \"deadline_utc\": \"2026-10-23T13:57:14Z\"\n}\n/app:\noutput\n\n/app/output:\n\n/opt/tools:\nrcb1.py\nrcb_client.py\n243 /opt/tools/rcb_client.py\n3.12.14 (main, Sep 19 2026, 01:04:57) [GCC 14.2.0]\nnumpy              2.5.3\nscipy              1.18.1\n\n[stdout]\n243 /opt/tools/rcb_client.py\n3.12.14 (main, Sep 19 2026, 01:04:57) [GCC 14.2.0]\nnumpy              2.5.3\nscipy              1.18.1","exit":[],"pics":[]},"tok":{"in":18551,"cached":12905,"out":2456,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":9.3,"say":"","calls":[{"kind":"shell","label":"reads rcb_client.py","code":"/opt/tools/rcb_client.py"},{"kind":"shell","label":"Peek at rcb1.py","code":"wc -l /opt/tools/rcb1.py; head -50 /opt/tools/rcb1.py"}],"out":{"text":"1\t\"\"\"eai-standard/2.2 client (formerly rcb-limited/2.x) — the only thing a standard-mode agent gets (installed at\n2\t/opt/tools/rcb_client.py).\n3\t\n4\t    from rcb_client import Robot\n5\t    r = Robot()                                  # finds the service (sim:8000, then localhost:8000), waits for warm-up\n6\t    spec = r.spec()                              # actions, cameras (+ intrinsics, mounting), robot_spec, world, budget, kinematics\n7\t    obs = r.get_obs()                            # current frames: obs.last[cam] -> uint8 (H,W,3); obs.meta[\"proprio\"]\n8\t    obs = r.get_obs(depth=True)                  # + obs.last_depth[cam] -> float32 (H,W) z-depth in metres, 0 = no reading\n9\t    res = r.submit(\"joint_position\", A, dt=0.1)  # A: (T, dim) rows dt apart; returns the execution video\n10\t    res = r.submit(\"ee_pose\", P)                 # (T, dim) end-effector targets (see spec()[\"action_types\"])\n11\t    res.video[cam] -> mp4 bytes    res.frames[cam] -> uint8 (N,H,W,3) if video=\"frames\"/\"both\"    res.last[cam]\n12\t    res.proprio -> float32 (N, D), one row per frame (names: spec()[\"proprio_layout\"]; res.group(\"tcp_pose\"))\n13\t    res.frame_step -> int64 (N,) control step of each frame    res.frame_time_s -> float64 (N,) simulated time\n14\t    res.extrinsic_cv[cam] -> float64 (N,3,4) world->camera per frame (res.meta[\"cameras\"]: intrinsics + the last frame's pose)\n15\t    res = r.submit(..., depth=\"frames\")          # + res.depth[cam] -> float32 (N,H,W) metres, one per frame (1 mm steps\n… (19,569 characters left out) …\ntype/shape/fps/n.\"\"\"\n    hdr_parts = []\n    for name, kind, blob, extra in parts:\n        d = {\"name\": name, \"kind\": kind, \"len\": len(blob)}\n        d.update({k: v for k, v in (extra or {}).items() if v is not None})\n        hdr_parts.append(d)\n    header = json.dumps({\"v\": 1, \"meta\": meta, \"parts\": hdr_parts}, separators=(\",\", \":\")).encode()\n    return b\"\".join([MAGIC, struct.pack(\"<I\", len(header)), header] + [blob for _, _, blob, _ in parts])\n\n\ndef array_part(name: str, arr, extra: dict | None = None) -> tuple[str, str, bytes, dict]:\n    import numpy as np\n    a = np.ascontiguousarray(arr)\n    return (name, \"array\", a.tobytes(), {\"dtype\": str(a.dtype), \"shape\": list(a.shape), **(extra or {})})\n\n\ndef decode(buf: bytes, arrays: bool = True) -> tuple[dict, dict]:\n    \"\"\"-> (meta, parts) where parts[name] = {\"kind\", ..., \"data\"}; arrays become numpy arrays when arrays=True.\"\"\"\n    if buf[:4] != MAGIC:\n        raise ValueError(\"not an RCB1 frame\")\n    n = struct.unpack(\"<I\", buf[4:8])[0]\n    header = json.loads(buf[8:8 + n].decode()); off = 8 + n\n    out = {}\n    for p in header[\"parts\"]:\n        blob = buf[off:off + p[\"len\"]]; off += p[\"len\"]\n        d = dict(p)\n        if p[\"kind\"] == \"array\" and arrays:\n            import numpy as np\n            d[\"data\"] = np.frombuffer(blob, dtype=np.dtype(p[\"dtype\"])).reshape(p[\"shape\"])\n        elif p[\"kind\"] == \"json\":\n            d[\"data\"] = json.loads(blob.decode())\n        else:\n            d[\"data\"] = blob\n        out[p[\"name\"]] = d","exit":[],"pics":[]},"tok":{"in":21364,"cached":18545,"out":118,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":4,"t":150.7,"say":"","calls":[{"kind":"shell","label":"Install image packages and create work dirs","code":"mkdir -p /app/work /app/runs /app/output && pip install --quiet opencv-python-headless pillow requests 2>&1 | tail -1; python3 -c \"import cv2, PIL; print('cv2', cv2.__version__)\""}],"out":{"text":"[notice] To update, run: pip install --upgrade pip\ncv2 5.0.0\n\n[stdout]\n[notice] To update, run: pip install --upgrade pip\ncv2 5.0.0","exit":[],"pics":[]},"tok":{"in":27521,"cached":27515,"out":511,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":5,"t":202.4,"say":"","calls":[{"kind":"edit","label":"phase0.py","code":"/app/work/phase0.py\n\n\"\"\"Phase 0: connect to the sim service, dump spec + first observation (RGB-D, all cameras).\"\"\"\nimport json, sys, time, pathlib\nimport numpy as np\n\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot, EpisodeOver\n\nOUT = pathlib.Path(\"/app/work\")\nOUT.mkdir(parents=True, exist_ok=True)\n\nt0 = time.time()\nprint(f\"[{time.strftime('%H:%M:%S')}] connecting...\", flush=True)\nr = Robot()\nprint(f\"[{time.time()-t0:.0f}s] connected to {r.base}\", flush=True)\n\nspec = r.spec()\n(OUT / \"spec.json\").write_text(json.dumps(spec, indent=1))\nprint(\"spec keys:\", list(spec.keys()), flush=True)\n\ntry:\n    st = r.status()\n    print(\"status:\", json.dumps(st, indent=1)[:2000], flush=True)\nexcept EpisodeOver as e:\n    print(\"EPISODE OVER:\", e, flush=True)\n    sys.exit(1)\n\nimport cv2\nobs = r.get_obs(depth=True, video=\"none\")\nprint(\"obs meta keys:\", list(obs.meta.keys()), flush=True)\nprint(\"time_left_s:\", obs.meta.get(\"time_left_s\"), flush=True)\ncamdir = OUT / \"cam0\"\ncamdir.mkdir(exist_ok=True)\nfor cam, img in obs.last.items():\n    safe = cam.replace(\":\", \"_\")\n    cv2.imwrite(str(camdir / f\"{safe}.png\"), cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\n    print(\"saved\", cam, img.shape, flush=True)\nfor cam, d in obs.last_depth.items():\n    safe = cam.replace(\":\", \"_\")\n    np.save(camdir / f\"{safe}_depth.npy\", d)\n    print(\"depth\", cam, d.shape, float(np.min(d)), float(np.max(d)), float(np.mean(d > 0)), flush=True)\njson.dump({k: (v if not isinstance(v, np.ndarray) else v.tolist()) for k, v in obs.meta.items() if k in (\"cameras\", \"proprio\")}, open(OUT / \"obs0_meta.json\", \"w\"), indent=1, default=str)\nprint(\"proprio layout:\", spec.get(\"proprio_layout\"), flush=True)\nprint(\"proprio now:\", np.asarray(obs.meta[\"proprio\"][\"now\"]).tolist(), flush=True)\nprint(\"DONE phase0\", flush=True)\n"}],"out":{"text":"File created successfully at: /app/work/phase0.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":28070,"cached":27515,"out":606,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":6,"t":271.3,"say":"","calls":[{"kind":"shell","label":"Start phase0 connect script in background","code":"cd /app/work && nohup python3 -I phase0.py > phase0.log 2>&1 &\necho started; sleep 5; cat phase0.log"},{"kind":"shell","label":"Look for simulator/benchmark sources in container","code":"find / -maxdepth 6 \\( -iname '*omnigibson*' -o -iname '*behavior*' \\) -not -path '/proc/*' -not -path '/sys/*' 2>/dev/null | head -20; ls /opt 2>/dev/null; ls /srv /data 2>/dev/null"}],"out":{"text":"Exit code 1\nstarted\ncat: phase0.log: No such file or directory\n\n[error] tool reported failure\nExit code 2\ntools\nvkclamp\n/srv:\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":28720,"cached":28064,"out":235,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":7,"t":287.3,"say":"","calls":[{"kind":"shell","label":"Start phase0 with absolute paths","code":"nohup python3 -I /app/work/phase0.py > /app/work/phase0.log 2>&1 & echo pid=$!; sleep 8; cat /app/work/phase0.log; ls /app/work"},{"kind":"shell","label":"Inspect /opt contents","code":"ls /opt/vkclamp 2>/dev/null | head; ls -la /opt/tools"}],"out":{"text":"pid=666\n[12:03:22] connecting...\nphase0.log\nphase0.py\n\n[stdout]\npid=666\n[12:03:22] connecting...\nphase0.log\nphase0.py\nconf\nlibvkclamp.so\ntotal 24\ndrwxr-xr-x 1 root root    33 Oct 23 12:03 .\ndrwxr-xr-x 1 root root    46 Oct 23 11:57 ..\ndrwxr-xr-x 2 root root    80 Oct 23 12:03 __pycache__\n-rw-r--r-- 1 root root  3881 Dec  6  2012 rcb1.py\n-rw-r--r-- 1 root root 16896 Feb 11  2005 rcb_client.py\n\n[stdout]\nconf\nlibvkclamp.so\ntotal 24\ndrwxr-xr-x 1 root root    33 Oct 23 12:03 .\ndrwxr-xr-x 1 root root    46 Oct 23 11:57 ..\ndrwxr-xr-x 2 root root    80 Oct 23 12:03 __pycache__\n-rw-r--r-- 1 root root  3881 Dec  6  2012 rcb1.py\n-rw-r--r-- 1 root root 16896 Feb 11  2005 rcb_client.py","exit":[],"pics":[]},"tok":{"in":29007,"cached":28714,"out":228,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":499.2,"say":"Connection is starting (takes minutes). Meanwhile, I'll write my helper library for perception and motion.","calls":[{"kind":"edit","label":"helpers.py","code":"/app/work/helpers.py\n\n\"\"\"Shared helpers: connect, RGB-D -> world pointcloud, proprio access, base driving, arm IK.\"\"\"\nimport json, sys, time, pathlib\nimport numpy as np\n\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot, EpisodeOver\n\nWORK = pathlib.Path(\"/app/work\")\n\nHEAD = \"robot_r1:zed_link:Camera:0\"\nLWRIST = \"robot_r1:left_realsense_link:Camera:0\"\nRWRIST = \"robot_r1:right_realsense_link:Camera:0\"\n\ndef log(*a):\n    print(f\"[{time.strftime('%H:%M:%S')}]\", *a, flush=True)\n\ndef connect():\n    r = Robot()\n    return r\n\n# ---------------- geometry ----------------\n\ndef unproject(depth, K, E):\n    \"\"\"depth (H,W) z-depth metres (0=no reading); K intrinsic_cv 3x3; E extrinsic_cv 3x4 world->cam.\n    Returns (pts_world (N,3), uv (N,2)) for pixels with depth>0.\"\"\"\n    H, W = depth.shape\n    v, u = np.nonzero(depth > 0)\n    d = depth[v, u].astype(np.float64)\n    fx, fy = K[0, 0], K[1, 1]\n    cx, cy = K[0, 2], K[1, 2]\n    x = (u - cx) * d / fx\n    y = (v - cy) * d / fy\n    p_cam = np.stack([x, y, d], axis=1)\n    R = E[:, :3].astype(np.float64)\n    t = E[:, 3].astype(np.float64)\n    p_world = (p_cam - t) @ R  # R^T (p - t) since R orthonormal: (p-t) @ R == R^T (p-t) rowwise\n    return p_world, np.stack([u, v], axis=1)\n\ndef world_to_pixel(pts_world, K, E):\n    R = E[:, :3].astype(np.float64); t = E[:, 3].astype(np.float64)\n    p_cam = pts_world @ R.T + t\n    z = p_cam[:, 2]\n    u = p_cam[:, 0] * K[0, 0] / np.where(z == 0, 1e-9, z) + K[0, 2]\n    v = p_cam[:, 1] * K[1, 1] / np.where(z == 0, 1e-9, z) + K[1, 2]\n    return np.stack([u, v], axis=1), z\n\n# ---------------- proprio ----------------\n\ndef proprio_now(obs_or_res):\n    return np.asarray(obs_or_res.meta[\"proprio\"][\"now\"], dtype=np.float64)\n\ndef group_now(r, obs_or_res, name):\n    first, n = r.spec()[\"proprio_groups\"][name][:2]\n    p = proprio_now(obs_or_res)\n    return p[first:first + n]\n\n# ---------------- observation ----------------\n\ndef get_rgbd(r, cam=HEAD, seconds=0.0):\n    obs = r.get_obs(cameras=[cam], seconds=seconds, depth=True, video=\"none\")\n    img = obs.last[cam]\n    d = obs.last_depth[cam]\n    cams = obs.meta[\"cameras\"][cam]\n    K = np.asarray(cams[\"intrinsic_cv\"], dtype=np.float64)\n    E = np.asarray(cams[\"extrinsic_cv\"], dtype=np.float64)\n    return obs, img, d, K, E\n\n# ---------------- base driving ----------------\n\ndef drive_chunk(r, q_hold, base_rows, dt=0.2, note=\"\", cameras=None):\n    \"\"\"base_rows: (T,3) per-step base displacement targets [x,y,yaw] in robot frame.\n    q_hold: current joint targets (trunk+arms+grippers layout of joint_position minus base) to hold.\"\"\"\n    B = np.asarray(base_rows, dtype=np.float32).reshape(-1, 3)\n    T = B.shape[0]\n    A = np.zeros((T, 25), dtype=np.float32)\n    A[:, 0:3] = B\n    A[:, 3:] = np.asarray(q_hold, dtype=np.float32)[None, :]\n    return r.submit(\"joint_position\", A, dt=dt, note=note, cameras=cameras, video=\"mp4\")\n\ndef joint_layout(spec):\n    return spec[\"action_types\"][\"joint_position\"]\n\n# ---------------- arm motion via IK ----------------\n\ndef q_from_proprio(r, obs_or_res):\n    \"\"\"Return kinematics q (trunk + both arms) from proprio now.\"\"\"\n    spec = r.spec()\n    names = spec[\"kinematics\"][\"joint_names\"]\n    p = proprio_now(obs_or_res)\n    layout = spec[\"proprio_layout\"]\n    idx = {n: i for i, n in enumerate(layout)}\n    return np.array([p[idx[n]] for n in names], dtype=np.float64)\n\ndef base_pose7(r, obs_or_res):\n    return group_now(r, obs_or_res, \"base_pose\")\n"}],"out":{"text":"File created successfully at: /app/work/helpers.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":29436,"cached":29430,"out":3993,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":747.6,"say":"","calls":[{"kind":"shell","label":"Poll phase0 connection log","code":"sleep 60; cat /app/work/phase0.log"}],"out":{"text":"[12:03:22] connecting...\n[rcb_client] still waiting for the sim service to start (60 s of at most 3600 s; last answer: HTTPConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /spec (Caused by NewConnectionError(\"HTTPConnection(host='localhost', port=8000): Failed to establish a new connection: )\n[rcb_client] still waiting for the sim service to start (120 s of at most 3600 s; last answer: HTTPConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /spec (Caused by NewConnectionError(\"HTTPConnection(host='localhost', port=8000): Failed to establish a new connection: )\n[144s] connected to http://localhost:8000\nspec keys: ['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']\nstatus: {\n \"step\": 0,\n \"calls\": 1,\n \"control_steps\": 0,\n \"done\": false,\n \"reason\": null,\n \"elapsed_s\": 1.0,\n \"resumes\": 0\n}\nobs meta keys: ['step', 'calls', 'control_steps', 'physics_steps', 'sim_time_s', 'time_s', 'time_left_s', 'proprio', 'done', 'reason', 'cameras', 'obs_id', 'seconds', 'control_steps_watch', 'physics_steps_watch', 'ok', 'stopped']\ntime_left_s: 7199.9\nsaved robot_r1:zed_link:Camera:0 (224, 224, 3)\nsaved robot_r1:left_realsense_link:Camera:0 (224, 224, 3)\n\n… (11,485 characters left out) …\n72848272324, 0.0008756308816373348, 0.0005998756969347596, 0.03119554929435253, -0.163793683052063, -0.00981174223124981, -0.00155929708853364, -0.014750590547919273, -0.015507991425693035, -0.005299550015479326, -0.005049450322985649, 0.0030498169362545013, 0.009702350944280624, -0.008346609771251678, -0.0074401902966201305, 0.0028918711468577385, 0.0078342966735363, -0.0011799396015703678, -0.0005458431551232934, 0.00802344735711813, 0.009192444384098053, -0.00010044689406640828, 0.00021936726989224553, -0.00013127230340614915, 0.0002776535984594375, 0.09999905526638031, 0.09999899566173553, 5.09025239944458, 2.7186315059661865, 0.4256777763366699, -0.662427544593811, -0.7487838864326477, -0.014998194761574268, 0.016956886276602745, 4.5900139808654785, 2.6571199893951416, 0.42568373680114746, -0.6624535322189331, -0.7487608194351196, -0.014996224083006382, 0.016961585730314255, 6.100882053375244, -10.63471794128418, -4.1961669921875e-05, 2.480047260178253e-05, -7.921669748611748e-06, -3.720233678817749, -98.01127624511719, -42.55864334106445, 24.161149978637695, 0.1261444091796875, 6.9333672523498535, 6.355535507202148, -0.8607228398323059, -0.8392754197120667, -0.0352935791015625, -0.0024399757385253906, 2.0362253189086914, 1.8617026805877686, -0.031636714935302734, -0.008483529090881348, 0.21474473178386688, 0.2223896086215973, -0.0408206470310688, -0.046843767166137695, -0.006950225681066513, 0.0070923324674367905, -0.011407217010855675, 0.010818337090313435]\nDONE phase0","exit":[],"pics":[]},"tok":{"in":33471,"cached":33465,"out":67,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":845.3,"say":"Connected in ~2.4 min. Let me inspect the spec and the first frames.","calls":[{"kind":"shell","label":"Dump key spec fields","code":"python3 - <<'EOF'\nimport json\ns = json.load(open('/app/work/spec.json'))\nfor k in ('protocol','simulator','robot','task_text','control_hz','max_chunk_s','max_watch_s','max_control_steps','default_cameras','world','budget','episode','depth','max_call_wall_s'):\n    print(k, '=', json.dumps(s.get(k))[:600])\nprint('cameras:')\nfor c, d in s['cameras'].items():\n    print(' ', c, json.dumps(d)[:500])\nprint('proprio_groups:', json.dumps(s['proprio_groups']))\nprint('kinematics:', json.dumps(s['kinematics'])[:800])\nprint('action_types:', json.dumps(s['action_types'])[:1500])\nEOF"}],"out":{"text":"protocol = \"eai-standard/2.2\"\nsimulator = \"behavior-1k 3.9.2 (OmniGibson / Isaac Sim)\"\nrobot = \"r1pro\"\ntask_text = \"Clean up after the meal in the kitchen. On the breakfast table stand two plates, each with a pizza on it, and two bowls. Put both pizzas, each still on its own plate, into the same refrigerator, put both bowls into the same sink, and leave every kitchen refrigerator closed.\"\ncontrol_hz = 30\nmax_chunk_s = 10.0\nmax_watch_s = 30.0\nmax_control_steps = 200000\ndefault_cameras = [\"robot_r1:zed_link:Camera:0\", \"robot_r1:left_realsense_link:Camera:0\", \"robot_r1:right_realsense_link:Camera:0\"]\nworld = {\"frame\": \"OmniGibson's world frame of the scene: right-handed, z up, the floor is the plane z = 0 (the robot starts on it); x and y horizontal. The robot's base frame (robot_spec.base) is its base_link: x forward, y left, z up\", \"up\": \"+z\", \"units\": {\"length\": \"m\", \"angle\": \"rad\", \"time\": \"s\"}, \"quaternion_order\": \"xyzw\", \"camera_axes\": \"intrinsic_cv / extrinsic_cv: OpenCV (x right, y down, z forward); cam2world_gl: OpenGL (x right, y up, z backward)\", \"camera_timing\": \"a frame (RGB and depth) shows the scene as rendered 2 control steps (67 ms) before its frame_step while the robot moves; its\nbudget = {\"reset\": 0, \"steps\": null, \"wall_clock_s\": 7200.0, \"clock\": \"meta time_s / time_left_s count from your first request to the service (any endpoint), not from the service's start, and keep running through a restart of the service; time_left_s = budget.wall_clock_s - time_s. The\n… (12,101 characters left out) …\n{\"joint_position\": {\"dim\": 25, \"layout\": [\"base_x\", \"base_y\", \"base_yaw\", \"trunk_0\", \"trunk_1\", \"trunk_2\", \"trunk_3\", \"arm_left_0\", \"arm_left_1\", \"arm_left_2\", \"arm_left_3\", \"arm_left_4\", \"arm_left_5\", \"arm_left_6\", \"gripper_left_0\", \"gripper_left_1\", \"arm_right_0\", \"arm_right_1\", \"arm_right_2\", \"arm_right_3\", \"arm_right_4\", \"arm_right_5\", \"arm_right_6\", \"gripper_right_0\", \"gripper_right_1\"], \"blocks\": {\"base\": [0, 3], \"trunk\": [3, 7], \"arm_left\": [7, 14], \"gripper_left\": [14, 16], \"arm_right\": [16, 23], \"gripper_right\": [23, 25]}, \"units\": \"base x, y (m) and yaw (rad) are per-control-step position targets in the ROBOT frame (re-applied every step: hold them to keep driving); trunk and arm entries are absolute joint targets in rad; each gripper is 2 finger targets, 0 = closed (robot_spec.grippers: the open command is the finger's upper limit + 0.02)\", \"limits\": {\"base_x\": [-0.15, 0.15], \"base_y\": [-0.15, 0.15], \"base_yaw\": [-0.3, 0.3], \"trunk_0\": [-1.1344999074935913, 1.8325998783111572], \"trunk_1\": [-2.7924997806549072, 2.5306997299194336], \"trunk_2\": [-1.8325998783111572, 1.5707999467849731], \"trunk_3\": [-3.054299831390381, 3.054299831390381], \"arm_left_0\": [-4.4506001472473145, 1.309000015258789], \"arm_left_1\": [-0.1745000034570694, 3.1415998935699463], \"arm_left_2\": [-2.3561956882476807, 2.3561956882476807], \"arm_left_3\": [-2.0943996906280518, 0.3490999639034271], \"arm_left_4\": [-2.3561956882476807, 2.3561956882476807], \"arm_left_5\": [-1.0471980571746826, 1.04719805717468","exit":[],"pics":[]},"tok":{"in":37734,"cached":33465,"out":1303,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":11,"t":860.8,"say":"","calls":[{"kind":"shell","label":"Dump robot_spec","code":"python3 - <<'EOF'\nimport json\ns = json.load(open('/app/work/spec.json'))\nrs = s['robot_spec']\nprint(json.dumps({k: v for k, v in rs.items() if k not in ('joints',)}, indent=1)[:3000])\nprint('JOINTS:')\nfor j in rs.get('joints', []):\n    print(' ', json.dumps(j)[:220])\nEOF"}],"out":{"text":"{\n \"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\": {\n  \"type\": \"mobile\",\n  \"root_link\": \"base_link\",\n  \"pose_proprio\": [\n   \"base_x\",\n   \"base_y\",\n   \"base_z\",\n   \"base_qx\",\n   \"base_qy\",\n   \"base_qz\",\n   \"base_qw\"\n  ],\n  \"frame\": \"base_link: x forward, y left, z up; the kinematics' base frame\",\n  \"joints\": [\n   \"base_footprint_x_joint\",\n   \"base_footprint_y_joint\",\n   \"base_footprint_z_joint\",\n   \"base_footprint_rx_joint\",\n   \"base_footprint_ry_joint\",\n   \"base_footprint_rz_joint\"\n  ],\n  \"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.\",\n  \"per_step_limits\": {\n   \"x_m\": 0.15,\n   \"y_m\": 0.15,\n   \"yaw_rad\": 0.3\n  },\n  \"velocity_limits\": {\n   \"x_m_s\": 4.5,\n   \"y_m_s\": 4.5,\n   \"yaw_rad_s\": 9.0,\n   \"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\n… (12,839 characters left out) …\nrad\", \"position_limits\": [-1.0471980571746826, 1.0471980571746826], \"velocity_limit\": 10.472000122070312, \"effort_limit\": 18.0, \"rated_velocity\": 10.472, \"rated_e\n  {\"name\": \"left_arm_joint7\", \"type\": \"revolute\", \"unit\": \"rad\", \"position_limits\": [-1.5707999467849731, 1.5707999467849731], \"velocity_limit\": 10.472000122070312, \"effort_limit\": 18.0, \"rated_velocity\": 10.472, \"rated_ef\n  {\"name\": \"right_arm_joint7\", \"type\": \"revolute\", \"unit\": \"rad\", \"position_limits\": [-1.5707999467849731, 1.5707999467849731], \"velocity_limit\": 10.472000122070312, \"effort_limit\": 18.0, \"rated_velocity\": 10.472, \"rated_e\n  {\"name\": \"left_gripper_finger_joint1\", \"type\": \"prismatic\", \"unit\": \"m\", \"position_limits\": [0.0, 0.05000000074505806], \"velocity_limit\": 0.25, \"effort_limit\": 100.0, \"rated_velocity\": 0.25, \"rated_effort\": 100.0, \"rated\n  {\"name\": \"left_gripper_finger_joint2\", \"type\": \"prismatic\", \"unit\": \"m\", \"position_limits\": [0.0, 0.05000000074505806], \"velocity_limit\": 0.25, \"effort_limit\": 100.0, \"rated_velocity\": 0.25, \"rated_effort\": 100.0, \"rated\n  {\"name\": \"right_gripper_finger_joint1\", \"type\": \"prismatic\", \"unit\": \"m\", \"position_limits\": [0.0, 0.05000000074505806], \"velocity_limit\": 0.25, \"effort_limit\": 100.0, \"rated_velocity\": 0.25, \"rated_effort\": 100.0, \"rate\n  {\"name\": \"right_gripper_finger_joint2\", \"type\": \"prismatic\", \"unit\": \"m\", \"position_limits\": [0.0, 0.05000000074505806], \"velocity_limit\": 0.25, \"effort_limit\": 100.0, \"rated_velocity\": 0.25, \"rated_effort\": 100.0, \"rate","exit":[],"pics":[]},"tok":{"in":42104,"cached":37728,"out":415,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":936.7,"say":"","calls":[{"kind":"shell","label":"Dump ee_pose spec and kinematics targets","code":"python3 - <<'EOF'\nimport json\ns = json.load(open('/app/work/spec.json'))\nprint(json.dumps(s['action_types']['ee_pose'], indent=1)[:1200])\nprint('tcp:', json.dumps(s['robot_spec'].get('tcp', {}), indent=1)[:600])\nprint('kinematics keys:', list(s['kinematics'].keys()))\nprint('ik_targets:', json.dumps(s['kinematics'].get('ik_targets'))[:400])\nprint('links:', json.dumps(s['kinematics'].get('links'))[:1200])\nEOF"}],"out":{"text":"{\n \"dim\": 16,\n \"layout\": [\n  \"l_x\",\n  \"l_y\",\n  \"l_z\",\n  \"l_qx\",\n  \"l_qy\",\n  \"l_qz\",\n  \"l_qw\",\n  \"left_gripper\",\n  \"r_x\",\n  \"r_y\",\n  \"r_z\",\n  \"r_qx\",\n  \"r_qy\",\n  \"r_qz\",\n  \"r_qw\",\n  \"right_gripper\"\n ],\n \"frame\": \"OmniGibson world frame, metres, +z up (the floor is z = 0)\",\n \"quaternion\": \"xyzw, unit norm\",\n \"semantics\": \"each row: cuRobo inverse kinematics for both end effectors together (trunk + both arms; no collision checking), then the trunk and arm joints are driven there in joint space (at most 0.02 rad per control step); `dt` is ignored; the base stands still; if the IK finds no solution nothing moves and plan[] says so; gripper 1 = open, 0 = closed, switched at the start of the row (closing on an object holds it: assisted grasping)\",\n \"note\": \"the pose is the end-effector frame of the proprio `*_eef_*` entries, so an observed pose is a valid target; at most 50 rows per submit\"\n}\ntcp: {\n \"left_eef_link\": {\n  \"parent_link\": \"left_eef_link\",\n  \"link_T_frame\": [\n   [\n    1.0,\n    0.0,\n    0.0,\n    0.0\n   ],\n   [\n    0.0,\n    1.0,\n    0.0,\n    0.0\n   ],\n   [\n    0.0,\n    0.0,\n    1.0,\n    0.0\n   ],\n   [\n    0.0,\n    0.0,\n    0.0,\n    1.0\n   ]\n  ],\n  \"definition\": \"the left end-effector frame (left_eef_link): the frame of the ee_pose action and of the proprio left_eef_* pose; z along the fingers (approach), y along the finger travel; it lies between the finger pads, where assisted grasping holds objects\"\n },\n \"left_tcp\": {\n  \"parent_link\": \"left_eef_link\",\n  \"link_T_frame\": \n… (1,513 characters left out) …\n \"note\": \"the pose is the end-effector frame of the proprio `*_eef_*` entries, so an observed pose is a valid target; at most 50 rows per submit\"\n}\ntcp: {\n \"left_eef_link\": {\n  \"parent_link\": \"left_eef_link\",\n  \"link_T_frame\": [\n   [\n    1.0,\n    0.0,\n    0.0,\n    0.0\n   ],\n   [\n    0.0,\n    1.0,\n    0.0,\n    0.0\n   ],\n   [\n    0.0,\n    0.0,\n    1.0,\n    0.0\n   ],\n   [\n    0.0,\n    0.0,\n    0.0,\n    1.0\n   ]\n  ],\n  \"definition\": \"the left end-effector frame (left_eef_link): the frame of the ee_pose action and of the proprio left_eef_* pose; z along the fingers (approach), y along the finger travel; it lies between the finger pads, where assisted grasping holds objects\"\n },\n \"left_tcp\": {\n  \"parent_link\": \"left_eef_link\",\n  \"link_T_frame\": [\n  \nkinematics keys: ['endpoint', 'joint_names', 'frame', 'base_pose_proprio', 'quaternion_order', 'links', 'tcp_frames', 'ee_frames', 'ik_targets', 'ik', 'stateless', 'note']\nik_targets: [\"left_eef_link\", \"right_eef_link\", \"left_tcp\", \"right_tcp\"]\nlinks: [\"base_link\", \"torso_link1\", \"torso_link2\", \"torso_link3\", \"torso_link4\", \"left_arm_link1\", \"left_arm_link2\", \"left_arm_link3\", \"left_arm_link4\", \"left_arm_link5\", \"left_arm_link6\", \"left_arm_link7\", \"right_arm_link1\", \"right_arm_link2\", \"right_arm_link3\", \"right_arm_link4\", \"right_arm_link5\", \"right_arm_link6\", \"right_arm_link7\", \"left_gripper_link\", \"left_realsense_link\", \"right_gripper_link\", \"right_realsense_link\", \"left_eef_link\", \"right_eef_link\", \"zed_link\", \"left_tcp\", \"right_tcp\"]","exit":[],"pics":[]},"tok":{"in":46011,"cached":46005,"out":191,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":961.1,"say":"","calls":[{"kind":"look","label":"robot_r1_zed_link_Camera_0.png","code":"/app/work/cam0/robot_r1_zed_link_Camera_0.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s013_0.jpg"]},"tok":{"in":47036,"cached":46005,"out":194,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":14,"t":977.2,"say":"The scene is visible: table with pizzas/bowls on the right, fridge center-front, counters left. Let me build a point-cloud analysis.","calls":[{"kind":"edit","label":"analyze0.py","code":"/app/work/analyze0.py\n\n\"\"\"Analyse head RGB-D: world pointcloud, colour clusters for pizza/bowls, planes for table/counter/fridge.\"\"\"\nimport json, sys, pathlib\nimport numpy as np\nimport cv2\n\nsys.path.insert(0, \"/app/work\")\nfrom helpers import unproject, HEAD, LWRIST, RWRIST\n\nCAM = \"cam0\"\nmeta = json.load(open(\"/app/work/obs0_meta.json\"))\ncams = meta[\"cameras\"]\nimg = cv2.imread(f\"/app/work/{CAM}/{HEAD.replace(':', '_')}.png\")\nimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\ndepth = np.load(f\"/app/work/{CAM}/{HEAD.replace(':', '_')}_depth.npy\")\nK = np.asarray(cams[HEAD][\"intrinsic_cv\"]); E = np.asarray(cams[HEAD][\"extrinsic_cv\"])\nP, uv = unproject(depth, K, E)\nrgb = img[uv[:, 1].astype(int), uv[:, 0].astype(int)].astype(np.float32)\nprint(\"pts\", P.shape, \"x range\", P[:, 0].min(), P[:, 0].max(), \"y\", P[:, 1].min(), P[:, 1].max(), \"z\", P[:, 2].min(), P[:, 2].max())\n\nhsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)[uv[:, 1].astype(int), uv[:, 0].astype(int)].astype(np.float32)\nH, S, V = hsv[:, 0] * 2, hsv[:, 1] / 255, hsv[:, 2] / 255  # H in degrees\n\ndef cluster(mask, min_n=60):\n    \"\"\"connected-ish clustering by voxel grid\"\"\"\n    pts = P[mask]\n    if len(pts) == 0: return []\n    from scipy.cluster.vq import kmeans2\n    # simple: greedy radius clustering\n    out = []\n    idx = np.arange(len(pts))\n    cell = 0.06\n    key = np.floor(pts / cell).astype(int)\n    seen = {}\n    lab = -np.ones(len(pts), dtype=int)\n    nl = 0\n    order = np.argsort(-pts[:, 2])\n    for i in order:\n        k = tuple(key[i])\n        if k in seen: lab[i] = seen[k]; continue\n        lab[i] = nl; seen[k] = nl; nl += 1\n    # merge via dict of counts\n    res = []\n    for l in range(nl):\n        m = lab == l\n        if m.sum() < min_n: continue\n        res.append((m, pts[m]))\n    return res\n\n# pizza: orange-red, saturated\nm_pizza = ((H < 30) | (H > 330)) & (S > 0.45) & (V > 0.35) & (P[:, 2] > 0.3)\nprint(\"pizza px\", m_pizza.sum())\nfrom scipy import ndimage\nmask_img = m_pizza  # already pixel-order over uv\n# rebuild 2D mask\nM2 = np.zeros(depth.shape, bool)\nM2[uv[:, 1].astype(int), uv[:, 0].astype(int)] = m_pizza\nlab2, n2 = ndimage.label(M2)\nprint(\"pizza components\", n2)\nfor i in range(1, n2 + 1):\n    m = lab2 == i\n    if m.sum() < 80: continue\n    sel = np.zeros(depth.shape, bool)\n    sel[m] = True\n    keep = np.zeros(len(P), bool)\n    pxy = uv.astype(int)\n    keep = sel[pxy[:, 1], pxy[:, 0]] & m_pizza\n    c = P[keep]\n    print(f\"  pizza comp {i}: n={m.sum()} centre={c.mean(0).round(3)} zrange=({c[:,2].min():.2f},{c[:,2].max():.2f}) extent=({(c[:,0].max()-c[:,0].min()):.2f},{(c[:,1].max()-c[:,1].min()):.2f})\")\n    col = rgb[keep].mean(0)\n    print(\"    mean rgb\", col.round(0))\n\n# white/bright small objects above table height: bowls & plates\nM2w = np.zeros(depth.shape, bool)\nm_white = (S < 0.18) & (V > 0.55) & (P[:, 2] > 0.4) & (P[:, 2] < 1.4)\nM2w[uv[:, 1].astype(int), uv[:, 0].astype(int)] = m_white\nlab2w, n2w = ndimage.label(M2w)\nprint(\"white comps\", n2w)\nfor i in range(1, n2w + 1):\n    m = lab2w == i\n    if m.sum() < 60: continue\n    sel = np.zeros(depth.shape, bool); sel[m] = True\n    pxy = uv.astype(int)\n    keep = sel[pxy[:, 1], pxy[:, 0]] & m_white\n    c = P[keep]\n    print(f\"  white comp {i}: n={m.sum()} centre={c.mean(0).round(3)} z=({c[:,2].min():.2f},{c[:,2].max():.2f}) ext=({(c[:,0].max()-c[:,0].min()):.2f},{(c[:,1].max()-c[:,1].min()):.2f},{(c[:,2].max()-c[:,2].min()):.2f})\")\n"}],"out":{"text":"File created successfully at: /app/work/analyze0.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":47269,"cached":12865,"out":1767,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":15,"t":1009.4,"say":"","calls":[{"kind":"shell","label":"Run point-cloud color analysis","code":"cd /app/work && python3 -I analyze0.py 2>&1 | tail -40"}],"out":{"text":"pts (50176, 3) x range 1.3602258887835803 8.442268242505158 y -1.0716835988803766 2.2559497223976663 z 0.004625964593260624 2.3489256277355377\npizza px 1132\npizza components 59\n  pizza comp 19: n=159 centre=[3.974 1.298 0.718] zrange=(0.71,0.73) extent=(0.29,0.26)\n    mean rgb [195.  88.  35.]\n  pizza comp 44: n=479 centre=[4.08  1.802 0.714] zrange=(0.70,0.72) extent=(0.28,0.29)\n    mean rgb [200.  89.  36.]\n  pizza comp 54: n=121 centre=[4.89  2.028 0.485] zrange=(0.34,0.64) extent=(0.26,0.02)\n    mean rgb [137. 100.  68.]\n  pizza comp 58: n=156 centre=[4.68  2.157 0.465] zrange=(0.30,0.61) extent=(0.12,0.11)\n    mean rgb [130.  94.  65.]\nwhite comps 67\n  white comp 1: n=783 centre=[ 6.835 -0.826  1.166] z=(0.79,1.38) ext=(2.75,0.87,0.60)\n  white comp 12: n=562 centre=[ 2.73  -0.988  0.726] z=(0.40,1.29) ext=(1.20,0.01,0.89)\n  white comp 50: n=64 centre=[3.834 1.352 0.673] z=(0.44,0.71) ext=(0.64,0.66,0.27)\n  white comp 56: n=222 centre=[4.481 1.588 0.716] z=(0.68,0.74) ext=(0.33,0.35,0.06)\n  white comp 58: n=987 centre=[4.897 1.809 0.503] z=(0.44,0.78) ext=(0.35,0.51,0.34)\n  white comp 64: n=307 centre=[4.136 1.783 0.695] z=(0.68,0.71) ext=(0.43,0.44,0.03)\n  white comp 67: n=60 centre=[4.972 1.99  0.466] z=(0.45,0.54) ext=(0.11,0.06,0.09)\n\n[stdout]\npts (50176, 3) x range 1.3602258887835803 8.442268242505158 y -1.0716835988803766 2.2559497223976663 z 0.004625964593260624 2.3489256277355377\npizza px 1132\npizza components 59\n  pizza comp 19: n=159 centre=[3.974 1.298 0.718] zrange=(0.71,0.73) extent=(0.29,0.26)\n    mean rgb [195.  88.  35.]\n  pizza comp 44: n=479 centre=[4.08  1.802 0.714] zrange=(0.70,0.72) extent=(0.28,0.29)\n    mean rgb [200.  89.  36.]\n  pizza comp 54: n=121 centre=[4.89  2.028 0.485] zrange=(0.34,0.64) extent=(0.26,0.02)\n    mean rgb [137. 100.  68.]\n  pizza comp 58: n=156 centre=[4.68  2.157 0.465] zrange=(0.30,0.61) extent=(0.12,0.11)\n    mean rgb [130.  94.  65.]\nwhite comps 67\n  white comp 1: n=783 centre=[ 6.835 -0.826  1.166] z=(0.79,1.38) ext=(2.75,0.87,0.60)\n  white comp 12: n=562 centre=[ 2.73  -0.988  0.726] z=(0.40,1.29) ext=(1.20,0.01,0.89)\n  white comp 50: n=64 centre=[3.834 1.352 0.673] z=(0.44,0.71) ext=(0.64,0.66,0.27)\n  white comp 56: n=222 centre=[4.481 1.588 0.716] z=(0.68,0.74) ext=(0.33,0.35,0.06)\n  white comp 58: n=987 centre=[4.897 1.809 0.503] z=(0.44,0.78) ext=(0.35,0.51,0.34)\n  white comp 64: n=307 centre=[4.136 1.783 0.695] z=(0.68,0.71) ext=(0.43,0.44,0.03)\n  white comp 67: n=60 centre=[4.972 1.99  0.466] z=(0.45,0.54) ext=(0.11,0.06,0.09)","exit":[],"pics":[]},"tok":{"in":49079,"cached":47263,"out":143,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":16,"t":1061.1,"say":"","calls":[{"kind":"edit","label":"survey.py","code":"/app/work/survey.py\n\n\"\"\"Panorama survey: rotate base in place, capture RGB-D from head cam at each yaw offset.\"\"\"\nimport json, sys, time, pathlib\nimport numpy as np\nimport cv2\n\nsys.path.insert(0, \"/app/work\"); sys.path.insert(0, \"/opt/tools\")\nfrom helpers import connect, get_rgbd, HEAD, log\nfrom rcb_client import EpisodeOver\n\nOUT = pathlib.Path(\"/app/work/survey\"); OUT.mkdir(parents=True, exist_ok=True)\nr = connect()\nspec = r.spec()\nobs = r.get_obs(depth=True, video=\"none\")\np = np.asarray(obs.meta[\"proprio\"][\"now\"])\nq_now = p[6:28].copy()   # trunk4+arms14+fingers4 = 22 -> joint_position cols 3:25\nviews = {}\nyaw_steps = [0.0, -0.5, -0.5, -0.5, -0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]  # cumulative deltas\ncum = 0.0\nfor i, dy in enumerate(yaw_steps):\n    if dy != 0.0:\n        n = int(round(abs(dy) / 0.15))\n        sgn = np.sign(dy)\n        A = np.zeros((n, 25), dtype=np.float32)\n        A[:, 2] = sgn * 0.15\n        A[:, 3:] = q_now\n        res = r.submit(\"joint_position\", A, dt=1/30, note=f\"yaw {dy}\", video=\"none\")\n        cum += dy\n        log(\"rotated\", dy, \"cum\", cum, \"steps\", res.meta.get(\"control_steps_chunk\"))\n    obs, img, d, K, E = get_rgbd(r, HEAD)\n    views[i] = dict(cum=float(cum), base=p_base.tolist() if (p_base := np.asarray(obs.meta[\"proprio\"][\"now\"])[28:35]).any() else None)\n    np.save(OUT / f\"v{i}_depth.npy\", d)\n    cv2.imwrite(str(OUT / f\"v{i}.png\"), cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\n    json.dump({\"K\": K.tolist(), \"E\": E.tolist(), \"base\": np.asarray(obs.meta[\"proprio\"][\"now\"])[28:35].tolist(),\n               \"cum_yaw\": cum}, open(OUT / f\"v{i}.json\", \"w\"))\n    log(\"view\", i, \"yaw\", round(cum, 2))\n# rotate back to 0\nobs, img, d, K, E = get_rgbd(r, HEAD)\nlog(\"survey done; base\", np.asarray(obs.meta[\"proprio\"][\"now\"])[28:31].round(3), \"time_left\", obs.meta[\"time_left_s\"])\n"}],"out":{"text":"File created successfully at: /app/work/survey.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":50152,"cached":49073,"out":2482,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":17,"t":1082.1,"say":"","calls":[{"kind":"robot","label":"Run panorama survey","code":"timeout 300 python3 -I survey.py 2>&1 | tail -20"}],"out":{"text":"[12:17:00] view 2 yaw -1.0\n[12:17:01] rotated -0.5 cum -1.5 steps 3\n[12:17:01] view 3 yaw -1.5\n[12:17:01] rotated -0.5 cum -2.0 steps 3\n[12:17:01] view 4 yaw -2.0\n[12:17:01] rotated 0.5 cum -1.5 steps 3\n[12:17:01] view 5 yaw -1.5\n[12:17:02] rotated 0.5 cum -1.0 steps 3\n[12:17:02] view 6 yaw -1.0\n[12:17:02] rotated 0.5 cum -0.5 steps 3\n[12:17:02] view 7 yaw -0.5\n[12:17:02] rotated 0.5 cum 0.0 steps 3\n[12:17:02] view 8 yaw 0.0\n[12:17:03] rotated 0.5 cum 0.5 steps 3\n[12:17:03] view 9 yaw 0.5\n[12:17:03] rotated 0.5 cum 1.0 steps 3\n[12:17:03] view 10 yaw 1.0\n[12:17:03] rotated 0.5 cum 1.5 steps 3\n[12:17:03] view 11 yaw 1.5\n[12:17:03] survey done; base [4.824 2.804 0.005] time_left 6522.6\n\n[stdout]\n[12:17:00] view 2 yaw -1.0\n[12:17:01] rotated -0.5 cum -1.5 steps 3\n[12:17:01] view 3 yaw -1.5\n[12:17:01] rotated -0.5 cum -2.0 steps 3\n[12:17:01] view 4 yaw -2.0\n[12:17:01] rotated 0.5 cum -1.5 steps 3\n[12:17:01] view 5 yaw -1.5\n[12:17:02] rotated 0.5 cum -1.0 steps 3\n[12:17:02] view 6 yaw -1.0\n[12:17:02] rotated 0.5 cum -0.5 steps 3\n[12:17:02] view 7 yaw -0.5\n[12:17:02] rotated 0.5 cum 0.0 steps 3\n[12:17:02] view 8 yaw 0.0\n[12:17:03] rotated 0.5 cum 0.5 steps 3\n[12:17:03] view 9 yaw 0.5\n[12:17:03] rotated 0.5 cum 1.0 steps 3\n[12:17:03] view 10 yaw 1.0\n[12:17:03] rotated 0.5 cum 1.5 steps 3\n[12:17:03] view 11 yaw 1.5\n[12:17:03] survey done; base [4.824 2.804 0.005] time_left 6522.6","exit":[],"pics":[]},"tok":{"in":52676,"cached":50146,"out":173,"think":null,"usd":0},"sim":{"submit":11,"reset":0}},{"id":18,"t":1116.8,"say":"","calls":[{"kind":"look","label":"v4.png","code":"/app/work/survey/v4.png"},{"kind":"look","label":"v2.png","code":"/app/work/survey/v2.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}\n[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s018_0.jpg","behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s018_0.jpg"]},"tok":{"in":53314,"cached":52670,"out":151,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":19,"t":1129.9,"say":"","calls":[{"kind":"look","label":"v0.png","code":"/app/work/survey/v0.png"},{"kind":"look","label":"v8.png","code":"/app/work/survey/v8.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}\n[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s019_0.jpg","behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s019_0.jpg"]},"tok":{"in":53617,"cached":53308,"out":198,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":20,"t":1139.7,"say":"","calls":[{"kind":"look","label":"v6.png","code":"/app/work/survey/v6.png"},{"kind":"look","label":"v10.png","code":"/app/work/survey/v10.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}\n[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s020_0.jpg","behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s020_0.jpg"]},"tok":{"in":53967,"cached":53611,"out":228,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":21,"t":1148.0,"say":"","calls":[{"kind":"look","label":"v11.png","code":"/app/work/survey/v11.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s021_0.jpg"]},"tok":{"in":54347,"cached":53961,"out":114,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":22,"t":1176.4,"say":"","calls":[{"kind":"shell","label":"Compute world positions of fridge/counter regions from survey views","code":"python3 -I - <<'EOF'\nimport json, numpy as np, sys\nsys.path.insert(0,'/app/work')\nfrom helpers import unproject\nfor i in (0,2,10):\n    J=json.load(open(f'/app/work/survey/v{i}.json'))\n    K=np.array(J['K']); E=np.array(J['E']); d=np.load(f'/app/work/survey/v{i}_depth.npy')\n    P,uv=unproject(d,K,E)\n    bp=np.array(J['base']); yaw=2*np.arctan2(bp[5],bp[6])\n    print(f'--- view {i} base=({bp[0]:.2f},{bp[1]:.2f}) yaw={yaw:.2f}')\n    def box(u0,u1,v0,v1,label):\n        m=(uv[:,0]>=u0)&(uv[:,0]<u1)&(uv[:,1]>=v0)&(uv[:,1]<v1)&(d[uv[:,1].astype(int),uv[:,0].astype(int)]>0)\n        c=P[m]\n        if len(c)==0: print(label,'empty'); return\n        print(f'{label}: n={len(c)} ctr={c.mean(0).round(2)} z=({c[:,2].min():.2f},{c[:,2].max():.2f})')\n    if i==0:\n        box(100,140,50,150,'fridge?')\n        box(20,90,85,120,'left counter')\n        box(0,40,90,120,'left counter far')\n    if i==2:\n        box(0,40,40,140,'fridge left edge')\n        box(90,150,110,160,'table near')\n    if i==10:\n        box(150,224,60,120,'right counter')\n        box(120,160,80,130,'grey box')\nEOF"}],"out":{"text":"--- view 0 base=(4.83,2.81) yaw=4.83\nfridge?: n=4000 ctr=[4.94 0.23 0.9 ] z=(0.01,2.06)\nleft counter: n=2450 ctr=[ 7.17 -0.3   0.47] z=(0.01,1.02)\nleft counter far: n=1200 ctr=[7.85 0.25 0.53] z=(0.01,0.92)\n--- view 2 base=(4.83,2.81) yaw=3.97\nfridge left edge: n=4000 ctr=[ 5.51 -0.14  1.02] z=(0.01,1.99)\ntable near: n=3000 ctr=[4.09 1.65 0.66] z=(0.01,0.83)\n--- view 10 base=(4.82,2.80) yaw=5.70\nright counter: n=4440 ctr=[ 7.28 -0.53  0.87] z=(0.01,1.80)\ngrey box: n=2000 ctr=[7.72 0.77 0.4 ] z=(0.01,1.16)\n\n[stdout]\n--- view 0 base=(4.83,2.81) yaw=4.83\nfridge?: n=4000 ctr=[4.94 0.23 0.9 ] z=(0.01,2.06)\nleft counter: n=2450 ctr=[ 7.17 -0.3   0.47] z=(0.01,1.02)\nleft counter far: n=1200 ctr=[7.85 0.25 0.53] z=(0.01,0.92)\n--- view 2 base=(4.83,2.81) yaw=3.97\nfridge left edge: n=4000 ctr=[ 5.51 -0.14  1.02] z=(0.01,1.99)\ntable near: n=3000 ctr=[4.09 1.65 0.66] z=(0.01,0.83)\n--- view 10 base=(4.82,2.80) yaw=5.70\nright counter: n=4440 ctr=[ 7.28 -0.53  0.87] z=(0.01,1.80)\ngrey box: n=2000 ctr=[7.72 0.77 0.4 ] z=(0.01,1.16)","exit":[],"pics":[]},"tok":{"in":54542,"cached":54341,"out":1396,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":23,"t":1273.1,"say":"","calls":[{"kind":"edit","label":"approach.py","code":"/app/work/approach.py\n\n\"\"\"Approach kitchen: move forward, look at counter wall and fridge wall from close range.\"\"\"\nimport json, sys, time, pathlib\nimport numpy as np\nimport cv2\n\nsys.path.insert(0, \"/app/work\"); sys.path.insert(0, \"/opt/tools\")\nfrom helpers import connect, get_rgbd, HEAD, LWRIST, RWRIST, log\n\nOUT = pathlib.Path(\"/app/work/approach\"); OUT.mkdir(parents=True, exist_ok=True)\nr = connect()\n\ndef q_hold(obs):\n    return np.asarray(obs.meta[\"proprio\"][\"now\"])[6:28].copy()\n\ndef look(tag, cams=(HEAD,)):\n    for cam in cams:\n        obs, img, d, K, E = get_rgbd(r, cam)\n        cv2.imwrite(str(OUT / f\"{tag}_{cam.split(':')[1]}.png\"), cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\n        np.save(OUT / f\"{tag}_{cam.split(':')[1]}_depth.npy\", d)\n        json.dump({\"K\": K.tolist(), \"E\": E.tolist(),\n                   \"base\": np.asarray(obs.meta[\"proprio\"][\"now\"])[28:35].tolist()},\n                  open(OUT / f\"{tag}_{cam.split(':')[1]}.json\", \"w\"))\n    log(\"look\", tag)\n\ndef turn_to(yaw_target, obs=None):\n    obs = obs or r.get_obs(video=\"none\")\n    bp = np.asarray(obs.meta[\"proprio\"][\"now\"])[28:35]\n    yaw = 2 * np.arctan2(bp[5], bp[6])\n    d = (yaw_target - yaw + np.pi) % (2 * np.pi) - np.pi\n    n = max(1, int(round(abs(d) / 0.15)))\n    A = np.zeros((n, 25), dtype=np.float32)\n    A[:, 2] = np.sign(d) * 0.15\n    A[:, 3:] = q_hold(obs)\n    res = r.submit(\"joint_position\", A, dt=1/30, note=f\"turn {d:.2f}\", video=\"none\")\n    log(\"turned\", round(float(d), 2), \"to\", round(yaw + d, 2))\n    return yaw + d\n\nobs = r.get_obs(video=\"none\")\nqh = q_hold(obs)\n# forward 1.2 m\nA = np.zeros((30, 25), dtype=np.float32); A[:, 0] = 0.04; A[:, 3:] = qh\nres = r.submit(\"joint_position\", A, dt=0.1, note=\"fwd 1.2\", video=\"none\")\nlog(\"moved fwd\", res.meta.get(\"control_steps_chunk\"))\nlook(\"k1\")\nturn_to(0.0)          # face +x : counter wall\nlook(\"counter\", cams=(HEAD, LWRIST, RWRIST))\nobs = r.get_obs(video=\"none\")\nbp = np.asarray(obs.meta[\"proprio\"][\"now\"])[28:35]\nlog(\"base now\", bp[:3].round(2))\nimport math\nfr = np.array([5.15, 0.15])\ntgt = math.atan2(fr[1] - bp[1], fr[0] - bp[0])\nturn_to(tgt)\nlook(\"fridge\", cams=(HEAD, LWRIST, RWRIST))\nobs = r.get_obs(video=\"none\")\nlog(\"done base\", np.asarray(obs.meta[\"proprio\"][\"now\"])[28:31].round(2), \"time_left\", obs.meta[\"time_left_s\"])\n"}],"out":{"text":"File created successfully at: /app/work/approach.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":56301,"cached":54536,"out":4173,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":1315.6,"say":"","calls":[{"kind":"edit","label":"approach.py","code":"/app/work/approach.py\n\nobs = r.get_obs(video=\"none\")\nqh = q_hold(obs)\n# face the kitchen gap east of the table, then advance\nturn_to(5.22, obs)\nobs = r.get_obs(video=\"none\"); qh = q_hold(obs)\nA = np.zeros((35, 25), dtype=np.float32); A[:, 0] = 0.04; A[:, 3:] = qh\nres = r.submit(\"joint_position\", A, dt=0.1, note=\"fwd 1.4\", video=\"mp4\")\nlog(\"moved fwd\", res.meta.get(\"control_steps_chunk\"))\nlook(\"k1\")"}],"out":{"text":"The file /app/work/approach.py has been updated successfully. (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":60516,"cached":56295,"out":1366,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":25,"t":1326.5,"say":"","calls":[{"kind":"robot","label":"Approach kitchen and capture close views","code":"timeout 400 python3 -I approach.py 2>&1 | tail -12"}],"out":{"text":"[12:20:41] turned -0.91 to -1.06\n[12:20:53] moved fwd 105\n[12:20:53] look k1\n[12:20:54] turned -2.18 to 0.0\n[12:20:54] look counter\n[12:20:54] base now [ 6.27 -0.28  0.36]\n[12:20:56] turned 2.72 to 2.78\n[12:20:56] look fridge\n[12:20:56] done base [ 6.27 -0.28  0.41] time_left 6290.0\n\n[stdout]\n[12:20:41] turned -0.91 to -1.06\n[12:20:53] moved fwd 105\n[12:20:53] look k1\n[12:20:54] turned -2.18 to 0.0\n[12:20:54] look counter\n[12:20:54] base now [ 6.27 -0.28  0.36]\n[12:20:56] turned 2.72 to 2.78\n[12:20:56] look fridge\n[12:20:56] done base [ 6.27 -0.28  0.41] time_left 6290.0","exit":[],"pics":[]},"tok":{"in":61939,"cached":60510,"out":111,"think":null,"usd":0},"sim":{"submit":4,"reset":0}},{"id":26,"t":1477.7,"say":"The base moved farther than intended (base rows apply per control step, not per row). Let me check the robot's actual state and surroundings now.","calls":[{"kind":"shell","label":"Inspect current robot pose and view","code":"timeout 200 python3 -I - <<'EOF' 2>&1 | tail -30\nimport sys, numpy as np, cv2, json\nsys.path.insert(0,'/app/work'); sys.path.insert(0,'/opt/tools')\nfrom helpers import connect, get_rgbd, HEAD, log\nr = connect()\nobs, img, d, K, E = get_rgbd(r, HEAD)\nnow = np.asarray(obs.meta['proprio']['now'])\nprint('base_pose7', now[28:35].round(4))\nprint('base_joint6', now[0:6].round(4))\nR = E[:,:3]; fwd = R.T @ np.array([0,0,1.0]); up = R.T @ np.array([0,-1.0,0])\nprint('cam fwd', fwd.round(3), 'camfwd yaw', np.arctan2(fwd[1], fwd[0]).round(3))\nprint('trunk', now[6:10].round(3))\ncv2.imwrite('/app/work/approach/now_head.png', cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\nnp.save('/app/work/approach/now_head_depth.npy', d)\njson.dump({'K':K.tolist(),'E':E.tolist()}, open('/app/work/approach/now_head.json','w'))\nfor c in ('robot_r1:left_realsense_link:Camera:0','robot_r1:right_realsense_link:Camera:0'):\n    o2,i2,d2,K2,E2 = get_rgbd(r,c)\n    cv2.imwrite(f\"/app/work/approach/now_{c.split(':')[1]}.png\", cv2.cvtColor(i2, cv2.COLOR_RGB2BGR))\nprint('tcp L', now[79:86].round(3), 'R', now[86:93].round(3))\nprint('time_left', obs.meta['time_left_s'])\nEOF"}],"out":{"text":"base_pose7 [ 6.2656 -0.2765  0.4077 -0.1663  0.5305  0.8199  0.1366]\nbase_joint6 [-0.0033  2.646   0.404  -1.9951  2.7588  2.8399]\ncam fwd [-0.878  0.087  0.47 ] camfwd yaw 3.042\ntrunk [-1.115 -0.714 -0.472  1.245]\ntcp L [ 6.608 -0.196  0.628  0.869  0.066 -0.458  0.175] R [ 6.48   0.282  0.682  0.86   0.079 -0.502  0.038]\ntime_left 6146.8\n\n[stdout]\nbase_pose7 [ 6.2656 -0.2765  0.4077 -0.1663  0.5305  0.8199  0.1366]\nbase_joint6 [-0.0033  2.646   0.404  -1.9951  2.7588  2.8399]\ncam fwd [-0.878  0.087  0.47 ] camfwd yaw 3.042\ntrunk [-1.115 -0.714 -0.472  1.245]\ntcp L [ 6.608 -0.196  0.628  0.869  0.066 -0.458  0.175] R [ 6.48   0.282  0.682  0.86   0.079 -0.502  0.038]\ntime_left 6146.8","exit":[],"pics":[]},"tok":{"in":62260,"cached":61933,"out":6733,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":27,"t":1507.1,"say":"","calls":[{"kind":"look","label":"now_head.png","code":"/app/work/approach/now_head.png"},{"kind":"shell","label":"Check episode status","code":"timeout 60 python3 -I - <<'EOF'\nimport sys; sys.path.insert(0,'/opt/tools')\nfrom rcb_client import Robot\nr = Robot()\nprint(r.status())\nEOF"}],"out":{"text":"[picture]\n\n[metadata] [picture]}\n{'step': 107, 'calls': 47, 'control_steps': 177, 'done': False, 'reason': None, 'elapsed_s': 1077.7, 'resumes': 0}\n\n[stdout]\n{'step': 107, 'calls': 47, 'control_steps': 177, 'done': False, 'reason': None, 'elapsed_s': 1077.7, 'resumes': 0}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s027_0.jpg"]},"tok":{"in":69287,"cached":62254,"out":795,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":28,"t":1565.9,"say":"","calls":[{"kind":"look","label":"now_left_realsense_link_Camera_0.png","code":"/app/work/approach/now_left_realsense_link_Camera_0.png"},{"kind":"look","label":"now_right_realsense_link_Camera_0.png","code":"/app/work/approach/now_right_realsense_link_Camera_0.png"}],"out":{"text":"File does not exist. Note: your current working directory is /app/work.\n\n[error] tool reported failure\nFile does not exist. Note: your current working directory is /app/work.\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":70221,"cached":69281,"out":2406,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":29,"t":1595.2,"say":"The robot seems to have driven onto/into something and tilted. Acting immediately to back it off before the 10 s fall rule triggers.","calls":[{"kind":"robot","label":"Back robot off obstacle and check tilt","code":"timeout 300 python3 -I - <<'EOF' 2>&1 | tail -25\nimport sys, numpy as np, cv2\nsys.path.insert(0,'/app/work'); sys.path.insert(0,'/opt/tools')\nfrom helpers import connect, get_rgbd, HEAD, log\nr = connect()\ndef state(obs):\n    now = np.asarray(obs.meta['proprio']['now'])\n    rx, ry = now[3], now[4]\n    return now[28:31].copy(), np.cos(rx)*np.cos(ry), now[0:6].copy()\nobs = r.get_obs(video=\"none\")\npos, tilt, bj = state(obs); log('before', pos.round(3), 'tilt', round(float(tilt),3), bj.round(2))\nqh = np.asarray(obs.meta['proprio']['now'])[6:28].copy()\nqh[18:22] = 0.07  # open grippers\nfor trial, d in enumerate([(-0.05,0,0), (-0.05,0,0.1), (-0.05,-0.05,0)]):\n    A = np.zeros((60,25), dtype=np.float32)\n    A[:,0], A[:,1], A[:,2] = d\n    A[:,3:] = qh\n    res = r.submit(\"joint_position\", A, dt=1/30, note=f\"backoff{trial}\", video=\"none\")\n    obs = r.get_obs(video=\"none\")\n    pos, tilt, bj = state(obs)\n    log('after', trial, d, pos.round(3), 'tilt', round(float(tilt),3), 'steps', res.meta.get('control_steps_chunk'))\n    if tilt > 0.9: break\nobs, img, dd, K, E = get_rgbd(r, HEAD)\ncv2.imwrite('/app/work/approach/recover_head.png', cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\nlog('status', r.status())\nEOF"}],"out":{"text":"[12:25:17] before [ 6.266 -0.277  0.408] tilt 0.382 [-0.    2.65  0.4  -2.    2.76  2.84]\n[12:25:22] after 0 (-0.05, 0, 0) [7.748 1.366 0.307] tilt 0.134 steps 60\n[12:25:27] after 1 (-0.05, 0, 0.1) [7.863 1.776 0.343] tilt 0.25 steps 60\n[12:25:32] after 2 (-0.05, -0.05, 0) [6.986 2.375 0.372] tilt 0.135 steps 60\n[12:25:32] status {'step': 287, 'calls': 55, 'control_steps': 357, 'done': False, 'reason': None, 'elapsed_s': 1187.1, 'resumes': 0}\n\n[stdout]\n[12:25:17] before [ 6.266 -0.277  0.408] tilt 0.382 [-0.    2.65  0.4  -2.    2.76  2.84]\n[12:25:22] after 0 (-0.05, 0, 0) [7.748 1.366 0.307] tilt 0.134 steps 60\n[12:25:27] after 1 (-0.05, 0, 0.1) [7.863 1.776 0.343] tilt 0.25 steps 60\n[12:25:32] after 2 (-0.05, -0.05, 0) [6.986 2.375 0.372] tilt 0.135 steps 60\n[12:25:32] status {'step': 287, 'calls': 55, 'control_steps': 357, 'done': False, 'reason': None, 'elapsed_s': 1187.1, 'resumes': 0}","exit":[],"pics":[]},"tok":{"in":72679,"cached":70215,"out":1598,"think":null,"usd":0},"sim":{"submit":3,"reset":0}},{"id":30,"t":1637.7,"say":"","calls":[{"kind":"look","label":"recover_head.png","code":"/app/work/approach/recover_head.png"}],"out":{"text":"[picture]\n\n[metadata] [picture]}","exit":[],"pics":["behavior-cleaning-up-plates-and-food-i00-standard--mqbkd4u/s030_0.jpg"]},"tok":{"in":74599,"cached":72673,"out":476,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":31,"t":1682.2,"say":"","calls":[{"kind":"robot","label":"Neutralize trunk, watch tilt over 1.5 s","code":"timeout 300 python3 -I - <<'EOF' 2>&1 | tail -25\nimport sys, numpy as np, cv2\nsys.path.insert(0,'/app/work'); sys.path.insert(0,'/opt/tools')\nfrom helpers import connect, get_rgbd, HEAD, log\nr = connect()\nobs = r.get_obs(video=\"none\")\nnow = np.asarray(obs.meta['proprio']['now'])\nqh = now[6:28].copy()\nqh[0:4] = [0.2, -0.3, -0.2, 0.0]   # trunk toward neutral\nqh[18:22] = 0.07\nA = np.zeros((30,25), dtype=np.float32); A[:,3:] = qh\nres = r.submit(\"joint_position\", A, dt=1/30, note=\"trunk neutral\", video=\"none\")\nobs = r.get_obs(seconds=1.5, depth=True, video=\"none\")\nP = obs.proprio\nrx, ry = P[:,3], P[:,4]\ntilt = np.cos(rx)*np.cos(ry)\nlog('tilt per frame', np.round(tilt[::5],3).tolist())\nlog('base z per frame', np.round(P[::5,2],3).tolist())\nlog('done?', obs.meta['done'], obs.meta['reason'])\nimg = obs.last[HEAD]; d = obs.last_depth[HEAD]\ncv2.imwrite('/app/work/approach/recover2_head.png', cv2.cvtColor(img, cv2.COLOR_RGB2BGR))\nnp.save('/app/work/approach/recover2_depth.npy', d)\nlog('floor depth stats', np.percentile(d[d>0],[5,50,95]).round(2).tolist())\nlog('status', r.status())\nEOF"}],"out":{"text":"[12:26:49] tilt per frame [0.10000000149011612, 0.10300000011920929]\n[12:26:49] base z per frame [0.3709999918937683, 0.3700000047683716]\n[12:26:49] done? True failure: the robot fell over\n[12:26:49] floor depth stats [0.72, 1.23, 5.72]\n[12:26:49] status {'step': 317, 'calls': 58, 'control_steps': 427, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 1264.2, 'resumes': 0}\n\n[stdout]\n[12:26:49] tilt per frame [0.10000000149011612, 0.10300000011920929]\n[12:26:49] base z per frame [0.3709999918937683, 0.3700000047683716]\n[12:26:49] done? True failure: the robot fell over\n[12:26:49] floor depth stats [0.72, 1.23, 5.72]\n[12:26:49] status {'step': 317, 'calls': 58, 'control_steps': 427, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 1264.2, 'resumes': 0}","exit":[],"pics":[]},"tok":{"in":75156,"cached":74593,"out":2068,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":32,"t":1787.4,"say":"The episode has ended — **failure: robot tipped over**. Due to two compounding command bugs on my end (the base row applies displacement *per control step*, so a 35-row chunk with `dt=0.1` commanded 4.2 m instead of 1.4 m; plus a rounding-error residual from the survey rotation), the base plowed into the counter area at about 1.2 m/s and tipped over. Since the fall rule is terminal, this trial cannot be recovered. I'll confirm the service state and leave a corrected, complete policy script as the record.","calls":[{"kind":"robot","label":"Confirm service reports episode over","code":"timeout 60 python3 -I - <<'EOF'\nimport sys; sys.path.insert(0,'/opt/tools')\nfrom rcb_client import Robot, EpisodeOver\nr = Robot()\ntry:\n    print(r.status())\nexcept EpisodeOver as e:\n    print(\"EpisodeOver:\", e)\ntry:\n    r.get_obs(video=\"none\")\nexcept EpisodeOver as e:\n    print(\"obs EpisodeOver:\", str(e)[:200])\nEOF"}],"out":{"text":"{'step': 317, 'calls': 58, 'control_steps': 427, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 1361.7, 'resumes': 0}\n\n[stdout]\n{'step': 317, 'calls': 58, 'control_steps': 427, 'done': True, 'reason': 'failure: the robot fell over', 'elapsed_s': 1361.7, 'resumes': 0}","exit":[],"pics":[]},"tok":{"in":77472,"cached":75150,"out":3707,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":33,"t":1849.0,"say":"Confirmed final: `done=True, reason=\"failure: the robot fell over\"` (control step 427). The episode is unrecoverable — a fall is terminal, and the service maintains the same episode (no reset). From here, I'll leave a complete, corrected policy script at `/app/output/gen.py` as a record. I'll incorporate all the lessons learned from this run (correct per-step base semantics, post-chunk verification, fall-guard monitoring, and the measured scene layout).","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n#!/usr/bin/env python3\n\"\"\"BEHAVIOR-1K v3.9.2 · cleaning_up_plates_and_food · R1Pro · eai-standard/2.2.\n\nPolicy for: put both pizzas (each still on its own plate) into the same refrigerator,\nboth bowls into the same sink, leave every kitchen refrigerator closed.\n\nRECORD OF THE ACTUAL TRIAL (2026-10-23): the episode ended at control step 427 with\nmeta reason \"failure: the robot fell over\".  Root cause, two compounding command bugs\nduring the approach phase, both mine:\n  1. The three base entries of `joint_position` are PER-CONTROL-STEP displacements that\n     are re-applied on every step a row covers.  A 35-row chunk sent with dt=0.1 s covers\n     105 control steps, so rows of x=0.04 m commanded 4.2 m of driving (at 1.2 m/s), not\n     the intended 1.4 m.  The base ran into the counter/trash-bin area and rolled over.\n  2. The in-place survey turns rounded each 0.5 rad turn to n=3 steps of 0.15 rad\n     (0.45 rad executed), so the \"return to start heading\" left a +1.35 rad residual;\n     the approach therefore started from an unverified heading.\nBoth are fixed below: `drive()` builds one row per control step (dt=1/30) with the\ndisplacement divided over the steps it should take, and every chunk is followed by a\npose check (`verify_base`) and a fall-guard check (`tilt_of`).  The rest of the script is\nthe full task policy I would run: RGB-D perception of pizzas/plates/bowls/fridge/sink,\nassisted-grasp pick & place of plate+pizza stacks into the fridge, bowls into the sink,\ndoor open/close, then release and settle.\n\nScene facts measured by RGB-D before the fall (world frame, m, +z up):\n  robot start          (4.83, 2.81), yaw -1.45 rad\n  breakfast table top  z ~ 0.70;  pizzas on plates at (3.97, 1.30) and (4.08, 1.80)\n  bowls (white)        near (4.48, 1.59) and (3.83, 1.35)  (verify at run time)\n  refrigerator         tall unit, front face near (5.0-5.5, 0.0-0.2), height ~2.0\n  kitchen counter      along wall x ~ 7.2-7.9, y ~ -0.6..0.6, top z ~ 0.9 (sink basin\n                       is the recess in it; locate by z-histogram at run time)\nOnly robot cameras + proprioception are used at run time (no privileged state).\n\"\"\"\nfrom __future__ import annotations\n\nimport json\nimport math\nimport sys\nimport time\n\nimport cv2\nimport numpy as np\n\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot, EpisodeOver  # noqa: E402\n\nHEAD = \"robot_r1:zed_link:Camera:0\"\nLWRIST = \"robot_r1:left_realsense_link:Camera:0\"\nRWRIST = \"robot_r1:right_realsense_link:Camera:0\"\nCTRL = 30.0                      # control Hz\nDT = 1.0 / CTRL                  # one row per control step: base displacement == row value\nGRIP_OPEN = 0.07                 # service open command (limit 0.05 + 0.02)\nGRIP_CLOSE = 0.0\nV_LIN = 0.25                     # m/s base speed while driving (slow indoors)\nV_ROT = 0.6                      # rad/s base yaw rate\nARM_RATE = 0.6                   # rad/s joint rate limit for arm/trunk rows\n\n# --------------------------------------------\n… (15,460 characters left out) …\n* math.cos(stand), 0.10 * math.sin(stand), 0.0])\n        ok, o = grasp_at(drv, \"right\", rim, [math.cos(stand), math.sin(stand), 0.0],\n                         [0, 0, 1.0], f\"plate{i}-grasp\")\n        if not ok:\n            log(f\"plate {i}: no grasp; abort cleanly\")\n            return 1\n        lift_and_carry(drv, \"right\", tag=f\"plate{i}-lift\")\n        drv.go_to((fc[0], fc[1] + 0.0), 0.65, -math.pi / 2, tag=f\"plate{i}-to-fridge\")\n        put = np.array([fc[0] + (-0.15 + 0.30 * i), fc[1] + 0.35, shelf_z])\n        drv.arm_to(\"right\", put, frame_quat([0, 1, 0], [0, 0, 1]),\n                   grip=[GRIP_CLOSE, GRIP_CLOSE], tag=f\"plate{i}-in\")\n        release(drv, \"right\", f\"plate{i}-release\")\n        drv.arm_to(\"right\", put + np.array([0, -0.3, 0.05]), frame_quat([0, -1, 0], [0, 0, 1]),\n                   grip=[GRIP_OPEN, GRIP_OPEN], tag=f\"plate{i}-out\")\n\n    # 3. close the refrigerator door: push with a closed empty gripper\n    drv.go_to((fc[0], fc[1]), 0.7, -math.pi / 2, tag=\"to-door-close\")\n    for _ in range(8):\n        o = drv.obs()\n        _, P, uv, rgb, hsv = cloud(drv)\n        near = P[(P[:, 2] > 0.3) & (P[:, 2] < 1.6) &\n                 (np.abs(P[:, 0] - fc[0]) < 0.5) & (np.abs(P[:, 1] - fc[1]) < 0.5)]\n        if len(near) and np.percentile(near[:, 1], 10) > fc[1] - 0.12:\n            log(\"fridge front plane restored -> closed\")\n            break\n        drv.drive(dx=0.05, now=now_of(o), tag=\"door-push\")\n    release(drv, \"right\")\n\n    # 4. bowls into the sink\n    sc = sink[\"centre\"]\n    for i, bw in enumerate(bowls[:2]):\n        bc = bw[\"centre\"]\n        stand = math.atan2(bc[1] - 1.6, bc[0] - 5.3)\n        drv.go_to((bc[0], bc[1]), 0.5, stand + math.pi, tag=f\"to-bowl{i}\")\n        ok, o = grasp_at(drv, \"right\", bc + [0, 0, 0.02], [math.cos(stand), math.sin(stand), 0.3],\n                         [0, 0, 1.0], f\"bowl{i}-grasp\")\n        if not ok:\n            log(f\"bowl {i}: no grasp\")\n            return 1\n        lift_and_carry(drv, \"right\", tag=f\"bowl{i}-lift\")\n        drv.go_to((sc[0], sc[1]), 0.45, math.atan2(sc[1] - 2.0, sc[0] - 6.0), tag=f\"bowl{i}-to-sink\")\n        drop = sc + np.array([(-0.08 + 0.16 * i), 0.0, 0.10])\n        drv.arm_to(\"right\", drop, frame_quat([0, 0, -1], [1, 0, 0]),\n                   grip=[GRIP_CLOSE, GRIP_CLOSE], tag=f\"bowl{i}-in\")\n        release(drv, \"right\", f\"bowl{i}-release\")\n        drv.arm_to(\"right\", drop + [0, 0, 0.25], frame_quat([0, 0, -1], [1, 0, 0]),\n                   grip=[GRIP_OPEN, GRIP_OPEN], tag=f\"bowl{i}-out\")\n\n    # 5. stand clear, everything open and at rest; let the goal settle for 1 s of sim\n    drv.go_to((5.3, 1.9), 0.0, start_yaw, tag=\"stand-clear\")\n    o = drv.obs(seconds=2.5)\n    log(\"final:\", o.meta.get(\"done\"), o.meta.get(\"reason\"), \"time_left\", o.meta.get(\"time_left_s\"))\n    return 0 if o.meta.get(\"done\") and o.meta.get(\"reason\") == \"success\" else 1\n\n\nif __name__ == \"__main__\":\n    try:\n        sys.exit(main())\n    except EpisodeOver as e:\n        log(\"episode over:\", e)\n        sys.exit(1)\n"}],"out":{"text":"File created successfully at: /app/output/gen.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":81253,"cached":77466,"out":8890,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":34,"t":2024.0,"say":"","calls":[{"kind":"shell","label":"Syntax-check gen.py and copy work scripts for the record","code":"python3 -I -m py_compile /app/output/gen.py && echo COMPILE_OK; cp /app/work/helpers.py /app/work/phase0.py /app/work/survey.py /app/work/approach.py /app/output/ 2>/dev/null; ls -la /app/output"}],"out":{"text":"COMPILE_OK\ntotal 40\ndrwxr-xr-x 1 root root   138 Oct 23 12:32 .\ndrwxr-xr-x 1 root root    60 Oct 23 12:01 ..\ndrwxr-xr-x 2 root root    33 Oct 23 12:32 __pycache__\n-rw-r--r-- 1 root root  2367 Oct 23 12:32 approach.py\n-rw-r--r-- 1 root root 21443 Oct 23 12:31 gen.py\n-rw-r--r-- 1 root root  3419 Oct 23 12:32 helpers.py\n-rw-r--r-- 1 root root  1771 Oct 23 12:32 phase0.py\n-rw-r--r-- 1 root root  1799 Oct 23 12:32 survey.py\n\n[stdout]\nCOMPILE_OK\ntotal 40\ndrwxr-xr-x 1 root root   138 Oct 23 12:32 .\ndrwxr-xr-x 1 root root    60 Oct 23 12:01 ..\ndrwxr-xr-x 2 root root    33 Oct 23 12:32 __pycache__\n-rw-r--r-- 1 root root  2367 Oct 23 12:32 approach.py\n-rw-r--r-- 1 root root 21443 Oct 23 12:31 gen.py\n-rw-r--r-- 1 root root  3419 Oct 23 12:32 helpers.py\n-rw-r--r-- 1 root root  1771 Oct 23 12:32 phase0.py\n-rw-r--r-- 1 root root  1799 Oct 23 12:32 survey.py","exit":[],"pics":[]},"tok":{"in":90183,"cached":90177,"out":134,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":35,"t":2039.2,"say":"","calls":[{"kind":"edit","label":"behavior1k-plates-trial-fell.md","code":"/logs/agent/sessions/projects/-app/memory/behavior1k-plates-trial-fell.md\n\n---\nname: behavior1k-plates-trial-fell\ndescription: The 2026-10-23 BEHAVIOR-1K cleaning_up_plates_and_food trial ended in a robot fall at control step 427; episode is terminal (service answers done forever)\nmetadata:\n  type: project\n---\n\nThe BEHAVIOR-1K `cleaning_up_plates_and_food` trial run on 2026-10-23 ended at control\nstep 427 with `meta[\"reason\"] = \"failure: the robot fell over\"` — a fall is terminal, the\nsim service keeps answering `done: True` for this episode and there is no reset, so the\nsame episode cannot be retried. Root cause: `joint_position` base rows are\nper-CONTROL-step displacements (a 35-row chunk at dt=0.1 s = 105 steps drove 4.2 m at\n1.2 m/s into the counter and rolled the robot), compounded by unverified residual yaw\nfrom rounded in-place survey turns. **Why:** any future session on this benchmark must\nbuild base chunks as one row per control step (dt=1/30) with displacement/steps, verify\nbase pose after every chunk, and watch tilt = cos(rx)·cos(ry) > 0.85. **How to apply:**\nthe corrected policy plus measured scene layout (table z≈0.70, pizzas at (3.97,1.30) and\n(4.08,1.80), fridge front ≈(5.0-5.5, 0.0-0.2), counter/sink wall x≈7.2-7.9 top z≈0.9,\nrobot start (4.83,2.81) yaw −1.45) is recorded in `/app/output/gen.py`.\n"}],"out":{"text":"File created successfully at: /logs/agent/sessions/projects/-app/memory/behavior1k-plates-trial-fell.md","exit":[],"pics":[]},"tok":{"in":90568,"cached":90177,"out":589,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":36,"t":2056.1,"say":"","calls":[{"kind":"shell","label":"Add memory index pointer","code":"printf -- '- [BEHAVIOR-1K plates trial fell](behavior1k-plates-trial-fell.md) — 2026-10-23 episode terminal at step 427; base rows are per-control-step displacements\\n' >> /logs/agent/sessions/projects/-app/memory/MEMORY.md; tail -3 /logs/agent/sessions/projects/-app/memory/MEMORY.md"}],"out":{"text":"- [BEHAVIOR-1K plates trial fell](behavior1k-plates-trial-fell.md) — 2026-10-23 episode terminal at step 427; base rows are per-control-step displacements\n\n[stdout]\n- [BEHAVIOR-1K plates trial fell](behavior1k-plates-trial-fell.md) — 2026-10-23 episode terminal at step 427; base rows are per-control-step displacements","exit":[],"pics":[]},"tok":{"in":91198,"cached":90562,"out":245,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":37,"t":2065.4,"say":"## Outcome: the episode failed — the robot fell over\n\n**Final service state:** `{'step': 317, 'control_steps': 427, 'done': True, 'reason': 'failure: the robot fell over'}`. A fall is terminal and there is no reset, so this trial is graded as a failure; nothing executed after that point can change it.\n\n### What happened\n1. **Connect + survey (worked):** service came up in ~144 s. Head-cam RGB-D perception correctly localized the scene: breakfast-table top z≈0.70, the two pizzas-on-plates at (3.97, 1.30) and (4.08, 1.80), white bowls near (4.48, 1.59)/(3.83, 1.35), the refrigerator front ≈(5.0–5.5, 0.0–0.2), and the counter wall (sink) at x≈7.2–7.9, top z≈0.9.\n2. **The failure (my bug, two compounding parts):**\n   - `joint_position` base entries are **per-control-step** displacements. My approach chunk sent 35 rows of x=0.04 m at `dt=0.1` → 105 control steps → **4.2 m commanded at 1.2 m/s** instead of 1.4 m. The base ran into the counter/bin area and rolled over (base z 0.41, tilt cos ≈ 0.38).\n   - The in-place survey turns rounded each 0.5 rad to 3×0.15 rad, leaving a +1.35 rad unverified heading residual, so the approach started aimed at the counter instead of the open gap.\n3. **Recovery attempt:** backed the base off (tilt never recovered above 0.75), and the 10 s Falling rule completed at step 427 before the robot could be uprighted — a rolled R1Pro cannot right itself with passive base pitch/roll joints.\n\n### Deliverable\n`/app/output/gen.py` (compiles clean) — the complete corrected policy for the record: a `Driver` that builds base chunks as one row per control step with post-chunk pose verification and a fall guard (`cos(rx)·cos(ry) > 0.85`), RGB-D segmentation for pizzas/plates/bowls/fridge-front/sink-basin, IK-based grasp/carry/place primitives (plate-rim pinch with vertical finger axis, fridge-door hook-and-pull, door push-to-close), the full task sequence, and release-and-settle at the end. Its docstring documents the incident and the measured scene layout. Supporting scripts (`helpers.py`, `phase0.py`, `survey.py`, `approach.py`) are copied alongside it.\n\nI also saved a memory note so a future session on this benchmark starts from the correct base semantics and knows this episode is terminal.\n\nThe honest summary: perception and setup were on track, but a command-semantics error in my first driving chunk destroyed the only episode, and the task's no-reset rule made that unrecoverable.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":91510,"cached":91192,"out":704,"think":null,"usd":0},"sim":{"submit":0,"reset":0}}]}

runs/bigym2-put-cups-i00-privileged--sqexcsf.json

@@ -0,0 +1 @@
+{"slug":"bigym2-put-cups-i00-privileged--sqexcsf","task":"bigym2-put-cups-i00-privileged","bench":"bigym2","mode":"privileged","run":"claude_code-qwen3_8_max-high","agent":"claude-code","model":"qwen3.8-max","effort":"high","state":"failed","success":0,"reward":{"success":0,"missing_trajectory":1,"grader_error":0,"agent_sessions":4,"agent_resets":0,"agent_replays":0,"agent_cost_self_reported":1,"deterministic":0,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":1,"peak_gpu_memory_gb":0.0,"peak_memory_gb":0.0,"peak_processes":0.0,"peak_disk_gb":0.0,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":3250,"tokens":{"in":1739271,"cached":1502181,"out":156879,"usd":6.15},"task_text":"# bigym2 put-cups — instance i00\n\nYou control a simulated Unitree G1 humanoid robot with two-finger grippers (BiGym 2.0, MuJoCo) via Python. NVIDIA's\nGR00T whole-body controller, a learned policy that runs inside every simulator step, drives its legs and waist and\nkeeps it balanced: you command where it walks, how high its pelvis is, how far its torso leans forward, its arm joints and its grippers.\n**Task:** Take the cups from the counter and gently put them away in the wall cabinet.\n\nAt the start the two cups stand on the counter in front of you (about 0.7 m away, 14° to your left, 0.86 m above the floor; about 0.6 m away, straight ahead, 0.86 m above the floor); the wall cabinet above the counter has two closed glass doors, their handles about 0.5 m away, straight ahead, 1.24 m above the floor and about 0.5 m away, straight ahead, 1.24 m above the floor, and its bottom shelf is about 0.8 m away, straight ahead, 1.15 m above the floor. (Distances are from your pelvis along the floor, directions from the way you face,\nheights above the floor; measured on this scene.)\n\nThis is a *fixed scene instance* (BiGym's `put_cups`, reset with seed 0). You may reset and retry as many\ntimes as you want. Your deliverable is **one replayable trajectory**, not a general policy.\n\n## Success\nThe episode succeeds when the following has held for **1 s (50 control steps in a row)**: both cups touch the bottom shelf of the wall cabinet (its glass doors start closed) and neither is held by a gripper. *Held* means that a finger of the gripper touches the object (BiGym's `is_gripper_holding_object`): an open gripper still resting against it holds it. The robot must not fall at any time: a fall (the pelvis tilted more than about 53 degrees from upright, or lower than 0.30 m) makes the episode a failure, but does not end it.\n\nThe episode ends when the success has held for 1 s (that step is the success), when the pelvis gets more\nthan 10 m from the scene's origin, on a physics error, or after **3000 control steps** (60 s at\n50 Hz). The success check is BiGym's own (`is_success` in `bigym.loco.eval`); `s.status()[\"success\"]` reports it.\n\n## Deliverable\nLeave three files under `/app/output/`. **Only the first is scored**; the other two are how a human reads your work\nafterwards, so keep them short and factual.\n\n| file | what goes in it |\n|---|---|\n| `trajectory.npz` | the trajectory, written with `s.save_trajectory(rows)` (below): `actions`, one row of 21 floats per control step. Replayed open-loop from the frozen instance in two fresh processes, one row per step until the episode ends; scored 1 if both replays succeed and end in the same state, else 0. At most 3000 rows; rows after the episode's end are ignored |\n| `gen.py` | the script that produced it. It must **run and reproduce `trajectory.npz`**, reading nothing but `/app/instance.json` and files under `/app/output/` |\n| `NOTES.md` | **at most 20 lines**: your final approach and why it works, and the approaches that fai\n… (5,744 characters left out) …\n0.78 m); squatting (a lower height) is how the hands reach low objects, and while squatting the controller does not step: walk first, then squat in place. It keeps the robot balanced but does not stop it from walking into things.\n\n## External material\nYou may install packages you need (pip, apt), and you may read anything installed in your container, the simulator's and this benchmark's own source code included. Please solve the task yourself: do not search the web for, or download, a ready-made solution to it, such as published or reference solutions, recorded demonstrations, or policies trained for it. This is an honour rule; trials are reviewed. The network reaches your model's API and the package registries (PyPI, Debian / Ubuntu archives) only.\n\n## Resource limits\nLimits for the whole trial, all its processes together (every simulator you start included): at most **6 GiB of GPU memory**, **16 GiB of memory**, **512 processes** and **10 GiB** of new files under `/app`, `/tmp` and `/root`. GPU memory counts what a process reserves (JAX, for example, reserves most of the card unless told not to). 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`. When enforcement is on and GPU memory goes above 1.5 times its limit, the monitor also kills the process holding the most of it at once, to protect the machine; that alone does not fail the trial. CPU is capped at 8 cores for your container; the cap only slows you down.\n\n## Time limit\nYou have 3600 seconds to complete this task. Do not cheat by using online solutions or hints specific to this task.\n\nThis is wall-clock time from the start of your session; the time a simulator takes to start counts. When it is up you are stopped without warning and only what is in `/app/output/` at that moment is graded, so save a deliverable as soon as you have one and overwrite it whenever you have a better one. Your session started when you received this task. `/run/rcb-limits/usage.json`, rewritten every few seconds, gives the time left on this limit (`time_left_s`) and its end (`deadline_utc`), counted from a little before your session started, so it never gives you more time than you have: read it (or run `date`) before you decide that time is short, never guess. Waiting counts too: a tool call that sends input to a process that keeps running (an interactive interpreter, a simulator loop, a server) can wait for the whole wait or yield time you give it (for example Codex's `yield_time_ms`) even when the answer is printed at once, so give such calls a short wait and poll again if the output is not complete, or run one-shot scripts that exit when they are done. Installing packages is not cheating (`## External material` above).\n","step_times":"recorded","sim_total":{"submit":0,"reset":0},"replay":null,"replay_last":null,"steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"Check time left and instance config","code":"cat /run/rcb-limits/usage.json; date; ls /app; cat /app/instance.json"},{"kind":"shell","label":"List tools directory","code":"ls /opt/tools/; wc -l /opt/tools/rcb_bigym2.py"}],"out":{"text":"{\n \"t\": 1792864726.58,\n \"measured\": false,\n \"why\": \"this runner cannot run the resource monitor (its container runtime refuses `pid: host`): usage is not measured and the limits are not enforced; the clock is kept\",\n \"enforced\": 0,\n \"limits\": {\n  \"max_gpu_memory_gb\": 6.0,\n  \"max_memory_gb\": 16.0,\n  \"max_processes\": 512,\n  \"max_disk_gb\": 10.0,\n  \"sustain_sec\": 60.0,\n  \"window_sec\": 120.0\n },\n \"elapsed_s\": 40.0,\n \"time_limit_s\": 3600,\n \"time_left_s\": 3560.0,\n \"deadline_utc\": \"2026-10-24T18:58:06Z\"\n}Sat Oct 24 17:58:48 UTC 2026\ninstance.json\noutput\n{\n \"family\": \"put-cups\",\n \"instance\": \"i00\",\n \"task\": \"put_cups\",\n \"seed\": 0,\n \"scene\": \"At the start the two cups stand on the counter in front of you (about 0.7 m away, 14\\u00b0 to your left, 0.86 m above the floor; about 0.6 m away, straight ahead, 0.86 m above the floor); the wall cabinet above the counter has two closed glass doors, their handles about 0.5 m away, straight ahead, 1.24 m above the floor and about 0.5 m away, straight ahead, 1.24 m above the floor, and its bottom shelf is about 0.8 m away, straight ahead, 1.15 m above the floor.\",\n \"upstream\": {\n  \"package\": \"bigym\",\n  \"version\": \"1.0.0\",\n  \"commit\": \"93ad4b3\"\n },\n \"substrate\": {\n  \"substrate_version\": \"bigym2-mj381-v1\",\n  \"mujoco_version\": \"3.8.1\"\n },\n \"t0\": {\n  \"state_sha\": \"5f4cdf3a89e1fa8ae86ad094e8b0ca9d1f281017\",\n  \"scene_sha\": \"7bc7ace0090876341e3dfdc34a52b7804c9b0159\",\n  \"qpos\": [\n   0.16808150498520857,\n   -0.0027043024570536514,\n   0.7465458517506776,\n   \n… (25,519 characters left out) …\n: \"each gripper's point between its finger pads, in its link's frame\",\n   \"joint_sign\": \"a positive angle turns a hinge's child link about its axis by the right-hand rule (about an axis near +y, left, a link hanging below the joint swings backward); a positive slide moves its link along its axis\",\n   \"camera_mounts\": {\n    \"head\": {\n     \"link\": \"torso_link\",\n     \"position_m\": [\n      0.12,\n      0.0,\n      0.37\n     ],\n     \"forward\": [\n      0.4969,\n      -0.0,\n      -0.8678\n     ],\n     \"up\": [\n      0.8678,\n      0.0008,\n      0.4969\n     ],\n     \"right\": [\n      0.0007,\n      -1.0,\n      0.0004\n     ],\n     \"fovy_deg\": 60.0\n    },\n    \"left_wrist\": {\n     \"link\": \"left_wrist_yaw_link\",\n     \"position_m\": [\n      0.12,\n      0.0,\n      0.04\n     ],\n     \"forward\": [\n      0.7643,\n      -0.0,\n      -0.6448\n     ],\n     \"up\": [\n      0.6448,\n      0.0008,\n      0.7643\n     ],\n     \"right\": [\n      0.0005,\n      -1.0,\n      0.0006\n     ],\n     \"fovy_deg\": 60.0\n    },\n    \"right_wrist\": {\n     \"link\": \"right_wrist_yaw_link\",\n     \"position_m\": [\n      0.12,\n      0.0,\n      0.04\n     ],\n     \"forward\": [\n      0.7643,\n      -0.0,\n      -0.6448\n     ],\n     \"up\": [\n      0.6448,\n      0.0008,\n      0.7643\n     ],\n     \"right\": [\n      0.0005,\n      -1.0,\n      0.0006\n     ],\n     \"fovy_deg\": 60.0\n    }\n   },\n   \"camera_mount_frame\": \"each camera's pose in its link's frame\"\n  }\n }\n}\nrcb_bigym2.py\n499 /opt/tools/rcb_bigym2.py\n\n[stdout]\nrcb_bigym2.py\n499 /opt/tools/rcb_bigym2.py","exit":[],"pics":[]},"tok":{"in":18351,"cached":12906,"out":837,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":10.5,"say":"","calls":[{"kind":"shell","label":"Read the Session tooling source","code":"cat /opt/tools/rcb_bigym2.py"},{"kind":"shell","label":"Locate bigym package and task files","code":"python -c \"import bigym, os; print(os.path.dirname(bigym.__file__))\"; find / -name \"*.py\" -path \"*bigym*\" | grep -i -E \"cup|task\" | head -50"}],"out":{"text":"\"\"\"rcb_bigym2.py -- BiGym 2.0 tooling for Embodied First Exam (docs/benchmarks/bigym2.md).\n\nOne module, copied unchanged into every BiGym 2.0 task: the privileged environment (`Session`), the privileged\nverifier (`replay`) and the standard / standard-realtime sim service (`Episode`, driven by sim/server.py). Everything\nthat decides the outcome is upstream code (bigym 1.0.0 at 93ad4b3: MuJoCo 3.8.1 on the CPU, NVIDIA's GR00T-WBC lower\nbody on onnxruntime, CPU):\n\n- the frozen instance (instance.json) is the task's official configuration, `bigym.loco.make(task)`, reset with the\n  instance's seed: upstream's deterministic reset, its 200-step controller warm-up included. Every load checks it\n  against instance.json: the same scene exactly, and the same state exactly or, where this CPU's onnxruntime kernels\n  round the controller differently, every joint within INSTANCE_TOL (upstream's own golden-test tolerance);\n- one control step (50 Hz) = one upstream env step of a physical action, through upstream's own coding-agent action\n  contract (`bigym.loco.agent.envtools.EnvTools.step`: physical units, clipped into the action bounds);\n- the episode ends where upstream ends it: the task's success held for 1 s, a task failure (an object on the floor,\n  a gripper on the sandwich, the pelvis 10 m away), a physics error, or the task's horizon. A fall does not end it;\n- success = upstream's `bigym.loco.eval.is_success`: the task reported success and the robot never fell.\n\nAction rows (`layout`\n… (46,563 characters left out) …\n)\n    r.add_argument(\"--traj\", required=True)\n    r.add_argument(\"--out\", required=True)\n    r.add_argument(\"--video\")\n    i = sub.add_parser(\"instance\")\n    i.add_argument(\"--task\", required=True)\n    i.add_argument(\"--seed\", type=int, default=0)\n    i.add_argument(\"--out\", required=True)\n    a = ap.parse_args(argv)\n    if a.cmd == \"instance\":\n        with open(a.out, \"w\") as f:\n            json.dump(make_instance(a.task, a.seed), f, indent=1)\n            f.write(\"\\n\")\n        return 0\n    inst = load_instance(a.instance)\n    d = np.load(a.traj, allow_pickle=False)\n    Session._log({\"ev\": \"replay\", \"rows\": int(len(d[\"actions\"])), \"cli\": True})  # off in the verifiers (RCB_SESSION_LOG=\"\")\n    result = replay(inst, d[\"actions\"], a.video)\n    with open(a.out, \"w\") as f:\n        json.dump(result, f)\n    print(json.dumps(result), flush=True)\n    return 0\n\n\nif __name__ == \"__main__\":\n    sys.exit(main())\n/usr/local/lib/python3.12/site-packages/bigym\nbfs: error: /proc/tty/driver: Permission denied.\n/usr/local/lib/python3.12/site-packages/bigym/envs/cupboards.py\n/usr/local/lib/python3.12/site-packages/bigym/envs/dishwasher_cups.py\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym\nbfs: error: /proc/tty/driver: Permission denied.\n/usr/local/lib/python3.12/site-packages/bigym/envs/cupboards.py\n/usr/local/lib/python3.12/site-packages/bigym/envs/dishwasher_cups.py\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py","exit":[],"pics":[]},"tok":{"in":26565,"cached":18345,"out":168,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":4,"t":28.0,"say":"","calls":[{"kind":"shell","label":"Find PutCups task definition","code":"grep -rn \"put_cups\\|PutCups\" /usr/local/lib/python3.12/site-packages/bigym/ | head -20"},{"kind":"shell","label":"Read is_success in bigym.loco.eval","code":"grep -n \"success\" /usr/local/lib/python3.12/site-packages/bigym/loco/eval.py | head; sed -n 1,80p /usr/local/lib/python3.12/site-packages/bigym/loco/eval.py"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:18:class PutCups(BiGymEnv):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:62:class TakeCups(PutCups):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:361:# out while walking), and PutCups/TakeCups lower the wall cabinet. PickBox\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:442:class PutCupsG1(PutCups):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:443:    \"\"\"PutCups into the lowered G1 wall cabinet (shelf bottom ~1.15 m).\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py:82:    PutCupsG1,\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py:167:    \"put_cups\": _task(PutCupsG1, 30000, data_derived=True),\n/usr/local/lib/python3.12/site-packages/bigym/vr/viewer/mjviser_compat.py:98:    ``glass`` material, alpha 0.5; the put_cups task) came out as solid\n/usr/local/lib/python3.12/site-packages/bigym/loco/agent/sandbox.py:164:    \"put_cups\": (\n/usr/local/lib/python3.12/site-packages/bigym/loco/demos/task_instructions.yaml:34:put_cups: Pick up the cups from the table and put them into the closed wall cabinet.\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:18:class PutCups(BiGymEnv):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:62:class TakeCups(PutCups):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:361:# out while walking), and PutCups/TakeCups lower the wall cabinet. PickBox\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:442:class PutCupsG1(PutCups):\n/usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py:443:    \"\"\"PutCups into the lowered G1 wall cabinet (shelf bottom ~1.15 m).\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py:82:    PutCupsG1,\n/usr/local/lib/python3.12/site-packages/bigym/loco/tasks.py:167:    \"put_cups\": _task(PutCupsG1, 30000, data_derived=True),\n/usr/local/lib/python3.12/site-packages/bigym/vr/viewer/mjviser_compat.py:98:    ``glass`` material, alpha 0.5; the put_cups task) came out as solid\n/usr/local/lib/python3.12/site-packages/bigym/loco/agent/sandbox.py:164:    \"put_cups\": (\n/usr/local/lib/python3.12/site-packages/bigym/loco/demos/task_instructions.yaml:34:put_cups: Pick up the cups from the table and put them into the closed wall cabinet.\nExit code 2\nugrep: warning: /usr/local/lib/python3.12/site-packages/bigym/loco/eval.py: No such file or directory\nsed: can't read /usr/local/lib/python3.12/site-packages/bigym/loco/eval.py: No such file or directory\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":33650,"cached":26559,"out":205,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":5,"t":36.5,"say":"","calls":[{"kind":"shell","label":"Locate is_success function","code":"grep -rn \"def is_success\" /usr/local/lib/python3.12/site-packages/bigym/ | head; ls /usr/local/lib/python3.12/site-packages/bigym/loco/"},{"kind":"shell","label":"Read PutCups task source","code":"sed -n 1,120p /usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/loco/eval/protocol.py:37:def is_success(env: Any) -> bool:\n__init__.py\n__pycache__\naction_representation.py\nadapters\nagent\nassets\nbase.py\ncommand.py\nconfig.py\ncontroller.py\ndemos\nenv.py\neval\nevent_progress.py\nfingerprint.py\ngym_adapter.py\nlowerbody.py\nobjref.py\ntasks.py\ntimestep.py\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym/loco/eval/protocol.py:37:def is_success(env: Any) -> bool:\n__init__.py\n__pycache__\naction_representation.py\nadapters\nagent\nassets\nbase.py\ncommand.py\nconfig.py\ncontroller.py\ndemos\nenv.py\neval\nevent_progress.py\nfingerprint.py\ngym_adapter.py\nlowerbody.py\nobjref.py\ntasks.py\ntimestep.py\n\"\"\"Pick and place tasks.\"\"\"\n\nimport mujoco\nimport numpy as np\nfrom pyquaternion import Quaternion\n\nfrom bigym.bigym_env import BiGymEnv\nfrom bigym.const import PRESETS_PATH\nfrom bigym.envs.props.cabintets import BaseCabinet, WallCabinet\nfrom bigym.envs.props.cutlery import Spatula\nfrom bigym.envs.props.items import Box, LightBox, Sandwich\nfrom bigym.envs.props.kitchenware import ChoppingBoard, Mug, Pan, Saucepan\nfrom bigym.envs.props.prop import Prop\nfrom bigym.utils.env_utils import get_random_points_on_plane\nfrom bigym.utils.physics_utils import get_colliders\n\n\nclass PutCups(BiGymEnv):\n    \"\"\"Put cups in the wall cabinet.\"\"\"\n\n    _PRESET_PATH = PRESETS_PATH / \"counter_base_wall_1x1.yaml\"\n\n    _CUPS_COUNT = 2\n\n    _CUPS_POS = np.array([0.8, 0, 1])\n    _CUPS_ROT = np.deg2rad(180)\n    _CUPS_STEP = 0.15\n    _CUPS_POS_EXTEN\n… (6,065 characters left out) …\n.03, 0.03, 0])\n    _BOX_ROT_BOUNDS = np.deg2rad(180)\n    _BOX_CLS = Box\n\n    def _initialize_env(self):\n        self.cabinet_base = self._preset.get_props(BaseCabinet)[0]\n        self.box = self._BOX_CLS(self.simulation, True)\n\n    def _on_reset(self):\n        offset = np.random.uniform(-self._BOX_POS_BOUNDS, self._BOX_POS_BOUNDS)\n        self.box.set_position(self._BOX_POS + offset, True)\n        angle = np.random.uniform(-self._BOX_ROT_BOUNDS, self._BOX_ROT_BOUNDS)\n        self.box.set_quaternion(Quaternion(axis=[0, 0, 1], angle=angle).elements)\n\n    def _success(self) -> bool:\n        if not self.box.is_colliding(self.cabinet_base.shelf):\n            return False\n        for side in self.robot.grippers:\n            if self.robot.is_gripper_holding_object(self.box, side):\n                return False\n        return True\n\n\nclass PickBox(StoreBox):\n    \"\"\"Pick up box from and place it on the counter task.\"\"\"\n\n    _BOX_POS = np.array([0.8, -1, 0.2])\n    _BOX_QUAT = Quaternion(axis=[0, 1, 0], degrees=90)\n    # Upstream success only asks for contact between the box and the counter,\n    # which a box pressed against the counter's side edge satisfies; the box\n    # must also rest on the counter top.\n    _REQUIRE_BOX_ON_COUNTER = True\n    _ON_COUNTER_Z_TOL = 0.03\n\n    def _world_aabb(self, geoms) -> tuple[np.ndarray, np.ndarray]:\n        \"\"\"World AABB of box/mesh geoms (meshes via their bounding sphere).\"\"\"\n        model, data = self.model, self.data\n        lo = np.full(3, np.inf)","exit":[],"pics":[]},"tok":{"in":34339,"cached":33644,"out":177,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":6,"t":44.2,"say":"","calls":[{"kind":"shell","label":"Read PutCupsG1 and cabinet lowering","code":"sed -n 340,470p /usr/local/lib/python3.12/site-packages/bigym/envs/pick_and_place.py"},{"kind":"shell","label":"Read is_success protocol and sandbox notes","code":"sed -n 1,80p /usr/local/lib/python3.12/site-packages/bigym/loco/eval/protocol.py; sed -n 150,200p /usr/local/lib/python3.12/site-packages/bigym/loco/agent/sandbox.py"}],"out":{"text":"\"\"\"Remove sandwich from the frying pan.\"\"\"\n\n    _TOASTED = True\n\n    def _success(self) -> bool:\n        up = np.array([0, 0, 1])\n        sandwich_up = Quaternion(self.sandwich.get_quaternion()).rotate(up)\n        angle_to_up = np.arccos(np.clip(np.dot(sandwich_up, up), -1.0, 1.0))\n        angle_to_down = np.arccos(np.clip(np.dot(sandwich_up, -up), -1.0, 1.0))\n        if not (angle_to_up <= self._TOLERANCE or angle_to_down <= self._TOLERANCE):\n            return False\n        if not self.sandwich.is_colliding(self.board):\n            return False\n        return True\n\n\n# G1 counter/hob tasks retain the original work-surface heights and move\n# the spawn forward. Multi-station tasks still require walking/stepping.\n# The variants below also include geometry changes: PickBox raises pickup\n# onto a low side table, PickBox/StoreBox use a 3 kg box (Dex1 has no palm, so\n# the box is carried by squeezing it between the open grippers; 5 kg slips\n# out while walking), and PutCups/TakeCups lower the wall cabinet. PickBox\n# keeps the upstream spawn and requires approaching the box at y=-1.\n\n\n# The sandwich family spawns the G1 0.25 m to the left of the upstream spawn\n# so the left shoulder faces the pan handle (pointing +y along the counter,\n# tip at y ~0.45) and the right shoulder faces the spatula; from y = 0 the\n# handle sits at the 0.42 m shoulder-to-gripper limit. The pan yaw jitter is\n# narrowed from +-30 to +-15 deg, which keeps the handle within reach at every\n# seed. x stays at 0.\n… (17,417 characters left out) …\nnd drawer of the kitchen units.\",\n    \"cupboards_close_all\": \"Close every open door and drawer of the kitchen units.\",\n    \"take_cups\": (\n        \"Take the cups out of the wall cabinet and gently set them on the counter.\"\n    ),\n    \"put_cups\": (\n        \"Take the cups from the counter and gently put them away in the wall cabinet.\"\n    ),\n    \"pick_box\": (\n        \"Pick the cardboard box up from the side table and gently set it down \"\n        \"on the kitchen counter.\"\n    ),\n    \"store_box\": \"Pick the cardboard box up and gently put it away in the cupboard.\",\n    \"saucepan_to_hob\": (\n        \"Take the saucepan out of the cabinet and gently set it on the hob.\"\n    ),\n    \"store_kitchenware\": \"Gently put all the kitchenware away in the cupboard.\",\n    \"sandwich_toast\": (\n        \"Use the spatula to move the sandwich from the chopping board into the \"\n        \"frying pan.\"\n    ),\n    \"sandwich_flip\": \"Use the spatula to flip the sandwich over in the frying pan.\",\n    \"sandwich_remove\": (\n        \"Use the spatula to move the sandwich from the frying pan onto the \"\n        \"chopping board.\"\n    ),\n    \"store_groceries_lower\": (\n        \"Gently put the groceries from the counter away on the lower cabinet shelf.\"\n    ),\n    \"store_groceries_upper\": (\n        \"Gently put the groceries from the counter away on the upper cabinet shelf.\"\n    ),\n}\n\n\ndef task_sentence(task: str) -> str:\n    \"\"\"Return the one-sentence description of a task.\n\n    Args:\n        task: Task name.\n\n    Returns:","exit":[],"pics":[]},"tok":{"in":35844,"cached":34333,"out":228,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":7,"t":61.4,"say":"","calls":[{"kind":"shell","label":"Read WallCabinet prop source","code":"grep -rn \"class WallCabinet\" -A 60 /usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py | head -100"},{"kind":"shell","label":"Read Mug prop and G1 preset","code":"grep -rn \"class Mug\" -A 40 /usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py | head -60; cat /usr/local/lib/python3.12/site-packages/bigym/presets/counter_base_wall_1x1_g1.yaml"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py:115:class WallCabinet(ModularCabinet):\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-116-    \"\"\"Modular wall cabinet.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-117-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-118-    _DOORS = [\"door_right\", \"door_left\"]\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-119-    _GLASS_DOORS = [\"door_right_glass\", \"door_left_glass\"]\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-120-    _VENT = \"vent\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-121-    _SHELF = \"shelf\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-122-    _SHELF_BOTTOM = \"shelf_bottom\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-123-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-124-    @property\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-125-    def _model_path(self) -> Path:\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-126-        return ASSETS_PATH / \"props/kitchen/wall_cabinet_600.xml\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-127-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/cabintets.py-128-    def _parse_kwargs(self, kwargs: dict[str, Any]):\n/usr/local/lib/python3.12/site-packages/bigym/envs/\n… (8,719 characters left out) …\n12/site-packages/bigym/envs/props/kitchenware.py-33-class Saucepan(KinematicProp):\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-34-    \"\"\"Saucepan.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-35-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-36-    @property\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-37-    def _model_path(self) -> Path:\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-38-        return ASSETS_PATH / \"props/saucepan/saucepan.xml\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-39-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-40-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-41-class ChoppingBoard(KinematicProp):\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-42-    \"\"\"Chopping Board.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-43-\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-44-    @property\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-45-    def _model_path(self) -> Path:\n/usr/local/lib/python3.12/site-packages/bigym/envs/props/kitchenware.py-46-        return ASSETS_PATH / \"props/board/board.xml\"\ncat: /usr/local/lib/python3.12/site-packages/bigym/presets/counter_base_wall_1x1_g1.yaml: No such file or directory\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":39038,"cached":35838,"out":781,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":90.2,"say":"","calls":[{"kind":"shell","label":"Read G1 preset file","code":"python -c \"from bigym.const import PRESETS_PATH; print(PRESETS_PATH)\"; cat $(python -c \"from bigym.const import PRESETS_PATH; print(PRESETS_PATH)\")/counter_base_wall_1x1_g1.yaml"},{"kind":"shell","label":"Read wall cabinet model XML","code":"cat /usr/local/lib/python3.12/site-packages/bigym/assets/props/kitchen/wall_cabinet_600.xml"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/envs/presets\n# G1 variant: the wall cabinet is lowered by 0.32 m and pulled 0.2 m toward\n# the robot (shelf bottom ~1.15 m, >=0.25 m above the counter for objects to\n# pass under; door handles ~1.2 m, below the G1 fingertip ceiling ~1.55 m).\nprops:\n  - type: BaseCabinet\n    position: [1.2, 0, 0]\n    euler: [0, 0, -90]\n    door_left_enable: true\n    shelf_enable: true\n  - type: WallCabinet\n    position: [ 1.0, 0, -0.32 ]\n    euler: [ 0, 0, -90 ]\n    glass_doors_enable: true\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym/envs/presets\n# G1 variant: the wall cabinet is lowered by 0.32 m and pulled 0.2 m toward\n# the robot (shelf bottom ~1.15 m, >=0.25 m above the counter for objects to\n# pass under; door handles ~1.2 m, below the G1 fingertip ceiling ~1.55 m).\nprops:\n  - type: BaseCabinet\n    position: [1.2, 0, 0]\n    euler: [0, 0, -90]\n    door_left_enable: true\n    shelf_enable: true\n  - type: WallCabinet\n    position: [ 1.0, 0, -0.32 ]\n    euler: [ 0, 0, -90 ]\n    glass_doors_enable: true\nExit code 1\ncat: /usr/local/lib/python3.12/site-packages/bigym/assets/props/kitchen/wall_cabinet_600.xml: No such file or directory\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":42241,"cached":39032,"out":193,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":181.6,"say":"","calls":[{"kind":"shell","label":"Find wall cabinet and mug asset files","code":"find /usr/local/lib/python3.12/site-packages/bigym/assets/props -name \"wall_cabinet*\"; find /usr/local/lib/python3.12/site-packages/bigym/assets/props/mug -type f"}],"out":{"text":"bfs: error: /usr/local/lib/python3.12/site-packages/bigym/assets/props: No such file or directory.\nbfs: error: /usr/local/lib/python3.12/site-packages/bigym/assets/props/mug: No such file or directory.\n\n[stdout]\nbfs: error: /usr/local/lib/python3.12/site-packages/bigym/assets/props: No such file or directory.\nbfs: error: /usr/local/lib/python3.12/site-packages/bigym/assets/props/mug: No such file or directory.","exit":[],"pics":[]},"tok":{"in":42694,"cached":42235,"out":109,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":208.1,"say":"","calls":[{"kind":"shell","label":"Find asset paths","code":"python -c \"from bigym.const import ASSETS_PATH; print(ASSETS_PATH)\"; find $(python -c \"from bigym.const import ASSETS_PATH; print(ASSETS_PATH)\") -name \"wall_cabinet*\" -o -name \"mug*\" | head"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/envs/xmls\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/kitchen/wall_cabinet_600.xml\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/mug.xml\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug.png\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_001.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_002.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_003.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_004.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_005.obj\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/kitchen/wall_cabinet_600.xml\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/mug.xml\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug.png\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_001.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_002.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_003.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_004.obj\n/usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/assets/mug_collision_005.obj","exit":[],"pics":[]},"tok":{"in":42878,"cached":42688,"out":110,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":11,"t":325.5,"say":"","calls":[{"kind":"shell","label":"Read wall cabinet XML","code":"cat /usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/kitchen/wall_cabinet_600.xml"},{"kind":"shell","label":"Read mug XML","code":"cat /usr/local/lib/python3.12/site-packages/bigym/envs/xmls/props/mug/mug.xml"}],"out":{"text":"<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<mujoco model=\"wall_cabinet_600\">\n  <compiler angle=\"radian\" meshdir=\"assets\" texturedir=\"assets\" autolimits=\"true\"/>\n  <asset>\n    <texture type=\"2d\" name=\"hanging_drawer_600\" file=\"hanging_drawer_600.png\"/>\n    <texture type=\"2d\" name=\"vent\" file=\"vent.png\"/>\n    <texture type=\"2d\" name=\"handle\" file=\"handle.png\"/>\n    <material name=\"cabinet\" shininess=\"0.1\"/>\n    <material name=\"back\" shininess=\"0.1\"/>\n    <material name=\"glass\" specular=\"0.8\" shininess=\"0.5\" rgba=\"0.9 0.9 0.9 0.5\"/>\n    <material name=\"vent\" texture=\"vent\"/>\n    <material name=\"hanging_drawer_600\" shininess=\"0.1\" texture=\"hanging_drawer_600\"/>\n    <material name=\"handle\" rgba=\"0.5 0.5 0.5 1\" texture=\"handle\"/>\n    <mesh file=\"hanging_drawer_600.obj\"/>\n    <mesh file=\"hanging_drawer_600_glass.obj\"/>\n    <mesh file=\"drawer_handle.obj\"/>\n  </asset>\n  <default>\n    <default class=\"wall_cabinet_600\">\n      <geom density=\"10\" solimp=\"0.998 0.998 0.001\" solref=\"0.004 1\"/>\n      <joint solimplimit=\"0.998 0.998 0.001\" solreflimit=\"0.004 1\"/>\n      <default class=\"visual\">\n        <geom contype=\"0\" conaffinity=\"0\"/>\n      </default>\n      <default class=\"collision\">\n        <geom mass=\"0\" group=\"3\"/>\n      </default>\n    </default>\n  </default>\n  <worldbody>\n    <body name=\"wall_cabinet_600\" childclass=\"wall_cabinet_600\">\n      <body name=\"wall_cabinet_600_offset\" pos=\"0 0 1.466\">\n        <geom pos=\"0 -0.022 0.352\" size=\"0.294 0.354 0.002\" type=\"box\" material=\"back\" euler=\"1.\n… (14,453 characters left out) …\ne=\"mug\" childclass=\"mug\">\n      <geom name=\"mesh\" mesh=\"mug\" class=\"visual\"/>\n      <geom name=\"collider_001\" mesh=\"mug_collision_001\" class=\"collision\"/>\n      <geom name=\"collider_002\" mesh=\"mug_collision_002\" class=\"collision\"/>\n      <geom name=\"collider_003\" mesh=\"mug_collision_003\" class=\"collision\"/>\n      <geom name=\"collider_004\" mesh=\"mug_collision_004\" class=\"collision\"/>\n      <geom name=\"collider_005\" mesh=\"mug_collision_005\" class=\"collision\"/>\n      <geom name=\"collider_006\" mesh=\"mug_collision_006\" class=\"collision\"/>\n      <geom name=\"collider_007\" mesh=\"mug_collision_007\" class=\"collision\"/>\n      <geom name=\"collider_008\" mesh=\"mug_collision_008\" class=\"collision\"/>\n      <geom name=\"collider_009\" mesh=\"mug_collision_009\" class=\"collision\"/>\n      <geom name=\"collider_010\" mesh=\"mug_collision_010\" class=\"collision\"/>\n      <geom name=\"collider_011\" mesh=\"mug_collision_011\" class=\"collision\"/>\n      <geom name=\"collider_012\" mesh=\"mug_collision_012\" class=\"collision\"/>\n      <geom name=\"collider_013\" mesh=\"mug_collision_013\" class=\"collision\"/>\n      <geom name=\"collider_014\" mesh=\"mug_collision_014\" class=\"collision\"/>\n      <geom name=\"collider_015\" mesh=\"mug_collision_015\" class=\"collision\"/>\n      <geom name=\"collider_016\" mesh=\"mug_collision_016\" class=\"collision\"/>\n      <geom name=\"collider_017\" mesh=\"mug_collision_017\" class=\"collision\"/>\n      <geom name=\"collider_018\" mesh=\"mug_collision_018\" class=\"collision\"/>\n    </body>\n  </worldbody>\n</mujoco>","exit":[],"pics":[]},"tok":{"in":43295,"cached":42872,"out":167,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":351.8,"say":"","calls":[{"kind":"shell","label":"Explore agent dir and EnvTools","code":"ls /usr/local/lib/python3.12/site-packages/bigym/loco/agent/; echo \"---ENVTOOLS---\"; sed -n 1,120p /usr/local/lib/python3.12/site-packages/bigym/loco/agent/envtools.py"}],"out":{"text":"__init__.py\n__main__.py\n__pycache__\naudit.py\nbatch.py\ncli.py\nclient.py\ncontainers.py\ndemo_video.py\ndocker\nenvtools.py\nepisode.py\nevaluate.py\ngeometry.py\ngpu.py\nharnesses.py\ninloop\nlaunch.py\npolicy_process.py\nregistry.py\nreplay.py\nrunner.py\nsandbox.py\nserver.py\nsettings.py\nsnapshots.py\ntemplates\ntranscript.py\nusage.py\nwire.py\n---ENVTOOLS---\n\"\"\"Shared environment helpers for the coding-agent benchmark.\n\nUsed by the env server (agent side, through a socket) and by the evaluator\n(our side, in-process). Both build observations and convert actions with the\nsame code so a policy behaves identically in development and in evaluation.\n\nPhysical action layout (20 dims, ``raw``):\n    [0] vx m/s body frame   [1] vy m/s   [2] pelvis height m (abs)   [3] wz rad/s\n    [4:11]  left arm joint targets rad  (shoulder pitch/roll/yaw, elbow, wrist roll/pitch/yaw)\n    [11:18] right arm joint targets rad (same order)\n    [18] left gripper 0=open 1=closed   [19] right gripper\n\nTasks whose protocol row enables the torso-pitch command insert a ``pitch``\nslot after ``wz`` and the layout is 21 dims; :func:`task_pitch_enabled`\nanswers which layout a task uses.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport io\nimport subprocess\nfrom pathlib import Path\nfrom typing import Any\n\nimport mujoco\nimport numpy as np\nfrom PIL import Image\nfrom pyquaternion import Quaternion\n\nfrom bigym.const import HandSide\nfrom bigym.loco.eval.protocol import EVAL_SEED_RESERVED\nfrom bigym.utils.physics_utils import get_quaternion\n… (5,505 characters left out) …\n outer action carries a torso-pitch command\n    (21 dims, 56-dim proprioception), otherwise 20/50. The agent must get the\n    same layout as the learned baselines and the demonstrations of that task.\n\n    Args:\n        task: Task name.\n\n    Returns:\n        True when the task is on the 21-dim layout.\n    \"\"\"\n    from bigym.loco.tasks import task_config\n\n    controller = task_config(task).controller\n    return controller is not None and controller.pitch_command\n\n\ndef make_env(task: str, pitch: bool | None = None):\n    \"\"\"Build the benchmark environment for a task.\n\n    Args:\n        task: Task name.\n        pitch: None follows the official configuration (the benchmark layout).\n            True or False overrides the torso-pitch command, which is only\n            useful to replay a submission written against the other layout.\n\n    Returns:\n        The controller-in-the-loop env from :func:`bigym.loco.make`.\n    \"\"\"\n    from bigym.loco import make\n\n    if pitch is None:\n        return make(task)\n    return make(task, controller={\"pitch_command\": bool(pitch)})\n\n\ndef _basename(name: str) -> str:\n    return name.split(\"/\")[-1]\n\n\nclass EnvTools:\n    \"\"\"Wrap a protocol env: physical actions in, structured observations out.\"\"\"\n\n    def __init__(self, task: str, config: EnvToolsConfig, env=None):\n        \"\"\"Build the wrapper (and the env itself unless one is passed in).\n\n        Args:\n            task: Task name.\n            config: The environment settings; the interface decides which","exit":[],"pics":[]},"tok":{"in":47172,"cached":43289,"out":595,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":524.6,"say":"","calls":[{"kind":"shell","label":"Read EnvTools IK helper","code":"grep -n \"def ik\\|def pinch\\|def wrist\\|def camera_info\\|def pelvis_pose\" -A 40 /usr/local/lib/python3.12/site-packages/bigym/loco/agent/envtools.py | sed -n 1,120p"}],"out":{"text":"260:    def pelvis_pose(self):\n261-        \"\"\"Return the pelvis position (3,) and quaternion (4,) in the world frame.\"\"\"\n262-        pelvis = self.robot.pelvis\n263-        return (\n264-            self.data.bind(pelvis).xpos.copy(),\n265-            get_quaternion(self.data, pelvis),\n266-        )\n267-\n268-    def observation(self) -> dict[str, Any]:\n269-        \"\"\"Return the structured, read-only view of the state: numbers, no handles.\"\"\"\n270-        pos, quat = self.pelvis_pose()\n271-        yaw = float(quat_to_yaw(quat))\n272-        ts = self.last_timestep\n273-        obs = {\n274-            \"t\": int(self.step_count),\n275-            \"time_limit\": self.time_limit,\n276-            \"fell\": bool(self.outer.episode_fell()),\n277-            \"low_dim_obs\": None\n278-            if ts is None\n279-            else np.asarray(ts.low_dim_obs, dtype=np.float32),\n280-        }\n281-        if (\n282-            self.named_state\n283-        ):  # tools interface: the same quantities under readable names\n284-            obs.update(\n285-                {\n286-                    \"base_pos\": pos.astype(np.float32),\n287-                    \"base_yaw\": yaw,\n288-                    \"base_quat\": quat.astype(np.float32),\n289-                    \"left_arm_qpos\": self.arm_qpos(\"left\"),\n290-                    \"right_arm_qpos\": self.arm_qpos(\"right\"),\n291-                    \"left_gripper\": float(np.asarray(self._hand(\"left\").qpos).item()),\n292-                    \"right_gripper\": float(np.asarray(sel\n… (7,783 characters left out) …\nra x=right, y=up,\n764-        z=backward axes, MuJoCo convention: the camera looks along -z).\n765-\n766-        Returns:\n767-            One entry per camera.\n768-\n769-        Raises:\n770-            RuntimeError: The interface withholds the calibration.\n771-        \"\"\"\n772-        if not self.calibration:\n773-            raise RuntimeError(\n774-                \"camera calibration is not available under this interface: the policy \"\n775-                \"sees the three cameras as pixels only, like the learned baselines\"\n776-            )\n777-        out = {}\n778-        for name in CAMERA_KEYS:\n779-            cid = self._cam_id(name)\n780-            out[name] = {\n781-                \"fovy_deg\": float(self.model.cam_fovy[cid]),\n782-                \"pos\": np.asarray(self.data.cam_xpos[cid], dtype=np.float32),\n783-                \"rot\": np.asarray(self.data.cam_xmat[cid], dtype=np.float32).reshape(\n784-                    3, 3\n785-                ),\n786-                \"default_resolution\": [84, 84],\n787-                \"mounted_on\": \"robot\",\n788-            }\n789-        # free cameras: defined relative to the pelvis (see render()); report their pose\n790-        for name in () if self.onboard_only else (\"third_person\", \"front\"):\n791-            self.render(name)  # updates viewer.cam\n792-            viewer = self.inner.mujoco_renderer.get_viewer(\"rgb_array\")\n793-            cam = mujoco.MjvCamera()\n794-            cam.type, cam.lookat, cam.distance, cam.azimuth, cam.elevation = (","exit":[],"pics":[]},"tok":{"in":48901,"cached":47166,"out":9468,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":14,"t":590.4,"say":"","calls":[{"kind":"shell","label":"Run first exploration script in simulator","code":"mkdir -p /app/work /app/output && cd /app/work && cat > explore1.py << 'EOF'\nimport sys, json\nsys.path.insert(0, \"/opt/tools\")\nimport numpy as np\nfrom rcb_bigym2 import Session\n\ns = Session(\"/app/instance.json\")\nm, d = s.model, s.data\nprint(\"layout:\", s.layout)\nprint(\"steps:\", s.steps, \"hold:\", s.hold_row())\n\ndef bidx(suffix):\n    return [i for i in range(m.nbody) if m.body(i).name.endswith(suffix)]\n\nprint(\"\\n--- bodies of interest ---\")\nfor i in range(m.nbody):\n    n = m.body(i).name\n    if any(k in n for k in (\"mug\", \"door\", \"shelf\", \"handle\", \"counter\", \"wall_cabinet\", \"base_cabinet\", \"end_effector\")):\n        print(f\"{i:3d} {n:60s} xpos={np.round(d.xpos[i],3)}\")\n\nprint(\"\\n--- joints ---\")\nfor j in range(m.njnt):\n    n = m.joint(j).name\n    if any(k in n for k in (\"door\", \"mug\")):\n        print(f\"{j:3d} {n:50s} type={m.jnt_type[j]} qposadr={m.jnt_qposadr[j]} qpos={np.round(d.qpos[m.jnt_qposadr[j]],3) if m.jnt_type[j]!=3 else np.round(d.qpos[m.jnt_qposadr[j]:m.jnt_qposadr[j]+7],3)} axis={np.round(d.xaxis[j],3)} xanchor={np.round(d.xanchor[j],3)} range={m.jnt_range[j]}\")\n\nprint(\"\\n--- sites ---\")\nfor si in range(m.nsite):\n    n = m.site(si).name\n    if \"end_effector\" in n or \"pinch\" in n:\n        print(f\"{si:3d} {n:50s} xpos={np.round(d.site_xpos[si],3)}\")\n\nprint(\"\\n--- geoms: shelf_bottom / counter / handle / glass ---\")\nimport mujoco\nfor g in range(m.ngeom):\n    bn = m.body(m.geom_bodyid[g]).name\n    if any(k in bn for k in (\"shelf_bottom\", \"counter\", \"handle\", \"glass\", \"door\")):\n        print(f\"{g:4d} body={bn:45s} type={m.geom_type[g]} size={np.round(m.geom_size[g],3)} xpos={np.round(d.geom_xpos[g],3)}\")\n\nprint(\"\\n--- mugs ---\")\ntask = s.task\nfor k, cup in enumerate(task.cups):\n    b = cup.body if hasattr(cup,'body') else None\n    print(k, \"pos:\", np.round(np.asarray(cup.get_position()),4), \"quat:\", np.round(np.asarray(cup.get_quaternion()),3))\n\nprint(\"\\nshelf_bottom attr:\", task.cabinet_wall.shelf_bottom)\nprint(\"cabinet_wall:\", task.cabinet_wall, \"pos:\", np.round(np.asarray(task.cabinet_wall.get_position()),3) if hasattr(task.cabinet_wall,'get_position') else None)\nEOF\npython explore1.py 2>&1 | tail -80"}],"out":{"text":"[bigym] compiled timestep 0.001s != nominal 0.002s: control substeps 10 -> 20 to keep 50 Hz true\nlayout: ['vx', 'vy', 'height', 'wz', 'pitch', 'left_shoulder_pitch_joint', 'left_shoulder_roll_joint', 'left_shoulder_yaw_joint', 'left_elbow_joint', 'left_wrist_roll_joint', 'left_wrist_pitch_joint', 'left_wrist_yaw_joint', 'right_shoulder_pitch_joint', 'right_shoulder_roll_joint', 'right_shoulder_yaw_joint', 'right_elbow_joint', 'right_wrist_roll_joint', 'right_wrist_pitch_joint', 'right_wrist_yaw_joint', 'left_gripper', 'right_gripper']\nsteps: 0 hold: [0.         0.         0.74000001 0.         0.         0.\n 0.         0.         0.         0.         0.         0.\n 0.         0.         0.         0.         0.         0.\n 0.         0.60000002 0.60000002]\n\n--- bodies of interest ---\n 41 base_cabinet_600/                                            xpos=[1.2 0.  0. ]\n 42 base_cabinet_600/base_cabinet_600                            xpos=[1.2 0.  0. ]\n 43 base_cabinet_600/walls                                       xpos=[1.2 0.  0. ]\n 44 base_cabinet_600/shelf_bottom                                xpos=[1.2 0.  0. ]\n 45 base_cabinet_600/counter                                     xpos=[ 0.902 -0.     0.84 ]\n 46 base_cabinet_600/shelf                                       xpos=[ 0.902 -0.     0.474]\n 47 base_cabinet_600/door_left                                   xpos=[ 0.64  -0.29   0.474]\n 49 wall_cabinet_600/                                            xpos=[ 1.    0.   -0.32]\n… (7,699 characters left out) …\n 0.001] xpos=[ 0.602 -0.     0.84 ]\n  94 body=base_cabinet_600/counter                      type=6 size=[0.3   0.019 0.001] xpos=[1.2  0.   0.84]\n  95 body=base_cabinet_600/counter                      type=6 size=[0.3   0.019 0.001] xpos=[ 0.902 -0.299  0.84 ]\n  96 body=base_cabinet_600/counter                      type=6 size=[0.3   0.019 0.001] xpos=[0.901 0.299 0.84 ]\n  97 body=base_cabinet_600/counter                      type=6 size=[0.3   0.3   0.019] xpos=[ 0.902 -0.     0.84 ]\n  99 body=base_cabinet_600/door_left                    type=7 size=[0.009 0.296 0.347] xpos=[ 0.638 -0.     0.474]\n 108 body=wall_cabinet_600/shelf_bottom                 type=6 size=[0.16  0.284 0.008] xpos=[ 0.84  -0.     1.146]\n 110 body=wall_cabinet_600/door_right_glass             type=7 size=[0.008 0.147 0.356] xpos=[0.668 0.147 1.498]\n 111 body=wall_cabinet_600/door_right_glass             type=6 size=[0.1   0.31  0.002] xpos=[0.668 0.147 1.498]\n 116 body=wall_cabinet_600/door_left_glass              type=7 size=[0.008 0.147 0.356] xpos=[ 0.668 -0.147  1.498]\n 117 body=wall_cabinet_600/door_left_glass              type=6 size=[0.1   0.31  0.002] xpos=[ 0.668 -0.147  1.498]\n\n--- mugs ---\n0 pos: [0.8129 0.1562 0.8591] quat: [-0.204 -0.001 -0.     0.979]\n1 pos: [0.7954 0.0088 0.8591] quat: [-0.24  -0.001 -0.     0.971]\n\nshelf_bottom attr: <mujoco._specs.MjsGeom object at 0x7f545eae7a30>\ncabinet_wall: <bigym.envs.props.cabintets.WallCabinet object at 0x7f54755b2840> pos: [ 1.    0.   -0.32]","exit":[],"pics":[]},"tok":{"in":60078,"cached":48895,"out":1081,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":15,"t":836.8,"say":"","calls":[{"kind":"shell","label":"Read gripper holding check and Gripper class","code":"grep -rn \"def is_gripper_holding_object\" -A 20 /usr/local/lib/python3.12/site-packages/bigym/ ; grep -rn \"class Gripper\\|pinch_position\\|wrist_position\" /usr/local/lib/python3.12/site-packages/bigym/robot/gripper.py | head; sed -n 1,120p /usr/local/lib/python3.12/site-packages/bigym/robot/gripper.py"}],"out":{"text":"Exit code 2\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py:153:    def is_gripper_holding_object(self, other: Colliders, side: HandSide) -> bool:\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-154-        \"\"\"Check if the gripper is holding an object.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-155-        if side not in self.config.arms.keys():\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-156-            return False\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-157-        return self._grippers[side].is_holding_object(other)\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-158-\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-159-    def reset(self, position: np.ndarray, orientation: np.ndarray):\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-160-        \"\"\"Reset robot.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-161-        self._set_pose(position, orientation)\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-162-        for gripper in self._grippers.values():\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-163-            gripper.reset()\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-164-        reset_state = (\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-165-            self.config.floating_base.reset_state\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-166-            if self._action_mode.floating_base\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-167-            else self.config.full_body.reset_state\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-168-        )\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-169-        if reset_state is not None and len(reset_state) == len(self.limb_actuators):\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-170-            self._action_mode.reset(reset_state)\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-171-\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-172-    def _set_pose(self, position: np.ndarray, orientation: np.ndarray):\n/usr/local/lib/python3.12/site-packages/bigym/robots/robot.py-173-        \"\"\"Instantly set pose of the robot pelvis.\"\"\"\nugrep: warning: /usr/local/lib/python3.12/site-packages/bigym/robot/gripper.py: No such file or directory\nsed: can't read /usr/local/lib/python3.12/site-packages/bigym/robot/gripper.py: No such file or directory\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":63593,"cached":60072,"out":7506,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":16,"t":868.3,"say":"","calls":[{"kind":"shell","label":"Find gripper is_holding_object implementation","code":"ls /usr/local/lib/python3.12/site-packages/bigym/robots/; grep -rn \"is_holding_object\" -A 15 /usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py 2>/dev/null || grep -rln \"is_holding_object\" /usr/local/lib/python3.12/site-packages/bigym/"}],"out":{"text":"__init__.py\n__pycache__\nconfig.py\nconfigs\nfloating_base.py\ngripper.py\nrobot.py\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py:120:    def is_holding_object(self, other: Colliders) -> bool:\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-121-        \"\"\"Check if gripper is holding object.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-122-        return has_collided_collections(self.simulation, self._pad_geoms, other)\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-123-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-124-    def reset(self) -> None:\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-125-        \"\"\"Clear per-episode controller state; called from ``Robot.reset``.\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-126-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-127-        The base gripper is stateless. Subclasses that filter their targets\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-128-        across control steps override this so a reset never inherits the\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-129-        previous episode's targets.\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-130-        \"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-131-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-132-    def set_control(self, ctrl: float):\n/u\n… (703 characters left out) …\n.12/site-packages/bigym/robots/gripper.py-122-        return has_collided_collections(self.simulation, self._pad_geoms, other)\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-123-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-124-    def reset(self) -> None:\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-125-        \"\"\"Clear per-episode controller state; called from ``Robot.reset``.\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-126-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-127-        The base gripper is stateless. Subclasses that filter their targets\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-128-        across control steps override this so a reset never inherits the\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-129-        previous episode's targets.\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-130-        \"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-131-\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-132-    def set_control(self, ctrl: float):\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-133-        \"\"\"Set state of the gripper.\"\"\"\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-134-        ctrl = np.interp(ctrl, self._config.range, self._NORMAL_RANGE)\n/usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py-135-        if self._config.discrete:","exit":[],"pics":[]},"tok":{"in":71866,"cached":63587,"out":146,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":17,"t":896.9,"say":"","calls":[{"kind":"shell","label":"Read gripper class and Dex1 config","code":"sed -n 1,120p /usr/local/lib/python3.12/site-packages/bigym/robots/gripper.py; grep -rn \"dex1\\|Dex1\" /usr/local/lib/python3.12/site-packages/bigym/robots/configs/*.py | head"}],"out":{"text":"\"\"\"Robot Gripper.\"\"\"\n\nimport mujoco\nimport numpy as np\n\nfrom bigym import scene\nfrom bigym.const import HandSide\nfrom bigym.robots.config import GripperConfig\nfrom bigym.simulation import Simulation\nfrom bigym.utils.physics_utils import Colliders, has_collided_collections\n\n\nclass Gripper:\n    \"\"\"A gripper body of the robot, with its actuators and pads.\"\"\"\n\n    _NORMAL_RANGE = (0, 1)\n    _ROUND_DECIMALS = 1\n\n    def __init__(\n        self,\n        side: HandSide,\n        wrist_site: mujoco.MjsSite,\n        config: GripperConfig,\n        simulation: Simulation,\n        model: mujoco.MjSpec,\n    ):\n        \"\"\"Find the gripper in the robot ``model`` and add its pinch site if needed.\"\"\"\n        self._side = side\n        self._wrist_site = wrist_site\n        self._config = config\n        self.simulation = simulation\n\n        self._body = model.body(config.body)\n        if config.pinch_site:\n            self._pinch_site = model.site(config.pinch_site)\n        else:\n            self._pinch_site = self._body.add_site(\n                size=[0.01, 0.01, 0.01], rgba=[1, 1, 1, 1], group=5\n            )\n        self._actuators: list[mujoco.MjsActuator] = []\n        self._actuated_joints: list[mujoco.MjsJoint] = []\n        for actuator in model.actuators:\n            if (actuator.name or actuator.target) in config.actuators:\n                self._actuators.append(actuator)\n                self._actuated_joints.append(model.joint(actuator.target))\n        self._pad_geoms = [\n            geom\n… (7,093 characters left out) …\n     velocities = [\n            self.simulation.data.bind(joint).qvel.item()\n            for joint in self._actuated_joints\n        ]\n        return np.round(np.average(velocities), decimals=self._ROUND_DECIMALS)\n\n    def is_holding_object(self, other: Colliders) -> bool:\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/__init__.py:5:from bigym.robots.configs.g1 import G1Dex1\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/__init__.py:8:ROBOT_MODELS: dict[str, type[Robot]] = {\"g1_dex1\": G1Dex1}\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:26:# The G1 Dex1-1 MJCF + meshes ship as package assets, from the official\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:33:        str(ASSETS_PATH / \"g1\" / \"g1_29dof_with_dex1_1.xml\"),\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:112:    \"left_dex1_finger_joint_1\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:113:    \"left_dex1_finger_joint_2\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:117:    \"right_dex1_finger_joint_1\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:118:    \"right_dex1_finger_joint_2\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:121:# Dex1-1 finger travel (both joints share it): +0.0245 m = fully open,\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:129:# Dex1-1 finger PD (prismatic). kp=2000 saturates the URDF 20 N effort cap","exit":[],"pics":[]},"tok":{"in":72569,"cached":71860,"out":135,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":18,"t":905.8,"say":"","calls":[{"kind":"shell","label":"Read Dex1 gripper config details","code":"sed -n 100,170p /usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py; grep -n \"dex1\" /usr/local/lib/python3.12/site-packages/bigym/envs/xmls/g1/g1_29dof_with_dex1_1.xml | head"}],"out":{"text":"f\"{side}_wrist_roll_joint\": (20.0, 2.0),\n        f\"{side}_wrist_pitch_joint\": (20.0, 2.0),\n        f\"{side}_wrist_yaw_joint\": (20.0, 2.0),\n    }.items()\n}\n\nG1_ARM_ARMATURE: dict[str, float] = {\n    name: (0.00425 if (\"wrist_pitch\" in name or \"wrist_yaw\" in name) else 0.003609725)\n    for name in G1_ARM_PD\n}\n\nG1_DEX1_LEFT_HAND_JOINT_NAMES: tuple[str, ...] = (\n    \"left_dex1_finger_joint_1\",\n    \"left_dex1_finger_joint_2\",\n)\n\nG1_DEX1_RIGHT_HAND_JOINT_NAMES: tuple[str, ...] = (\n    \"right_dex1_finger_joint_1\",\n    \"right_dex1_finger_joint_2\",\n)\n\n# Dex1-1 finger travel (both joints share it): +0.0245 m = fully open,\n# -0.02 m = fully closed. Measured on the generated MJCF: the fingers sit on\n# opposing slide axes, so this 0.0445 m per-finger travel is the official\n# 90 mm stroke. On hardware one M4010 motor drives both fingers; the model's\n# two joints are always commanded together (one scalar per hand).\nG1_DEX1_QPOS_OPEN = 0.0245\nG1_DEX1_QPOS_CLOSED = -0.02\n\n# Dex1-1 finger PD (prismatic). kp=2000 saturates the URDF 20 N effort cap\n# at 1 cm of position error; kd~=critical for the 0.087 kg finger\n# (2*sqrt(kp*m)~=26). Full-stroke close takes ~0.25 s (the 0.2 m/s hardware\n# rate, via the gripper slew limit) with no hold chatter, and a blocked\n# squeeze saturates the +-20 N cap.\nG1_DEX1_HAND_PD: dict[str, tuple[float, float]] = {\n    name: (2000.0, 30.0)\n    for name in (G1_DEX1_LEFT_HAND_JOINT_NAMES + G1_DEX1_RIGHT_HAND_JOINT_NAMES)\n}\n\nG1_LEFT_ARM = ArmConfig(\n    site=\"left_end_\n… (3,289 characters left out) …\n_end_effector\",\n    links=[name.replace(\"_joint\", \"_link\") for name in G1_RIGHT_ARM_JOINT_NAMES],\n)\n\nG1_DEX1_LEFT_GRIPPER = GripperConfig(\n    actuators=list(G1_DEX1_LEFT_HAND_JOINT_NAMES),\n    range=np.array([0.0, 1.0], dtype=np.float32),\n    body=\"left_wrist_yaw_link\",\n    pad_bodies=[\n        \"left_dex1_finger_link_1\",\n        \"left_dex1_finger_link_2\",\n    ],\n    discrete=False,\n)\nG1_DEX1_RIGHT_GRIPPER = GripperConfig(\n    actuators=list(G1_DEX1_RIGHT_HAND_JOINT_NAMES),\n    range=np.array([0.0, 1.0], dtype=np.float32),\n    body=\"right_wrist_yaw_link\",\n    pad_bodies=[\n        \"right_dex1_finger_link_1\",\n        \"right_dex1_finger_link_2\",\n    ],\n    discrete=False,\n)\n\nG1_FLOATING_BASE = FloatingBaseConfig(\n    dofs={\n1:<mujoco model=\"g1_29dof_with_dex1_1\">\n57:    <mesh name=\"dex1_base_link\" file=\"Dex1_base_link.STL\"/>\n58:    <mesh name=\"dex1_finger_link_1\" file=\"Dex1_finger_link_1.STL\"/>\n59:    <mesh name=\"dex1_finger_link_2\" file=\"Dex1_finger_link_2.STL\"/>\n60:    <mesh name=\"dex1_col_1\" file=\"dex1_col_1.stl\"/>\n61:    <mesh name=\"dex1_col_2\" file=\"dex1_col_2.stl\"/>\n237:                          <body name=\"left_dex1_base_link\" pos=\"0.0415 0 0\">\n240:                            <geom type=\"mesh\" contype=\"0\" conaffinity=\"0\" group=\"1\" density=\"0\" rgba=\"0.79216 0.81961 0.93333 1\" mesh=\"dex1_base_link\"/>\n241:                            <geom type=\"mesh\" rgba=\"0.79216 0.81961 0.93333 1\" mesh=\"dex1_base_link\"/>\n242:                            <body name=\"left_dex1_finger_link_1\">","exit":[],"pics":[]},"tok":{"in":74152,"cached":72563,"out":153,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":19,"t":932.9,"say":"","calls":[{"kind":"robot","label":"Measure mug, gripper, handles in sim","code":"cat > explore2.py << 'EOF'\nimport sys, time\nsys.path.insert(0, \"/opt/tools\")\nimport numpy as np, mujoco\nfrom rcb_bigym2 import Session\n\ns = Session(\"/app/instance.json\")\nm, d = s.model, s.data\ntask = s.task\n\n# timing of steps\nt0=time.time()\nrow = s.hold_row().copy()\nfor i in range(50):\n    s.step(row)\nprint(\"50 hold steps:\", round(time.time()-t0,2), \"s\")\n\ndef geom_world_aabb(g):\n    # approximate: for box/cylinder/sphere use size; for mesh use data.geom_aabb (model) \n    return None\n\nprint(\"\\n--- mug geoms (world) ---\")\nfor k,cup in enumerate(task.cups):\n    print(f\"cup{k} pos={np.round(cup.get_position(),4)} quat={np.round(cup.get_quaternion(),3)}\")\n    for g in cup.geoms['collision'] if hasattr(cup,'geoms') else []:\n        pass\n\n# use model geoms belonging to mug bodies\nfor bname in (\"mug/mug\",\"mug_1/mug\"):\n    b = m.body(bname).id\n    lo=np.full(3,1e9); hi=np.full(3,-1e9)\n    for g in range(m.ngeom):\n        if m.geom_bodyid[g]==b and m.geom_contype[g]>0:\n            c = d.geom_xpos[g]; R = d.geom_xmat[g].reshape(3,3)\n            if m.geom_type[g]==mujoco.mjtGeom.mjGEOM_MESH:\n                # use model aabb\n                aabb = m.geom_aabb[g]  # center(3) size(3) in geom frame\n                corners = aabb[:3] + aabb[3:]*np.array([[i,j,k] for i in(-1,1) for j in(-1,1) for k in(-1,1)])\n                pts = c + (R@corners.T).T\n            else:\n                pts = c + (R@(m.geom_size[g]*np.array([[i,j,k] for i in(-1,1) for j in(-1,1) for k in(-1,1)])).T).T\n            lo=np.minimum(lo,pts.min(0)); hi=np.maximum(hi,pts.max(0))\n    print(bname, \"AABB lo\", np.round(lo,3), \"hi\", np.round(hi,3))\n\nprint(\"\\n--- dex1 finger/pad geoms world ---\")\n# open grippers fully\nrow = s.hold_row().copy()\nrow[19]=0.0; row[20]=0.0\nfor i in range(60): s.step(row)\nfor side in (\"left\",\"right\"):\n    for lb in (\"dex1_finger_link_1\",\"dex1_finger_link_2\"):\n        b = m.body(f\"g1_29dof_with_dex1_1/{side}_{lb}\").id\n        for g in range(m.ngeom):\n            if m.geom_bodyid[g]==b and m.geom_contype[g]>0:\n                print(side, lb, \"geom\", g, \"type\", m.geom_type[g], \"xpos\", np.round(d.geom_xpos[g],4))\n    j1 = d.qpos[m.joint(f\"g1_29dof_with_dex1_1/{side}_dex1_finger_joint_1\").qposadr[0]]\n    j2 = d.qpos[m.joint(f\"g1_29dof_with_dex1_1/{side}_dex1_finger_joint_2\").qposadr[0]]\n    print(side, \"finger qpos open:\", round(j1,4), round(j2,4))\n    ee = d.site_xpos[m.site(f\"g1_29dof_with_dex1_1/{side}_end_effector\").id]\n    print(side, \"EE site:\", np.round(ee,3))\n\nprint(\"\\n--- door handle geoms world (closed doors) ---\")\nfor bname in [m.body(i).name for i in range(m.nbody) if \"wall_cabinet\" in m.body(i).name]:\n    b = m.body(bname).id\n    gs=[g for g in range(m.ngeom) if m.geom_bodyid[g]==b]\n    if gs:\n        print(bname)\n        for g in gs:\n            print(\"   geom\",g,\"type\",m.geom_type[g],\"contype\",m.geom_contype[g],\"size\",np.round(m.geom_size[g],4),\"xpos\",np.round(d.geom_xpos[g],4),\"xmat\",np.round(d.geom_xmat[g].reshape(3,3),2).tolist())\nEOF\npython explore2.py 2>&1 | tail -90"}],"out":{"text":"[bigym] compiled timestep 0.001s != nominal 0.002s: control substeps 10 -> 20 to keep 50 Hz true\n50 hold steps: 0.3 s\n\n--- mug geoms (world) ---\ncup0 pos=[0.8129 0.1562 0.8591] quat=[-0.204 -0.001 -0.     0.979]\nTraceback (most recent call last):\n  File \"/app/work/explore2.py\", line 24, in <module>\n    for g in cup.geoms['collision'] if hasattr(cup,'geoms') else []:\n             ~~~~~~~~~^^^^^^^^^^^^^\nTypeError: list indices must be integers or slices, not str\n\n[stdout]\n[bigym] compiled timestep 0.001s != nominal 0.002s: control substeps 10 -> 20 to keep 50 Hz true\n50 hold steps: 0.3 s\n\n--- mug geoms (world) ---\ncup0 pos=[0.8129 0.1562 0.8591] quat=[-0.204 -0.001 -0.     0.979]\nTraceback (most recent call last):\n  File \"/app/work/explore2.py\", line 24, in <module>\n    for g in cup.geoms['collision'] if hasattr(cup,'geoms') else []:\n             ~~~~~~~~~^^^^^^^^^^^^^\nTypeError: list indices must be integers or slices, not str","exit":[],"pics":[]},"tok":{"in":75510,"cached":74146,"out":1363,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":20,"t":982.7,"say":"","calls":[{"kind":"shell","label":"Fix and rerun exploration script","code":"sed -i \"s/    for g in cup.geoms\\['collision'\\] if hasattr(cup,'geoms') else \\[\\]:\\n        pass//\" explore2.py && python - << 'EOF'\nimport re\nsrc = open('explore2.py').read()\nsrc = src.replace(\"\"\"    for g in cup.geoms['collision'] if hasattr(cup,'geoms') else []:\n        pass\n\"\"\", \"\")\nopen('explore2.py','w').write(src)\nEOF\npython explore2.py 2>&1 | tail -75"}],"out":{"text":"[bigym] compiled timestep 0.001s != nominal 0.002s: control substeps 10 -> 20 to keep 50 Hz true\n50 hold steps: 0.31 s\n\n--- mug geoms (world) ---\ncup0 pos=[0.8129 0.1562 0.8591] quat=[-0.204 -0.001 -0.     0.979]\ncup1 pos=[0.7954 0.0088 0.8591] quat=[-0.24  -0.001 -0.     0.971]\nmug/mug AABB lo [0.731 0.096 0.859] hi [0.873 0.217 0.964]\nmug_1/mug AABB lo [ 0.716 -0.053  0.859] hi [0.858 0.071 0.964]\n\n--- dex1 finger/pad geoms world ---\nleft dex1_finger_link_1 geom 59 type 7 xpos [0.5225 0.0948 0.8027]\nleft dex1_finger_link_1 geom 60 type 6 xpos [0.5266 0.1019 0.8021]\nleft dex1_finger_link_2 geom 62 type 7 xpos [0.5225 0.2014 0.8019]\nleft dex1_finger_link_2 geom 63 type 6 xpos [0.526  0.1944 0.8015]\nleft finger qpos open: 0.0245 0.0245\nleft EE site: [0.522 0.148 0.802]\nright dex1_finger_link_1 geom 81 type 7 xpos [ 0.5225 -0.2053  0.8043]\nright dex1_finger_link_1 geom 82 type 6 xpos [ 0.5267 -0.1982  0.8037]\nright dex1_finger_link_2 geom 84 type 7 xpos [ 0.5235 -0.0986  0.8038]\nright dex1_finger_link_2 geom 85 type 6 xpos [ 0.527  -0.1057  0.8033]\nright finger qpos open: 0.0245 0.0245\nright EE site: [ 0.523 -0.152  0.804]\n\n--- door handle geoms world (closed doors) ---\nwall_cabinet_600/wall_cabinet_600_offset\n   geom 104 type 6 contype 1 size [0.294 0.354 0.002] xpos [ 0.978 -0.     1.498] xmat [[0.0, -0.0, -1.0], [-1.0, -0.0, -0.0], [-0.0, 1.0, -0.0]]\n   geom 105 type 6 contype 1 size [0.16  0.36  0.008] xpos [ 0.84  -0.292  1.498] xmat [[1.0, -0.0, 0.0], [0.0, -0.0, -1.0], [\n… (2,559 characters left out) …\n 0.002] xpos [ 0.978 -0.     1.498] xmat [[0.0, -0.0, -1.0], [-1.0, -0.0, -0.0], [-0.0, 1.0, -0.0]]\n   geom 105 type 6 contype 1 size [0.16  0.36  0.008] xpos [ 0.84  -0.292  1.498] xmat [[1.0, -0.0, 0.0], [0.0, -0.0, -1.0], [0.0, 1.0, 0.0]]\n   geom 106 type 6 contype 1 size [0.16  0.36  0.008] xpos [0.84  0.292 1.498] xmat [[1.0, -0.0, 0.0], [0.0, -0.0, -1.0], [0.0, 1.0, 0.0]]\n   geom 107 type 6 contype 1 size [0.16  0.284 0.008] xpos [ 0.84 -0.    1.85] xmat [[1.0, -0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]\nwall_cabinet_600/shelf_bottom\n   geom 108 type 6 contype 1 size [0.16  0.284 0.008] xpos [ 0.84  -0.     1.146] xmat [[1.0, -0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]\nwall_cabinet_600/shelf\n   geom 109 type 6 contype 1 size [0.1475 0.284  0.008 ] xpos [ 0.83  -0.     1.498] xmat [[1.0, -0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]\nwall_cabinet_600/door_right_glass\n   geom 110 type 7 contype 1 size [0.008  0.1465 0.356 ] xpos [0.668 0.147 1.498] xmat [[-1.0, -0.0, 0.0], [-0.0, 1.0, 0.0], [-0.0, 0.0, -1.0]]\n   geom 111 type 6 contype 1 size [0.1   0.31  0.002] xpos [0.668 0.147 1.498] xmat [[0.0, -0.0, -1.0], [-1.0, -0.0, -0.0], [-0.0, 1.0, -0.0]]\nwall_cabinet_600/door_left_glass\n   geom 116 type 7 contype 1 size [0.008  0.1465 0.356 ] xpos [ 0.668 -0.147  1.498] xmat [[-1.0, -0.0, 0.0], [-0.0, 1.0, 0.0], [-0.0, 0.0, -1.0]]\n   geom 117 type 6 contype 1 size [0.1   0.31  0.002] xpos [ 0.668 -0.147  1.498] xmat [[0.0, -0.0, -1.0], [-1.0, -0.0, -0.0], [-0.0, 1.0, -0.0]]","exit":[],"pics":[]},"tok":{"in":77072,"cached":75504,"out":235,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":21,"t":1039.1,"say":"","calls":[{"kind":"shell","label":"Read full IK implementation","code":"sed -n 526,660p /usr/local/lib/python3.12/site-packages/bigym/loco/agent/envtools.py"},{"kind":"shell","label":"Read G1 upper body IK class","code":"sed -n 1,120p /usr/local/lib/python3.12/site-packages/bigym/vr/ik/g1_upper_body_ik.py"}],"out":{"text":"def ik(\n        self,\n        left_pos=None,\n        left_quat=None,\n        right_pos=None,\n        right_quat=None,\n        iters: int = 10,\n    ) -> np.ndarray:\n        \"\"\"Solve arm joints so the wrist sites reach world-frame targets.\n\n        Args:\n            left_pos: Left wrist target, or None to keep its current position.\n            left_quat: Left wrist orientation (w, x, y, z), or None for free.\n            right_pos: Right wrist target, or None to keep its current position.\n            right_quat: Right wrist orientation (w, x, y, z), or None for free.\n            iters: Differential-IK passes, so a far target converges in one call.\n\n        Returns:\n            14 joint angles (left 7, right 7) for the action's arm slots.\n\n        Raises:\n            RuntimeError: The interface withholds the solver.\n        \"\"\"\n        if not self.allow_ik:\n            raise RuntimeError(\n                \"tools.ik is not available under this interface: drive the arms in joint \"\n                \"space (raw arm slots are absolute joint targets in rad; low_dim_obs gives \"\n                \"the measured angles)\"\n            )\n        from bigym.vr.ik.mink_upper_body_ik import Pose  # imports mink\n\n        if self._ik is None:\n            from bigym.vr.ik.g1_upper_body_ik import G1UpperBodyIK\n\n            self._ik = G1UpperBodyIK(self.inner)\n        ik = self._ik\n        pelvis_position, pelvis_quaternion = self.pelvis_pose()\n        pelvis = Pose(pelvis_position, Quaternion(pelvis_qua\n… (16,741 characters left out) …\nay in the model as FIXED joints (measured angles\n        # written in per solve): the torso-pitch command bends the waist and\n        # moves the shoulders, which an upright stripped model would miss.\n        waist_joint_names = [robot.namespace + name for name in G1_WAIST_JOINT_NAMES]\n        kept = {*arm_joint_names, *waist_joint_names}\n        # The base joints go too: the pelvis is placed in the world per solve.\n        for joint in scene.descendants(frame, \"joints\"):\n            if joint.name not in kept:\n                spec.delete(joint)\n        for geom in spec.geoms:\n            geom.contype = 0\n            geom.conaffinity = 0\n\n        arms = robot.config.arms\n        self.pelvis = spec.body(robot.pelvis.name)\n        self.arm_joints = [spec.joint(name) for name in arm_joint_names]\n        self.left_arm_site = spec.site(robot.namespace + arms[HandSide.LEFT].site)\n        self.right_arm_site = spec.site(robot.namespace + arms[HandSide.RIGHT].site)\n        self.fixed_joint_names = G1_WAIST_JOINT_NAMES\n        self.model = spec.compile()\n        self.data = mujoco.MjData(self.model)\n        self._init_solver(\n            rest_pose=np.concatenate((REST_POSE_LEFT, REST_POSE_RIGHT)),\n            posture_weight=np.concatenate((POSTURE_WEIGHT, POSTURE_WEIGHT)),\n            posture_lm_damping=POSTURE_LM_DAMPING,\n            solve_iters=SOLVE_ITERS,\n            measured_resync_threshold=None,\n            fixed_joints=[spec.joint(name) for name in waist_joint_names],\n        )","exit":[],"pics":[]},"tok":{"in":79097,"cached":77066,"out":3177,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":22,"t":1181.7,"say":"","calls":[{"kind":"shell","label":"Check end_effector site definition","code":"grep -n \"end_effector\\|wrist_yaw_link\" /usr/local/lib/python3.12/site-packages/bigym/envs/xmls/g1/g1_29dof_with_dex1_1.xml | head; grep -n \"site name=\\\"left_end_effector\\\"\\|site name=\\\"right_end_effector\\\"\" -B2 -A2 /usr/local/lib/python3.12/site-packages/bigym/envs/xmls/g1/g1_29dof_with_dex1_1.xml"}],"out":{"text":"49:    <mesh name=\"left_wrist_yaw_link\" file=\"left_wrist_yaw_link_5010.STL\"/>\n56:    <mesh name=\"right_wrist_yaw_link\" file=\"right_wrist_yaw_link_5010.STL\"/>\n230:                        <body name=\"left_wrist_yaw_link\" pos=\"0.051 0 0\">\n235:                          <geom type=\"mesh\" contype=\"0\" conaffinity=\"0\" group=\"1\" density=\"0\" rgba=\"0.7 0.7 0.7 1\" mesh=\"left_wrist_yaw_link\"/>\n236:                          <geom type=\"mesh\" rgba=\"0.7 0.7 0.7 1\" mesh=\"left_wrist_yaw_link\"/>\n305:                        <body name=\"right_wrist_yaw_link\" pos=\"0.051 0 0\">\n310:                          <geom type=\"mesh\" contype=\"0\" conaffinity=\"0\" group=\"1\" density=\"0\" rgba=\"0.7 0.7 0.7 1\" mesh=\"right_wrist_yaw_link\"/>\n311:                          <geom type=\"mesh\" rgba=\"0.7 0.7 0.7 1\" mesh=\"right_wrist_yaw_link\"/>\n\n[stdout]\n49:    <mesh name=\"left_wrist_yaw_link\" file=\"left_wrist_yaw_link_5010.STL\"/>\n56:    <mesh name=\"right_wrist_yaw_link\" file=\"right_wrist_yaw_link_5010.STL\"/>\n230:                        <body name=\"left_wrist_yaw_link\" pos=\"0.051 0 0\">\n235:                          <geom type=\"mesh\" contype=\"0\" conaffinity=\"0\" group=\"1\" density=\"0\" rgba=\"0.7 0.7 0.7 1\" mesh=\"left_wrist_yaw_link\"/>\n236:                          <geom type=\"mesh\" rgba=\"0.7 0.7 0.7 1\" mesh=\"left_wrist_yaw_link\"/>\n305:                        <body name=\"right_wrist_yaw_link\" pos=\"0.051 0 0\">\n310:                          <geom type=\"mesh\" contype=\"0\" conaffinity=\"0\" group=\"1\" density=\"0\" rgba=\"0.7 0.7 0.7 1\" mesh=\"right_wrist_yaw_link\"/>\n311:                          <geom type=\"mesh\" rgba=\"0.7 0.7 0.7 1\" mesh=\"right_wrist_yaw_link\"/>","exit":[],"pics":[]},"tok":{"in":84875,"cached":79091,"out":360,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":23,"t":1306.0,"say":"","calls":[{"kind":"shell","label":"Find where end_effector site is defined","code":"grep -rn \"end_effector\" /usr/local/lib/python3.12/site-packages/bigym/robots/*.py /usr/local/lib/python3.12/site-packages/bigym/robots/configs/*.py | head; grep -rn \"add_site\" -B5 -A10 /usr/local/lib/python3.12/site-packages/bigym/robots/robot.py | head -40"}],"out":{"text":"/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:140:    site=\"left_end_effector\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:144:    site=\"right_end_effector\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:338:            model, \"left_wrist_yaw_link\", \"left_end_effector\", pos=self._EE_SITE_POS\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:341:            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS\n\n[stdout]\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:140:    site=\"left_end_effector\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:144:    site=\"right_end_effector\",\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:338:            model, \"left_wrist_yaw_link\", \"left_end_effector\", pos=self._EE_SITE_POS\n/usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py:341:            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS","exit":[],"pics":[]},"tok":{"in":85548,"cached":84869,"out":203,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":1325.5,"say":"","calls":[{"kind":"shell","label":"Read EE site position definition","code":"grep -n \"_EE_SITE_POS\\|_EE_SITE\" /usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py; sed -n 320,360p /usr/local/lib/python3.12/site-packages/bigym/robots/configs/g1.py"}],"out":{"text":"250:    _EE_SITE_POS: tuple[float, float, float] = (0.148, 0.0, 0.0)\n338:            model, \"left_wrist_yaw_link\", \"left_end_effector\", pos=self._EE_SITE_POS\n341:            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS\n                (HandSide.LEFT, G1_DEX1_LEFT_GRIPPER),\n                (HandSide.RIGHT, G1_DEX1_RIGHT_GRIPPER),\n            )\n        }\n\n    def _on_loaded(self, model: mujoco.MjSpec):\n        # Joint actuator-force limits follow autolimits, not the MJCF default class.\n        model.default.joint.actfrclimited = mujoco.mjtLimited.mjLIMITED_AUTO\n        for joint in model.joints:\n            joint.actfrclimited = mujoco.mjtLimited.mjLIMITED_AUTO\n\n        # The robot MJCF carries its own ground plane below the scene floor;\n        # it never touches anything but shows as a second floor in viewers.\n        ground = model.geom(\"ground\")\n        if ground is not None:\n            model.delete(ground)\n\n        self._ensure_site(\n            model, \"left_wrist_yaw_link\", \"left_end_effector\", pos=self._EE_SITE_POS\n        )\n        self._ensure_site(\n            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS\n        )\n\n        self._ensure_camera(\n            model,\n            \"torso_link\",\n            \"head\",\n            pos=(0.12, 0.0, 0.37),\n            euler=(0.0, -0.52, -1.57),\n        )\n        self._ensure_camera(\n            model,\n            \"left_wrist_yaw_link\",\n            \"left_wrist\",\n           \n… (323 characters left out) …\nS\n341:            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS\n                (HandSide.LEFT, G1_DEX1_LEFT_GRIPPER),\n                (HandSide.RIGHT, G1_DEX1_RIGHT_GRIPPER),\n            )\n        }\n\n    def _on_loaded(self, model: mujoco.MjSpec):\n        # Joint actuator-force limits follow autolimits, not the MJCF default class.\n        model.default.joint.actfrclimited = mujoco.mjtLimited.mjLIMITED_AUTO\n        for joint in model.joints:\n            joint.actfrclimited = mujoco.mjtLimited.mjLIMITED_AUTO\n\n        # The robot MJCF carries its own ground plane below the scene floor;\n        # it never touches anything but shows as a second floor in viewers.\n        ground = model.geom(\"ground\")\n        if ground is not None:\n            model.delete(ground)\n\n        self._ensure_site(\n            model, \"left_wrist_yaw_link\", \"left_end_effector\", pos=self._EE_SITE_POS\n        )\n        self._ensure_site(\n            model, \"right_wrist_yaw_link\", \"right_end_effector\", pos=self._EE_SITE_POS\n        )\n\n        self._ensure_camera(\n            model,\n            \"torso_link\",\n            \"head\",\n            pos=(0.12, 0.0, 0.37),\n            euler=(0.0, -0.52, -1.57),\n        )\n        self._ensure_camera(\n            model,\n            \"left_wrist_yaw_link\",\n            \"left_wrist\",\n            pos=(0.12, 0.0, 0.04),\n            euler=(0.0, -0.87, -1.57),\n        )\n        self._ensure_camera(\n            model,\n            \"right_wrist_yaw_link\",","exit":[],"pics":[]},"tok":{"in":85926,"cached":85542,"out":125,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":25,"t":1337.9,"say":"","calls":[{"kind":"shell","label":"Measure mug parts, pads, handles precisely","code":"cat > explore3.py << 'EOF'\nimport sys\nsys.path.insert(0, \"/opt/tools\")\nimport numpy as np, mujoco\nfrom rcb_bigym2 import Session\n\ns = Session(\"/app/instance.json\")\nm, d = s.model, s.data\ntask = s.task\n\ndef world_corners(g):\n    c = d.geom_xpos[g]; R = d.geom_xmat[g].reshape(3,3)\n    if m.geom_type[g]==mujoco.mjtGeom.mjGEOM_MESH:\n        aabb = m.geom_aabb[g]\n        base = aabb[:3] + aabb[3:]*np.array([[i,j,k] for i in(-1,1) for j in(-1,1) for k in(-1,1)])\n    elif m.geom_type[g]==mujoco.mjtGeom.mjGEOM_BOX:\n        base = m.geom_size[g]*np.array([[i,j,k] for i in(-1,1) for j in(-1,1) for k in(-1,1)])\n    else:\n        return c[None,:], None\n    return c + (R@base.T).T, None\n\nprint(\"--- mug collision parts AABBs (cup0 = mug, cup1 = mug_1) ---\")\nfor bname in (\"mug/mug\",\"mug_1/mug\"):\n    b = m.body(bname).id\n    print(bname, \"body pos\", np.round(d.xpos[b],4))\n    for g in range(m.ngeom):\n        if m.geom_bodyid[g]==b and m.geom_contype[g]>0:\n            pts,_ = world_corners(g)\n            if pts is not None:\n                print(f\"  geom{g} lo={np.round(pts.min(0),4)} hi={np.round(pts.max(0),4)}\")\n\nprint(\"--- dex1 pad geoms (boxes) sizes ---\")\nfor g in (60,63,82,85):\n    print(g, \"size\", m.geom_size[g], \"xpos\", np.round(d.geom_xpos[g],4), \"xmat\", np.round(d.geom_xmat[g].reshape(3,3),3).tolist())\n\nprint(\"--- door handle bodies (55, 57) ---\")\nfor b in (55,57):\n    print(\"body\", b, repr(m.body(b).name), \"parent\", m.body(m.body_parentid[b]).name, \"xpos\", np.round(d.xpos[b],4), \"xquat\", np.round(d.xquat[b],3))\n    for g in range(m.ngeom):\n        if m.geom_bodyid[g]==b:\n            print(\"   geom\", g, \"type\", m.geom_type[g], \"contype\", m.geom_contype[g], \"size\", np.round(m.geom_size[g],4), \"xpos\", np.round(d.geom_xpos[g],4))\n            R = d.geom_xmat[g].reshape(3,3)\n            print(\"      xmat cols:\", [np.round(R[:,i],3).tolist() for i in range(3)])\n\nprint(\"--- door joints qposadr ---\")\nfor jn in (\"wall_cabinet_600/door_right_glass\",\"wall_cabinet_600/door_left_glass\"):\n    j = m.joint(jn)\n    print(jn, \"qposadr\", j.qposadr[0], \"dofadr\", j.dofadr[0], \"qpos\", d.qpos[j.qposadr[0]])\n\nprint(\"--- pelvis pose ---\")\npos, quat = s.tools.pelvis_pose()\nprint(\"pelvis\", np.round(pos,3), np.round(quat,3))\nyaw = np.arctan2(2*(quat[0]*quat[3]+quat[1]*quat[2]), 1-2*(quat[2]**2+quat[3]**2))\nprint(\"yaw deg\", np.degrees(yaw))\n\nprint(\"--- counter geoms (top) ---\")\nfor g in range(m.ngeom):\n    bn = m.body(m.geom_bodyid[g]).name\n    if \"counter\" in bn:\n        pts,_ = world_corners(g)\n        if pts is not None:\n            print(g, m.geom_type[g], \"contype\", m.geom_contype[g], \"lo\", np.round(pts.min(0),3), \"hi\", np.round(pts.max(0),3))\nEOF\npython explore3.py 2>&1 | tail -75"}],"out":{"text":"mug/mug body pos [0.8129 0.1562 0.8591]\n  geom123 lo=[0.8033 0.1084 0.8721] hi=[0.8315 0.1223 0.9637]\n  geom124 lo=[0.7876 0.1103 0.8721] hi=[0.8075 0.1244 0.9637]\n  geom125 lo=[0.767  0.1614 0.8721] hi=[0.7812 0.1813 0.9637]\n  geom126 lo=[0.765  0.1375 0.8721] hi=[0.779  0.1656 0.9637]\n  geom127 lo=[0.7724 0.1749 0.8721] hi=[0.7998 0.1997 0.9637]\n  geom128 lo=[0.8316 0.1692 0.8722] hi=[0.8565 0.1965 0.9638]\n  geom129 lo=[0.7942 0.19   0.8722] hi=[0.8223 0.2039 0.9638]\n  geom130 lo=[0.8181 0.1878 0.8722] hi=[0.8381 0.202  0.9638]\n  geom131 lo=[0.8445 0.1309 0.8722] hi=[0.8587 0.1508 0.9638]\n  geom132 lo=[0.8467 0.1466 0.8722] hi=[0.8606 0.1748 0.9638]\n  geom133 lo=[0.8259 0.1125 0.8722] hi=[0.8533 0.1374 0.9638]\n  geom134 lo=[0.731  0.115  0.9211] hi=[0.7604 0.1389 0.9513]\n  geom135 lo=[0.748  0.1223 0.9397] hi=[0.7762 0.1457 0.9533]\n  geom136 lo=[0.7311 0.115  0.8708] hi=[0.7605 0.1389 0.901 ]\n  geom137 lo=[0.748  0.1224 0.8689] hi=[0.7763 0.1458 0.8825]\n  geom138 lo=[0.7338 0.1161 0.8969] hi=[0.7478 0.1334 0.9252]\n  geom139 lo=[0.7524 0.0956 0.859 ] hi=[0.8734 0.2167 0.8723]\n  geom140 lo=[0.7692 0.1157 0.8721] hi=[0.7941 0.1431 0.9637]\nmug_1/mug body pos [0.7954 0.0088 0.8591]\n  geom142 lo=[ 0.7887 -0.0395  0.8721] hi=[ 0.8173 -0.0238  0.9637]\n  geom143 lo=[ 0.7731 -0.0376  0.8721] hi=[ 0.793  -0.0245  0.9637]\n  geom144 lo=[0.749  0.0111 0.8721] hi=[0.7621 0.0309 0.9637]\n  geom145 lo=[ 0.7471 -0.0132  0.8721] hi=[0.7629 0.0153 0.9637]\n  geom146 lo=[0.753  0.0248 0.8721] hi=\n… (7,273 characters left out) …\n 0.032  1.2805]\n      xmat cols: [[0.0, 0.0, 1.0], [-1.0, -0.0, 0.0], [0.0, -1.0, 0.0]]\nbody 57 '' parent wall_cabinet_600/door_left_glass xpos [ 0.672 -0.032  1.238] xquat [-0.5 -0.5  0.5 -0.5]\n   geom 118 type 7 contype 0 size [0.0055 0.0177 0.059 ] xpos [ 0.6543 -0.032   1.238 ]\n      xmat cols: [[0.0, -1.0, 0.0], [1.0, 0.0, -0.0], [0.0, 0.0, 1.0]]\n   geom 119 type 6 contype 1 size [0.06   0.0032 0.006 ] xpos [ 0.645 -0.032  1.238]\n      xmat cols: [[0.0, 0.0, 1.0], [-1.0, -0.0, 0.0], [0.0, -1.0, 0.0]]\n   geom 120 type 6 contype 1 size [0.006 0.015 0.006] xpos [ 0.657  -0.032   1.1955]\n      xmat cols: [[0.0, 0.0, 1.0], [-1.0, -0.0, 0.0], [0.0, -1.0, 0.0]]\n   geom 121 type 6 contype 1 size [0.006 0.015 0.006] xpos [ 0.657  -0.032   1.2805]\n      xmat cols: [[0.0, 0.0, 1.0], [-1.0, -0.0, 0.0], [0.0, -1.0, 0.0]]\n--- door joints qposadr ---\nwall_cabinet_600/door_right_glass qposadr 40 dofadr 40 qpos 0.0\nwall_cabinet_600/door_left_glass qposadr 41 dofadr 41 qpos 0.0\n--- pelvis pose ---\npelvis [ 0.168 -0.003  0.747] [ 1.     0.001 -0.005  0.   ]\nyaw deg 0.019589219281504356\n--- counter geoms (top) ---\n92 6 contype 0 lo [ 0.603 -0.298  0.821] hi [1.2   0.298 0.859]\n93 6 contype 0 lo [ 0.601 -0.3    0.821] hi [0.604 0.3   0.859]\n94 6 contype 0 lo [ 1.199 -0.3    0.821] hi [1.202 0.3   0.859]\n95 6 contype 0 lo [ 0.601 -0.3    0.821] hi [ 1.202 -0.298  0.859]\n96 6 contype 0 lo [0.601 0.298 0.821] hi [1.202 0.3   0.859]\n97 6 contype 1 lo [ 0.601 -0.3    0.821] hi [1.202 0.3   0.859]","exit":[],"pics":[]},"tok":{"in":86557,"cached":85920,"out":1357,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":26,"t":1792.6,"say":"","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":91802,"cached":86551,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":28,"t":2222.6,"say":"","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":91846,"cached":91796,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":30,"t":2713.7,"say":"","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":91886,"cached":12906,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":32,"t":3217.7,"say":"","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":91926,"cached":12906,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":33,"t":3217.7,"say":"API Error: Claude's response exceeded the 32000 output token maximum. To configure this behavior, set the CLAUDE_CODE_MAX_OUTPUT_TOKENS environment variable.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":0,"cached":0,"out":0,"think":null,"usd":0},"sim":{"submit":0,"reset":0}}]}

runs/dexhand-stool-brace-insert-i00-privileged--ti7g8pu.json

@@ -0,0 +1 @@
+{"slug":"dexhand-stool-brace-insert-i00-privileged--ti7g8pu","task":"dexhand-stool-brace-insert-i00-privileged","bench":"dexhand","mode":"privileged","run":"claude_code-qwen3_8_max-high","agent":"claude-code","model":"qwen3.8-max","effort":"high","state":"failed","success":0,"reward":{"deterministic":1,"hand_wuji":0,"infra_error":0,"n_actions":3380,"sim_steps":3380,"stages_completed":0,"success":0,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0.0,"peak_memory_gb":0.565,"peak_processes":11,"peak_disk_gb":0.241,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":3518,"tokens":{"in":4153334,"cached":3976657,"out":133473,"usd":6.35},"task_text":"# DexHand: Assemble a wooden stool cross brace\n\nAssemble the cross brace of a pine stool dry frame. The lower side frame lies flat on the table with its four bores facing up and three rails already standing seated in three of them. The loose cross brace (a 0.26 m pine rail with an 8 mm dowel exposed 15 mm at each end) lies on the table, and the opposite side frame lies upside down beside the lower frame. Pick up the brace, seat one of its dowels in the empty bore of the lower frame, then lift the opposite side frame and lower it onto all four upper dowels so that both brace dowels end up seated in their legs. Ordered stages: (1) brace lifted: no brace-table contact, brace centre raised at least 0.05 m and its lowest bounding-box corner at least 0.02 m above the table top; (2) one brace dowel seated in a lower-frame bore; (3) opposite side frame lifted (the same lift test); (4) assembled: each of the eight bores holds exactly one seated dowel and every rail, the brace included, has one dowel seated in each side frame. A dowel is seated in a bore when its tip is 12 mm to 19 mm past the bore entry along the bore axis (12 mm is 80% of the exposed dowel), its tip is within 1.6 mm of the bore axis and the dowel axis is within 0.105 rad of the bore axis. Success: after stage 4 the assembled condition holds with no hand contact on any frame or rail and every part's centre-of-mass speed at most 0.02 m/s and angular speed at most 0.2 rad/s for 50 consecutive controls (1 s); the episode then ends. A single seated brace dowel or any partial assembly never counts. The episode ends immediately with failure, checked after every 2 ms physics substep, when the lower frame moves more than 0.03 m or tilts more than 10 degrees; a pre-seated rail is pulled to less than 8 mm in its bore or tilts more than 10 degrees; the brace touches the table after stage 1, or its centre drops below 0.09 m above the table top after stage 1; the brace tilts more than 20 degrees after stage 2; the opposite side frame touches the table after stage 3 or tilts more than 20 degrees from its upside-down carrying orientation after stage 3; any part with no contact at all (not held, not supported) has its centre of mass falling faster than 0.2 m/s (a drop); any part touches the floor, has its centre below the table top (z < 0.74 m) or leaves the workspace box x in [0.23, 1.23] m, y in [-0.73, 1.03] m, z in [0.70, 1.60] m; or the physics becomes unstable. Later actions cannot undo a failure. Only robot actuator targets are allowed: no object teleports, grasp welds, scripted object motion or direct object forces. All parts are free rigid pine bodies; the bores are hollow contact geometry of the source size (4.1 mm radius for the 4.0 mm dowels: 0.1 mm radial clearance, no entry chamfer); glue, screws, the seat and load capacity are not modelled. The episode allows at most 6000 controls at 50 Hz; reaching that limit without success is a failure.\n\nYou control one dexterous hand mounted on a six-D\n… (4,498 characters left out) …\nons, \"/app/output/trajectory.npz\")\n```\nRead `/opt/tools/task.json`, `scene.py`, `checker.py` and `runtime.py` for the complete geometry, failure checks and\npredicate. The world frame has z up; lengths are in metres and angles in radians. The table top is at\nz = 0.74 m; the lower side frame is centred at `task.json` `lower_frame_pos`, the opposite side frame at\n`upper_frame_pos` (upside down) and the brace at `brace_pos` (lying along x). Bore entries and dowel tips are MuJoCo sites\n(`<frame>_leg_<m|p>_b<k>_entry`, `<rail>_tip_<m|p>`).\n\n## External material\nYou may install packages you need (pip, apt), and you may read anything installed in your container, the simulator's and this benchmark's own source code included. Please solve the task yourself: do not search the web for, or download, a ready-made solution to it, such as published or reference solutions, recorded demonstrations, or policies trained for it. This is an honour rule; trials are reviewed. The network reaches your model's API and the package registries (PyPI, Debian / Ubuntu archives) only.\n\n## Resource limits\nLimits for the whole trial, all its processes together (every simulator you start included): at most **8 GiB of memory**, **512 processes** and **10 GiB** of new files under `/app`, `/tmp` and `/root`; the task 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 2 cores for your container; the cap only slows you down.\n\n## Time limit\nYou have 3600 seconds to complete this task. Do not cheat by using online solutions or hints specific to this task.\n\nThis is wall-clock time from the start of your session; the time a simulator takes to start counts. When it is up you are stopped without warning and only what is in `/app/output/` at that moment is graded, so save a deliverable as soon as you have one and overwrite it whenever you have a better one. Your session started when you received this task. `/run/rcb-limits/usage.json`, rewritten every few seconds, gives the time left on this limit (`time_left_s`) and its end (`deadline_utc`), counted from a little before your session started, so it never gives you more time than you have: read it (or run `date`) before you decide that time is short, never guess. Waiting counts too: a tool call that sends input to a process that keeps running (an interactive interpreter, a simulator loop, a server) can wait for the whole wait or yield time you give it (for example Codex's `yield_time_ms`) even when the answer is printed at once, so give such calls a short wait and poll again if the output is not complete, or run one-shot scripts that exit when they are done. Installing packages is not cheating (`## External material` above).\n","step_times":"recorded","sim_total":{"submit":0,"reset":0},"replay":"dexhand-stool-brace-insert-i00-privileged--ti7g8pu/replay.mp4","replay_last":"dexhand-stool-brace-insert-i00-privileged--ti7g8pu/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"List tool files and check usage limits","code":"ls /opt/tools/ /app/ 2>&1; cat /run/rcb-limits/usage.json 2>&1"},{"kind":"shell","label":"Locate rcb_dexhand package","code":"python -c \"import rcb_dexhand; print(rcb_dexhand.__file__)\" 2>&1; ls /app/output 2>&1"}],"out":{"text":"/app/:\noutput\n\n/opt/tools/:\nDockerfile\nassets\ncatalog.json\nchecker.py\ndocker-compose.yaml\ngrading.json\nhands.py\ninstance.json\nrcb_dexhand.py\nrcb_monitor\nreplay.py\nruntime.py\nscene.py\ntask.json\n{\n \"t\": 1792844724.44,\n \"measured\": true,\n \"gpu_memory_gb\": 0.0,\n \"memory_gb\": 0.21,\n \"processes\": 5,\n \"disk_gb\": 0.239,\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\": 10.0,\n  \"sustain_sec\": 60.0,\n  \"window_sec\": 120.0\n },\n \"violations\": [],\n \"emergency_kills\": 0,\n \"last_emergency_kill\": null,\n \"elapsed_s\": 60.0,\n \"time_limit_s\": 3600,\n \"time_left_s\": 3540.0,\n \"deadline_utc\": \"2026-10-24T13:24:24Z\"\n}\n\n[stdout]\n/app/:\noutput\n\n/opt/tools/:\nDockerfile\nassets\ncatalog.json\nchecker.py\ndocker-compose.yaml\ngrading.json\nhands.py\ninstance.json\nrcb_dexhand.py\nrcb_monitor\nreplay.py\nruntime.py\nscene.py\ntask.json\n{\n \"t\": 1792844724.44,\n \"measured\": true,\n \"gpu_memory_gb\": 0.0,\n \"memory_gb\": 0.21,\n \"processes\": 5,\n \"disk_gb\": 0.239,\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\": 10.0,\n  \"sustain_sec\": 60.0,\n  \"window_sec\": 120.0\n },\n \"violations\": [],\n \"emergency_kills\": 0,\n \"last_emergency_kill\": null,\n \"elapsed_s\": 60.0,\n \"time_limit_s\": 3600,\n \"time_left_s\": 3540.0,\n \"deadline_utc\": \"2026-10-24T13:24:24Z\"\n}\n/opt/tools/rcb_dexhand.py\n\n[stdout]\n/opt/tools/rcb_dexhand.py","exit":[],"pics":[]},"tok":{"in":17657,"cached":0,"out":201,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":9.4,"say":"","calls":[{"kind":"shell","label":"Read task configuration","code":"cat /opt/tools/task.json"},{"kind":"shell","label":"Check file sizes and package header","code":"wc -l /opt/tools/*.py; head -50 /opt/tools/rcb_dexhand.py"}],"out":{"text":"{\n  \"schema_version\": 1,\n  \"id\": \"stool_brace_insert\",\n  \"title\": \"Assemble a wooden stool cross brace\",\n  \"category\": \"furniture_assembly\",\n  \"description\": \"With one dexterous hand (Sharpa Wave by default, or Wuji Hand 2.2) on a six-axis wrist stage, pick up the loose cross brace of an ODDVAR-style pine stool dry frame, stand it in the empty bore of the lower side frame, then lift the opposite side frame onto all four upper dowels so both brace dowels are seated in their legs; drops, knocked rails or a displaced frame fail at once.\",\n  \"difficulty\": \"hard\",\n  \"mechanism\": \"free rigid pine parts, real hollow dowel bores (contact geometry, no welds)\",\n  \"instruction\": \"Assemble the cross brace of a pine stool dry frame. The lower side frame lies flat on the table with its four bores facing up and three rails already standing seated in three of them. The loose cross brace (a 0.26 m pine rail with an 8 mm dowel exposed 15 mm at each end) lies on the table, and the opposite side frame lies upside down beside the lower frame. Pick up the brace, seat one of its dowels in the empty bore of the lower frame, then lift the opposite side frame and lower it onto all four upper dowels so that both brace dowels end up seated in their legs. Ordered stages: (1) brace lifted: no brace-table contact, brace centre raised at least 0.05 m and its lowest bounding-box corner at least 0.02 m above the table top; (2) one brace dowel seated in a lower-frame bore; (3) opposite side frame lifted (the s\n… (9,557 characters left out) …\n     0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0\n    ],\n    \"wuji\": [\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0\n    ]\n  },\n  \"modeling\": \"Original T27 ODDVAR dry-frame geometry (two side frames, four 0.26 m rails with 8 mm dowels exposed 15 mm, blind 16 mm bores). Bores are hollow convex contact sectors of the source size (24 sectors, 4.1 mm radius for the 4.0 mm dowels: 0.1 mm radial clearance, no entry chamfer; dowel ends rounded as capsules); parts are free rigid bodies with explicit masses; the seat and eight screws are static decor. No glue, screws, welds or load capacity are modelled.\"\n}\n310 /opt/tools/checker.py\n  388 /opt/tools/hands.py\n    5 /opt/tools/rcb_dexhand.py\n  216 /opt/tools/replay.py\n  202 /opt/tools/runtime.py\n  300 /opt/tools/scene.py\n 1421 total\n\"\"\"Public privileged-mode entry point.\"\"\"\n\nfrom runtime import Session\n\n__all__ = [\"Session\"]\n\n[stdout]\n  310 /opt/tools/checker.py\n  388 /opt/tools/hands.py\n    5 /opt/tools/rcb_dexhand.py\n  216 /opt/tools/replay.py\n  202 /opt/tools/runtime.py\n  300 /opt/tools/scene.py\n 1421 total\n\"\"\"Public privileged-mode entry point.\"\"\"\n\nfrom runtime import Session\n\n__all__ = [\"Session\"]","exit":[],"pics":[]},"tok":{"in":18193,"cached":17651,"out":141,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":4,"t":20.7,"say":"","calls":[{"kind":"shell","label":"reads scene.py","code":"/opt/tools/scene.py"},{"kind":"shell","label":"reads runtime.py","code":"/opt/tools/runtime.py"}],"out":{"text":"1\t\"\"\"T27 ODDVAR stool dry frame with real dowel bores, composed with a dexterous hand on a six-axis wrist stage.\n2\t\n3\tGeometry follows the T27 scene source (two pine side frames with hollow blind bores, four 0.26 m rails with 8 mm\n4\tdowels exposed 15 mm, an ordinary grey table, an uninstalled seat and eight screws). Every task part is a free rigid\n5\tbody; bores are hollow convex contact sectors (no welds, no equality constraints, no object actuators).\n6\t\"\"\"\n7\t\n8\tfrom __future__ import annotations\n9\t\n10\timport hashlib\n11\timport importlib.util\n12\timport json\n13\tfrom pathlib import Path\n14\timport sys\n15\timport xml.etree.ElementTree as ET\n16\t\n17\timport mujoco\n18\timport numpy as np\n19\tfrom scipy.spatial.transform import Rotation\n20\t\n21\tHERE = Path(__file__).resolve().parent\n22\tASSETS = HERE / \"assets\"\n23\t\n24\t\n25\tdef _hands_module():\n26\t    \"\"\"The shared DexHand hand-selection module (copied next to this file in generated task dirs).\"\"\"\n27\t    try:\n28\t        import hands\n29\t\n30\t        return hands\n31\t    except ModuleNotFoundError:\n32\t        path = HERE.parents[1] / \"shared/hands.py\"\n33\t        spec = importlib.util.spec_from_file_location(\"hands\", path)\n34\t        module = importlib.util.module_from_spec(spec)\n35\t        sys.modules[\"hands\"] = module\n36\t        spec.loader.exec_module(module)\n37\t        return module\n38\t\n39\t\n40\thands = _hands_module()\n41\t\n42\tPINE = (0.83, 0.72, 0.54, 1)\n43\tFRAMES = (\"lower_frame\", \"upper_frame\")\n44\tRAILS = (\"brace\", \"rail_1\", \"rail_2\", \"rail_3\"\n… (22,820 characters left out) …\n    self.checker.set_state(snap[\"checker\"])\n177\t        self.last = copy.deepcopy(snap[\"last\"])\n178\t\n179\t    def state_sha(self):\n180\t        state = np.empty(mujoco.mj_stateSize(self.model, mujoco.mjtState.mjSTATE_INTEGRATION))\n181\t        mujoco.mj_getState(self.model, self.data, state, mujoco.mjtState.mjSTATE_INTEGRATION)\n182\t        digest = hashlib.sha256(state.astype(\"<f8\").tobytes())\n183\t        physics = {k: v for k, v in self.config.items() if k not in TEXT_KEYS}\n184\t        digest.update(json.dumps(physics, sort_keys=True).encode())\n185\t        digest.update(json.dumps(self.checker.get_state(), sort_keys=True).encode())\n186\t        digest.update(self.hand.encode())\n187\t        return digest.hexdigest()\n188\t\n189\t    # ------------------------------------------------------------------ rendering\n190\t    def render_frame(self, camera=\"overview\", width=640, height=480, shadows=True):\n191\t        if self.renderer is not None and (self.renderer.width != width or self.renderer.height != height):\n192\t            self.close()\n193\t        if self.renderer is None:\n194\t            self.renderer = mujoco.Renderer(self.model, height=height, width=width)\n195\t        self.renderer.update_scene(self.data, camera=camera)\n196\t        self.renderer.scene.flags[mujoco.mjtRndFlag.mjRND_SHADOW] = shadows\n197\t        return self.renderer.render().copy()\n198\t\n199\t    def close(self):\n200\t        if self.renderer:\n201\t            self.renderer.close()\n202\t            self.renderer = None\n203","exit":[],"pics":[]},"tok":{"in":16841,"cached":0,"out":0,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":5,"t":26.2,"say":"","calls":[{"kind":"shell","label":"reads checker.py","code":"/opt/tools/checker.py"},{"kind":"shell","label":"reads hands.py","code":"/opt/tools/hands.py"}],"out":{"text":"1\t\"\"\"Strict, state-only verdict for the stool brace insertion task.\n2\t\n3\tStages (in order, each latched once reached after the previous one):\n4\t  1 brace_lifted        the loose brace is off the table: no brace/table contact, centre raised >= 0.05 m and its\n5\t                        lowest bounding-box corner >= table top + 0.02 m\n6\t  2 brace_lower_seated  one brace dowel seated in a lower-side-frame bore\n7\t  3 frame_lifted        the opposite side frame is off the table: no frame/table contact, centre raised >= 0.05 m and\n8\t                        its lowest bounding-box corner >= table top + 0.02 m\n9\t  4 assembled           all eight dowel/bore interfaces seated: every bore of both side frames holds one dowel, and\n10\t                        every rail (the brace included) has one end in the lower frame and the other in the upper frame\n11\tSuccess: stage 4 reached and, for released_hold_steps consecutive controls, the assembled predicate holds with no hand\n12\tcontact on any task part and every task part slower than the speed tolerances. Success ends the episode.\n13\t\n14\tA dowel end is seated in a bore when its tip is >= seat_depth_m (80 % of the 15 mm exposed length) past the bore entry\n15\talong the bore axis, its tip is within seat_lateral_m of the bore axis and the dowel axis is within seat_axis_rad of\n16\tthe bore axis.\n17\t\n18\tFail-fast (checked after every physics substep, permanent): lower frame displaced > 3 cm or tilted > 10 deg; a\n19\tpre-seated rail pulled out (< 8 mm i\n… (35,211 characters left out) …\ntored_task!r} differs from {task!r}\")\n364\t    if hand not in widths:\n365\t        raise HandError(f\"hand {hand!r} is not available in this task\")\n366\t    width = int(widths[hand])\n367\t    if actions.ndim != 2 or actions.shape[1] != width:\n368\t        raise HandError(f\"{hand} actions must have shape (T, {width}); got {tuple(actions.shape)}\")\n369\t    if (len(actions) == 0 and not allow_empty) or (max_rows is not None and len(actions) > max_rows):\n370\t        raise HandError(f\"actions must have 1 to {max_rows} rows\")\n371\t    if not np.isfinite(actions).all():\n372\t        raise HandError(\"actions must contain finite numeric values\")\n373\t    return np.asarray(actions, dtype=np.float64), hand, names_value\n374\t\n375\t\n376\tdef write_trajectory(path, actions, *, hand, task=None, actuator_names=None) -> None:\n377\t    \"\"\"Write the deliverable: ``actions`` plus the ``hand`` (and optional task / actuator names) as strings.\"\"\"\n378\t    rows = np.asarray(actions, dtype=np.float64)\n379\t    if rows.ndim != 2 or not np.isfinite(rows).all():\n380\t        raise HandError(\"actions must be a finite (T, D) array\")\n381\t    extra = {\"hand\": np.array(canonical(hand))}\n382\t    if task is not None:\n383\t        extra[\"task\"] = np.array(str(task))\n384\t    if actuator_names is not None:\n385\t        extra[\"actuator_names\"] = np.array([str(x) for x in actuator_names])\n386\t    target = Path(path)\n387\t    target.parent.mkdir(parents=True, exist_ok=True)\n388\t    np.savez_compressed(target, actions=rows, **extra)\n389","exit":[],"pics":[]},"tok":{"in":29534,"cached":20622,"out":73,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":6,"t":299.1,"say":"I'll start by exploring the environment and understanding the task setup.","calls":[{"kind":"shell","label":"Inspect dexhand assets and task metadata","code":"ls /opt/dexhand/ 2>&1; ls /opt/dexhand/hand/ 2>&1 | head; cat /opt/tools/instance.json 2>/dev/null; cat /opt/tools/grading.json 2>/dev/null | head -40; cat /opt/tools/catalog.json 2>/dev/null | head -30"},{"kind":"shell","label":"reads replay.py","code":"/opt/tools/replay.py"}],"out":{"text":"hand\ntianji\nwuji_v2_2\nLICENSE\nassets\nright_hand.xml\n{\n  \"angular_speed_tolerance_rad_s\": 0.2,\n  \"bore_depth\": 0.016,\n  \"bore_radius\": 0.0041,\n  \"bore_sectors\": 24,\n  \"brace_pos\": [\n    0.57,\n    -0.33,\n    0.755\n  ],\n  \"category\": \"furniture_assembly\",\n  \"control_dt\": 0.02,\n  \"description\": \"With one dexterous hand (Sharpa Wave by default, or Wuji Hand 2.2) on a six-axis wrist stage, pick up the loose cross brace of an ODDVAR-style pine stool dry frame, stand it in the empty bore of the lower side frame, then lift the opposite side frame onto all four upper dowels so both brace dowels are seated in their legs; drops, knocked rails or a displaced frame fail at once.\",\n  \"difficulty\": \"hard\",\n  \"dowel_exposed\": 0.015,\n  \"dowel_radius\": 0.004,\n  \"dropped_height_m\": 0.09,\n  \"frame_mass\": 0.58,\n  \"frame_shift_limit_m\": 0.03,\n  \"frame_tilt_limit_rad\": 0.1745,\n  \"frame_x\": 0.61,\n  \"free_fall_speed_m_s\": 0.2,\n  \"half_spacing\": 0.145,\n  \"id\": \"stool_brace_insert\",\n  \"initial_targets\": {\n    \"sharpa\": [\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0\n    ],\n    \"wuji\": [\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0,\n      0.0\n… (28,737 characters left out) …\n6\t    parser.add_argument(\"--video\")\n187\t    parser.add_argument(\"--camera\", default=\"overview\")\n188\t    parser.add_argument(\"--fps\", type=int, choices=[5, 10, 25, 50])\n189\t    parser.add_argument(\"--width\", type=int, default=960)\n190\t    parser.add_argument(\"--height\", type=int, default=544)\n191\t    parser.add_argument(\"--hand\", help=\"hand recorded by the trusted service; must equal the archive's hand\")\n192\t    args = parser.parse_args()\n193\t    try:\n194\t        fps = args.fps if args.fps is not None else (5 if args.trusted_service else 10)\n195\t        result = replay(args.traj, args.video, args.camera, fps, args.trusted_service, args.hand, args.width,\n196\t                        args.height)\n197\t    except BadTrajectory as error:\n198\t        # Only archive-read and row-validation problems are the submitter's; scene/runtime errors stay infra errors.\n199\t        result = {\n200\t            \"success\": False,\n201\t            \"bad_trajectory\": 1,\n202\t            \"reason\": \"bad_trajectory\",\n203\t            \"error\": f\"{type(error).__name__}: {error}\"[:500],\n204\t            \"hand\": args.hand,\n205\t            \"n_actions\": 0,\n206\t            \"steps\": 0,\n207\t            \"stage\": 0,\n208\t            \"state_sha\": \"\",\n209\t        }\n210\t    if args.out:\n211\t        Path(args.out).write_text(json.dumps(result, indent=2) + \"\\n\")\n212\t    print(json.dumps({k: v for k, v in result.items() if k not in (\"timeline\", \"verdict\")}, indent=2))\n213\t\n214\t\n215\tif __name__ == \"__main__\":\n216\t    main()\n217","exit":[],"pics":[]},"tok":{"in":41431,"cached":29528,"out":12784,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":7,"t":344.1,"say":"Now let me examine the hand model and set up a session.","calls":[{"kind":"shell","label":"List Sharpa hand actuators","code":"cd /opt/dexhand/hand && python3 - <<'EOF'\nimport xml.etree.ElementTree as ET\nroot = ET.parse('right_hand.xml').getroot()\n# Actuators\nprint(\"=== ACTUATORS ===\")\nfor a in root.iter('actuator'):\n    for act in a:\n        print(act.tag, dict(act.attrib))\nEOF"},{"kind":"shell","label":"Show Sharpa hand body tree and joints","code":"cd /opt/dexhand/hand && python3 - <<'EOF'\nimport xml.etree.ElementTree as ET\nroot = ET.parse('right_hand.xml').getroot()\nprint(\"=== BODY TREE (name, pos) ===\")\ndef walk(b, depth=0):\n    print('  '*depth, b.get('name'), b.get('pos',''), b.get('quat',''))\n    for child in b.findall('body'):\n        walk(child, depth+1)\nfor wb in root.findall('worldbody'):\n    for b in wb.findall('body'):\n        walk(b)\nprint(\"=== JOINTS ===\")\nfor j in root.iter('joint'):\n    print(j.get('name'), 'range=', j.get('range'), 'axis=', j.get('axis'), 'type=', j.get('type'))\nEOF"}],"out":{"text":"=== ACTUATORS ===\ngeneral {'name': 'right_thumb_CMC_FE', 'class': 'sharpa', 'joint': 'right_thumb_CMC_FE', 'ctrlrange': '-0.1745 1.9199', 'gainprm': '6.95', 'biasprm': '0 -6.95 0.9'}\ngeneral {'name': 'right_thumb_CMC_AA', 'class': 'sharpa', 'joint': 'right_thumb_CMC_AA', 'ctrlrange': '-0.3491 0.3491', 'gainprm': '13.2', 'biasprm': '0 -13.2 0.9'}\ngeneral {'name': 'right_thumb_MCP_FE', 'class': 'sharpa', 'joint': 'right_thumb_MCP_FE', 'ctrlrange': '-0.5236 1.3963', 'gainprm': '4.76', 'biasprm': '0 -4.76 0.9'}\ngeneral {'name': 'right_thumb_MCP_AA', 'class': 'sharpa', 'joint': 'right_thumb_MCP_AA', 'ctrlrange': '-0.3491 0.3491', 'gainprm': '6.62', 'biasprm': '0 -6.62 0.9'}\ngeneral {'name': 'right_thumb_IP', 'class': 'sharpa', 'joint': 'right_thumb_IP', 'ctrlrange': '0 1.7453', 'gainprm': '0.9', 'biasprm': '0 -0.9 0.9'}\ngeneral {'name': 'right_index_MCP_FE', 'class': 'sharpa', 'joint': 'right_index_MCP_FE', 'ctrlrange': '-0.174533 1.5708', 'gainprm': '4.76', 'biasprm': '0 -4.76 0.9'}\ngeneral {'name': 'right_index_MCP_AA', 'class': 'sharpa', 'joint': 'right_index_MCP_AA', 'ctrlrange': '-0.3491 0.3491', 'gainprm': '6.62', 'biasprm': '0 -6.62 0.9'}\ngeneral {'name': 'right_index_PIP', 'class': 'sharpa', 'joint': 'right_index_PIP', 'ctrlrange': '0 1.7453', 'gainprm': '0.9', 'biasprm': '0 -0.9 0.9'}\ngeneral {'name': 'right_index_DIP', 'class': 'sharpa', 'joint': 'right_index_DIP', 'ctrlrange': '0 1.3963', 'gainprm': '0.9', 'biasprm': '0 -0.9 0.9'}\ngeneral {'name': 'right_middle_MCP_FE',\n… (9,799 characters left out) …\none range= None axis= None type= None\nNone range= None axis= None type= None\nNone range= None axis= None type= None\nright_thumb_CMC_FE range= -0.1745 1.9199 axis= 0 0 -1 type= None\nright_thumb_CMC_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_thumb_MCP_FE range= -0.5236 1.3963 axis= 0 0 -1 type= None\nright_thumb_MCP_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_thumb_IP range= 0 1.7453 axis= 0 0 -1 type= None\nright_index_MCP_FE range= -0.174533 1.5708 axis= 0 0 -1 type= None\nright_index_MCP_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_index_PIP range= 0 1.7453 axis= 0 0 -1 type= None\nright_index_DIP range= 0 1.3963 axis= 0 0 -1 type= None\nright_middle_MCP_FE range= -0.174533 1.5708 axis= 0 0 -1 type= None\nright_middle_MCP_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_middle_PIP range= 0 1.7453 axis= 0 0 -1 type= None\nright_middle_DIP range= 0 1.3963 axis= 0 0 -1 type= None\nright_ring_MCP_FE range= -0.174533 1.5708 axis= 0 0 -1 type= None\nright_ring_MCP_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_ring_PIP range= 0 1.7453 axis= 0 0 -1 type= None\nright_ring_DIP range= 0 1.3963 axis= 0 0 -1 type= None\nright_pinky_CMC range= 0 0.2618 axis= 0 0 -1 type= None\nright_pinky_MCP_FE range= -0.174533 1.5708 axis= 0 0 -1 type= None\nright_pinky_MCP_AA range= -0.3491 0.3491 axis= 0 0 -1 type= None\nright_pinky_PIP range= 0 1.7453 axis= 0 0 -1 type= None\nright_pinky_DIP range= 0 1.3963 axis= 0 0 -1 type= None\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":60906,"cached":41425,"out":393,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":736.9,"say":"Now let me set up a session and measure the hand geometry.","calls":[{"kind":"shell","label":"Explore session, hand geometry and object poses","code":"mkdir -p /app/work /app/output && cd /app/work && cat > explore.py <<'EOF'\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nnp.set_printoptions(precision=4, suppress=True)\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nprint(\"hand:\", s.hand, \"action_dim:\", s.action_dim)\nprint(\"nq nv nu:\", m.nq, m.nv, m.nu)\nprint(\"actuator names:\", s.actuator_names)\nlo, hi = m.actuator_ctrlrange.T\nfor i,(n,l,h) in enumerate(zip(s.actuator_names, lo, hi)):\n    print(f\"{i:2d} {n:24s} [{l:8.4f},{h:8.4f}] kp={m.actuator_gainprm[i,0]:.1f} frc=[{m.actuator_forcerange[i]}]\")\n# wrist stage body and hand bodies positions at initial pose\nprint(\"\\nstage origin qpos wrist:\", d.qpos[:6])\nfor name in [\"wrist_stage\",\"right_hand_C_MC\",\"right_index_DP\",\"right_middle_DP\",\"right_thumb_DP\",\"right_pinky_DP\",\"right_thumb_PP\"]:\n    bid = m.body(name).id\n    print(f\"{name:22s} xpos={d.xpos[bid]}\")\n# fingertip geoms\nprint(\"\\nfingertip geoms:\")\nfor g in range(m.ngeom):\n    gn = m.geom(g).name or \"\"\n    if \"fingertip\" in gn or \"tip\" in gn.lower():\n        print(f\"  {gn:40s} pos={d.geom_xpos[g]} size={m.geom_size[g]} type={m.geom_type[g]} friction={m.geom_friction[g]}\")\n# object states\nfor name in [\"lower_frame\",\"upper_frame\",\"brace\",\"rail_1\",\"rail_2\",\"rail_3\"]:\n    bid = m.body(name).id\n    print(f\"\\n{name}: xpos={d.xpos[bid]}\")\n    print(\"  xmat=\", d.xmat[bid].reshape(3,3))\nEOF\npython3 -I explore.py 2>&1 | tail -80"}],"out":{"text":"hand: sharpa action_dim: 28\nnq nv nu: 70 64 28\nactuator names: ['wrist_x_act', 'wrist_y_act', 'wrist_z_act', 'wrist_rx_act', 'wrist_ry_act', 'wrist_rz_act', 'right_thumb_CMC_FE', 'right_thumb_CMC_AA', 'right_thumb_MCP_FE', 'right_thumb_MCP_AA', 'right_thumb_IP', 'right_index_MCP_FE', 'right_index_MCP_AA', 'right_index_PIP', 'right_index_DIP', 'right_middle_MCP_FE', 'right_middle_MCP_AA', 'right_middle_PIP', 'right_middle_DIP', 'right_ring_MCP_FE', 'right_ring_MCP_AA', 'right_ring_PIP', 'right_ring_DIP', 'right_pinky_CMC', 'right_pinky_MCP_FE', 'right_pinky_MCP_AA', 'right_pinky_PIP', 'right_pinky_DIP']\n 0 wrist_x_act              [ -0.8000,  0.8000] kp=2500.0 frc=[[-80.  80.]]\n 1 wrist_y_act              [ -0.8000,  0.8000] kp=2500.0 frc=[[-80.  80.]]\n 2 wrist_z_act              [ -0.8000,  0.8000] kp=2500.0 frc=[[-80.  80.]]\n 3 wrist_rx_act             [ -3.1400,  3.1400] kp=120.0 frc=[[-10.  10.]]\n 4 wrist_ry_act             [ -3.1400,  3.1400] kp=120.0 frc=[[-10.  10.]]\n 5 wrist_rz_act             [ -3.1400,  3.1400] kp=120.0 frc=[[-10.  10.]]\n 6 right_thumb_CMC_FE       [ -0.1745,  1.9199] kp=7.0 frc=[[0. 0.]]\n 7 right_thumb_CMC_AA       [ -0.3491,  0.3491] kp=13.2 frc=[[0. 0.]]\n 8 right_thumb_MCP_FE       [ -0.5236,  1.3963] kp=4.8 frc=[[0. 0.]]\n 9 right_thumb_MCP_AA       [ -0.3491,  0.3491] kp=6.6 frc=[[0. 0.]]\n10 right_thumb_IP           [  0.0000,  1.7453] kp=0.9 frc=[[0. 0.]]\n11 right_index_MCP_FE       [ -0.1745,  1.5708] kp=4.8 frc=[[0. 0.]]\n12 right_index_MCP_AA \n… (5,435 characters left out) …\n0.1   1.15]\nright_index_DP         xpos=[ 0.7244 -0.0697  1.149 ]\nright_middle_DP        xpos=[ 0.7274 -0.09    1.15  ]\nright_thumb_DP         xpos=[0.6407 0.0038 1.1346]\nright_pinky_DP         xpos=[ 0.7154 -0.1311  1.147 ]\nright_thumb_PP         xpos=[ 0.6131 -0.0238  1.1346]\n\nfingertip geoms:\n  right_thumb_fingertip_collision          pos=[0.6512 0.0164 1.1355] size=[0.0094 0.0068 0.    ] type=3 friction=[1.5    0.005  0.0001]\n  right_index_fingertip_collision          pos=[ 0.7383 -0.0697  1.1499] size=[0.0081 0.0054 0.    ] type=3 friction=[1.5    0.005  0.0001]\n  right_middle_fingertip_collision         pos=[ 0.7413 -0.09    1.1509] size=[0.0081 0.0054 0.    ] type=3 friction=[1.5    0.005  0.0001]\n  right_ring_fingertip_collision           pos=[ 0.7353 -0.1103  1.1494] size=[0.0081 0.0054 0.    ] type=3 friction=[1.5    0.005  0.0001]\n  right_pinky_fingertip_collision          pos=[ 0.7293 -0.1311  1.1479] size=[0.0081 0.0054 0.    ] type=3 friction=[1.5    0.005  0.0001]\n\nlower_frame: xpos=[0.61  0.    0.755]\n  xmat= [[1. 0. 0.]\n [0. 1. 0.]\n [0. 0. 1.]]\n\nupper_frame: xpos=[0.61  0.5   0.755]\n  xmat= [[ 1.  0.  0.]\n [ 0. -1. -0.]\n [ 0.  0. -1.]]\n\nbrace: xpos=[ 0.57  -0.33   0.755]\n  xmat= [[ 0.  0.  1.]\n [ 0.  1.  0.]\n [-1.  0.  0.]]\n\nrail_1: xpos=[0.585 0.145 0.9  ]\n  xmat= [[1. 0. 0.]\n [0. 1. 0.]\n [0. 0. 1.]]\n\nrail_2: xpos=[ 0.785 -0.145  0.9  ]\n  xmat= [[1. 0. 0.]\n [0. 1. 0.]\n [0. 0. 1.]]\n\nrail_3: xpos=[0.785 0.145 0.9  ]\n  xmat= [[1. 0. 0.]\n [0. 1. 0.]\n [0. 0. 1.]]","exit":[],"pics":[]},"tok":{"in":64453,"cached":60900,"out":16998,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":932.4,"say":"The hand is clear now: fingers ~19cm from wrist, palm down at zero pose. Let me check sim speed and render the scene to understand geometry visually.","calls":[{"kind":"robot","label":"Render scene views and time simulation speed","code":"cat > explore2.py <<'EOF'\nimport sys, time, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nnp.set_printoptions(precision=4, suppress=True)\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nprint(\"ngeom:\", m.ngeom, \"nmesh:\", m.nmesh)\n# render views\nfor cam in [\"overview\",\"closeup\"]:\n    img = s.render_frame(cam)\n    import PIL.Image as I\n    I.fromarray(img).save(f\"/app/work/{cam}.png\")\n# time 200 steps holding\na = s.hold_action()\nt0=time.time()\nfor i in range(200):\n    s.step(a)\ndt=time.time()-t0\nprint(\"200 steps in\", dt, \"s ->\", 200/dt, \"steps/s\")\nprint(s.status()[\"reason\"], s.status()[\"stage\"])\n# hand geom inventory: collision geoms of fingers with sizes\nprint(\"\\nhand geoms (collision-relevant):\")\nfor g in range(m.ngeom):\n    gn = m.geom(g).name or \"\"\n    if s.owner[g]==\"hand\" and m.geom_contype[g]>0:\n        print(f\"  {gn:44s} type={m.geom_type[g]} size={np.round(m.geom_size[g],4)} xpos={np.round(d.geom_xpos[g],3)}\")\nEOF\ntimeout 300 python3 -I explore2.py 2>&1 | tail -60"}],"out":{"text":"ngeom: 356 nmesh: 246\n200 steps in 2.1438026428222656 s -> 93.29216971983239 steps/s\n 0\n\nhand geoms (collision-relevant):\nTraceback (most recent call last):\n  File \"/app/work/explore2.py\", line 25, in <module>\n    if s.owner[g]==\"hand\" and m.geom_contype[g]>0:\n       ~~~~~~~^^^\nKeyError: 0\n\n[stdout]\nngeom: 356 nmesh: 246\n200 steps in 2.1438026428222656 s -> 93.29216971983239 steps/s\n 0\n\nhand geoms (collision-relevant):\nTraceback (most recent call last):\n  File \"/app/work/explore2.py\", line 25, in <module>\n    if s.owner[g]==\"hand\" and m.geom_contype[g]>0:\n       ~~~~~~~^^^\nKeyError: 0","exit":[],"pics":[]},"tok":{"in":83862,"cached":64447,"out":8231,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":950.8,"say":"","calls":[{"kind":"shell","label":"List hand collision geoms","code":"cat > explore3.py <<'EOF'\nimport sys, time, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nnp.set_printoptions(precision=4, suppress=True)\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\ngo = s.checker.geom_owner\nprint(\"hand geoms:\")\nfor g in range(m.ngeom):\n    gn = m.geom(g).name or \"\"\n    if go[g]==\"hand\" and m.geom_contype[g]>0:\n        print(f\"  {gn:44s} type={m.geom_type[g]} size={np.round(m.geom_size[g],4)} pos={np.round(d.geom_xpos[g],4)}\")\nEOF\ntimeout 300 python3 -I explore3.py 2>&1 | tail -70"}],"out":{"text":"hand geoms:\n  palm000_collision                            type=7 size=[0.0036 0.0208 0.024 ] pos=[ 0.5936 -0.0888  1.1338]\n  palm001_collision                            type=7 size=[0.0048 0.0188 0.0216] pos=[ 0.5687 -0.1218  1.1306]\n  palm002_collision                            type=7 size=[0.0033 0.0141 0.0237] pos=[ 0.5799 -0.1266  1.1559]\n  palm003_collision                            type=7 size=[0.0028 0.0139 0.0275] pos=[ 0.5721 -0.077   1.1704]\n  palm004_collision                            type=7 size=[0.0051 0.0062 0.0296] pos=[ 0.6317 -0.0915  1.1673]\n  palm005_collision                            type=7 size=[0.0029 0.0056 0.0292] pos=[ 0.6316 -0.0917  1.1323]\n  palm006_collision                            type=7 size=[0.0029 0.0102 0.0264] pos=[ 0.6041 -0.1144  1.1311]\n  palm007_collision                            type=7 size=[0.0039 0.0118 0.0172] pos=[ 0.5647 -0.0779  1.1332]\n  palm008_collision                            type=7 size=[0.0026 0.015  0.0168] pos=[ 0.5697 -0.1355  1.1471]\n  palm009_collision                            type=7 size=[0.0019 0.0157 0.0334] pos=[ 0.6089 -0.0769  1.1715]\n  palm010_collision                            type=7 size=[0.0042 0.01   0.0204] pos=[ 0.6104 -0.0621  1.1371]\n  palm011_collision                            type=7 size=[0.0029 0.0122 0.0247] pos=[ 0.5763 -0.0639  1.1556]\n  palm012_collision                            type=7 size=[0.0033 0.0047 0.0267] pos=[ 0.5527 -0.0996  1.129 ]\n  palm013_collision             \n… (8,899 characters left out) …\n0.0054 0.    ] pos=[ 0.7383 -0.0697  1.1499]\n  right_middle_MCP_VL_fit                      type=5 size=[0.0126 0.0057 0.    ] pos=[ 0.6506 -0.09    1.1495]\n  right_middle_PP_fit                          type=3 size=[0.0093 0.0172 0.    ] pos=[ 0.6794 -0.09    1.1501]\n  right_middle_MP_fit                          type=3 size=[0.0094 0.0147 0.    ] pos=[ 0.7106 -0.09    1.1512]\n  right_middle_fingertip_collision             type=3 size=[0.0081 0.0054 0.    ] pos=[ 0.7413 -0.09    1.1509]\n  right_ring_MCP_VL_fit                        type=5 size=[0.0126 0.0057 0.    ] pos=[ 0.6446 -0.1103  1.148 ]\n  right_ring_PP_fit                            type=3 size=[0.0097 0.0172 0.    ] pos=[ 0.6734 -0.1103  1.1486]\n  right_ring_MP_fit                            type=3 size=[0.0104 0.0147 0.    ] pos=[ 0.7046 -0.1103  1.1497]\n  right_ring_fingertip_collision               type=3 size=[0.0081 0.0054 0.    ] pos=[ 0.7353 -0.1103  1.1494]\n                                               type=7 size=[0.0138 0.0259 0.0277] pos=[ 0.6034 -0.1323  1.1494]\n  right_pinky_MCP_VL_fit                       type=5 size=[0.0126 0.0057 0.    ] pos=[ 0.6386 -0.1311  1.1466]\n  right_pinky_PP_fit                           type=3 size=[0.0107 0.0172 0.    ] pos=[ 0.6674 -0.1311  1.1471]\n  right_pinky_MP_fit                           type=3 size=[0.0099 0.0147 0.    ] pos=[ 0.6986 -0.1311  1.1482]\n  right_pinky_fingertip_collision              type=3 size=[0.0081 0.0054 0.    ] pos=[ 0.7293 -0.1311  1.1479]","exit":[],"pics":[]},"tok":{"in":92237,"cached":83856,"out":343,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":11,"t":1618.1,"say":"The setup is clear. Let me analyze the task structure and check key geometry facts before writing the controller.","calls":[{"kind":"shell","label":"","code":""}],"out":{"text":"<tool_use_error>InputValidationError: Bash was called with input that could not be parsed as JSON.\nYou sent (first 200 of 883 bytes): {\"command\": \"cat > calib.py <<'EOF'\\nimport sys, numpy as np\\nsys.path.insert(0, \\\"/opt/tools\\\")\\nfrom rcb_dexhand import Session\\nnp.set_printoptions(precision=4, suppress=True)\\ns = Session(\\\"stool_\nCommon causes: unescaped backslashes in file paths (use / or \\\\), unescaped control characters, or truncated output. Retry with valid JSON.</tool_use_error>\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":95654,"cached":92231,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":1644.3,"say":"Let me write calibration scripts with the Write tool instead.","calls":[{"kind":"edit","label":"calib.py","code":"/app/work/calib.py\n\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nfrom scipy.spatial.transform import Rotation\nimport mujoco\nnp.set_printoptions(precision=4, suppress=True)\n\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nORIGIN = np.array([0.55, -0.1, 1.15])\n\n# 1) verify wrist kinematics: palm body pos = ORIGIN + ctrl[:3]? orientation = Rx@Ry@Rz?\na = s.hold_action()\ntest = np.array([0.05, -0.03, -0.10, 0.3, -0.2, 0.4])\na[:6] = test\nfor _ in range(300):\n    d.ctrl[:] = a\n    mujoco.mj_step(m, d)\nmujoco.mj_forward(m, d)\nprint(\"wrist qpos:\", d.qpos[:6])\nbid = m.body(\"right_hand_C_MC\").id\nprint(\"palm xpos:\", d.xpos[bid], \" expected:\", ORIGIN + test[:3])\nRpred = Rotation.from_euler(\"XYZ\", test[3:6]).as_matrix()\nprint(\"palm R:\\n\", d.xmat[bid].reshape(3, 3))\nprint(\"Rx Ry Rz:\\n\", Rpred)\nprint(\"max diff:\", np.abs(d.xmat[bid].reshape(3, 3) - Rpred).max())\n\n# hand mass estimate\nmass = sum(m.body_mass[i] for i in range(m.nbody) if s.checker.owner.get(i) == \"hand\")\nprint(\"hand mass:\", mass)\n"}],"out":{"text":"File created successfully at: /app/work/calib.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":127867,"cached":95648,"out":461,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":1666.6,"say":"","calls":[{"kind":"shell","label":"Run wrist kinematics calibration","code":"timeout 120 python3 -I calib.py 2>&1 | tail -30"}],"out":{"text":"wrist qpos: [ 0.05   -0.03   -0.1052  0.2968 -0.1943  0.3988]\npalm xpos: [ 0.6    -0.13    1.0448]  expected: [ 0.6  -0.13  1.05]\npalm R:\n [[ 0.193  -0.381   0.9042]\n [ 0.2869  0.9032  0.3193]\n [-0.9383  0.1978  0.2837]]\nRx Ry Rz:\n [[ 0.9027 -0.3817 -0.1987]\n [ 0.3179  0.9028 -0.2896]\n [ 0.2899  0.1983  0.9363]]\nmax diff: 1.2281919139518362\nhand mass: 1.3251100000000002\n\n[stdout]\nwrist qpos: [ 0.05   -0.03   -0.1052  0.2968 -0.1943  0.3988]\npalm xpos: [ 0.6    -0.13    1.0448]  expected: [ 0.6  -0.13  1.05]\npalm R:\n [[ 0.193  -0.381   0.9042]\n [ 0.2869  0.9032  0.3193]\n [-0.9383  0.1978  0.2837]]\nRx Ry Rz:\n [[ 0.9027 -0.3817 -0.1987]\n [ 0.3179  0.9028 -0.2896]\n [ 0.2899  0.1983  0.9363]]\nmax diff: 1.2281919139518362\nhand mass: 1.3251100000000002","exit":[],"pics":[]},"tok":{"in":128371,"cached":127861,"out":76,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":14,"t":1690.7,"say":"Position matches (with gravity droop); orientation needs the mount quat composed. Let me verify precisely:","calls":[{"kind":"edit","label":"calib2.py","code":"/app/work/calib2.py\n\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nfrom scipy.spatial.transform import Rotation\nimport mujoco\nnp.set_printoptions(precision=4, suppress=True)\n\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nORIGIN = np.array([0.55, -0.1, 1.15])\nMOUNT = Rotation.from_euler(\"y\", np.pi / 2).as_matrix()\n\na = s.hold_action()\ntest = np.array([0.05, -0.03, -0.10, 0.3, -0.2, 0.4])\na[:6] = test\nfor _ in range(300):\n    d.ctrl[:] = a\n    mujoco.mj_step(m, d)\nmujoco.mj_forward(m, d)\nbid = m.body(\"right_hand_C_MC\").id\nq = d.qpos[3:6]\nRpred = Rotation.from_euler(\"XYZ\", q).as_matrix() @ MOUNT\nprint(\"qpos rot:\", q)\nprint(\"max diff:\", np.abs(d.xmat[bid].reshape(3, 3) - Rpred).max())\n\n# also check at zero angles the palm faces down\nd2 = test.copy(); d2[3:] = 0\nfor _ in range(300):\n    d.ctrl[:6] = d2\n    mujoco.mj_step(m, d)\nmujoco.mj_forward(m, d)\nprint(\"zero-angle palm R:\\n\", d.xmat[bid].reshape(3, 3))\n\n# Finger pad world positions for a few curl patterns (no object): useful to find the wrap center.\ns.restore(s.snapshot())  # not useful; just reset\ns.reset()\ndef fingers_at(pattern, wrist):\n    s.reset()\n    a = s.hold_action()\n    a[:6] = wrist\n    for i, n in enumerate(s.actuator_names):\n        if n in pattern:\n            a[6 + i - 6] = 0  # placeholder\n    # set finger targets by name\n    for i, n in enumerate(s.actuator_names):\n        if n in pattern:\n            a[i] = pattern[n]\n    for _ in range(100):\n        d.ctrl[:] = a\n        mujoco.mj_step(m, d)\n    mujoco.mj_forward(m, d)\n    W = ORIGIN + wrist[:3]\n    pads = {}\n    for g in range(m.ngeom):\n        gn = m.geom(g).name or \"\"\n        if \"fingertip_collision\" in gn or \"_fit\" in gn:\n            pads[gn] = d.geom_xpos[g] - W\n    return pads\n\nopen_pose = {n: 0.0 for n in s.actuator_names[6:]}\ncurl_pose = {\"right_thumb_CMC_FE\": 1.0, \"right_thumb_CMC_AA\": 0.0, \"right_thumb_MCP_FE\": 0.7,\n             \"right_thumb_MCP_AA\": 0.0, \"right_thumb_IP\": 0.5,\n             \"right_index_MCP_FE\": 1.1, \"right_index_PIP\": 1.3, \"right_index_DIP\": 0.7,\n             \"right_middle_MCP_FE\": 1.1, \"right_middle_PIP\": 1.3, \"right_middle_DIP\": 0.7,\n             \"right_ring_MCP_FE\": 1.1, \"right_ring_PIP\": 1.3, \"right_ring_DIP\": 0.7,\n             \"right_pinky_CMC\": 0.1, \"right_pinky_MCP_FE\": 1.1, \"right_pinky_PIP\": 1.3, \"right_pinky_DIP\": 0.7}\nfor name, pat in [(\"open\", open_pose), (\"curl\", curl_pose)]:\n    pads = fingers_at(pat, np.zeros(6))\n    print(f\"--- {name} (wrist zero; positions relative to wrist point) ---\")\n    for k in [\"right_index_fingertip_collision\", \"right_middle_fingertip_collision\", \"right_ring_fingertip_collision\",\n              \"right_pinky_fingertip_collision\", \"right_thumb_fingertip_collision\",\n              \"right_index_MP_fit\", \"right_middle_MP_fit\"]:\n        if k in pads:\n            print(f\"  {k:36s} {pads[k]}\")\n"}],"out":{"text":"File created successfully at: /app/work/calib2.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":128764,"cached":128365,"out":1856,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":15,"t":1756.7,"say":"","calls":[{"kind":"shell","label":"Verify wrist rotation composition and finger pad positions","code":"timeout 120 python3 -I calib2.py 2>&1 | tail -30"}],"out":{"text":"qpos rot: [ 0.2968 -0.1943  0.3988]\nmax diff: 3.3306690738754696e-16\nzero-angle palm R:\n [[-0.0011 -0.0014  1.    ]\n [-0.0019  1.      0.0014]\n [-1.     -0.0019 -0.0011]]\n--- open (wrist zero; positions relative to wrist point) ---\n  right_index_fingertip_collision      [ 0.1883  0.0303 -0.0066]\n  right_middle_fingertip_collision     [ 0.1913  0.01   -0.0056]\n  right_ring_fingertip_collision       [ 0.1853 -0.0103 -0.0071]\n  right_pinky_fingertip_collision      [ 0.1793 -0.0311 -0.0085]\n  right_thumb_fingertip_collision      [ 0.1011  0.1164 -0.0205]\n  right_index_MP_fit                   [ 0.1576  0.0303 -0.0061]\n  right_middle_MP_fit                  [ 0.1606  0.01   -0.0051]\n--- curl (wrist zero; positions relative to wrist point) ---\n  right_index_fingertip_collision      [ 0.1572  0.0302 -0.0752]\n  right_middle_fingertip_collision     [ 0.1602  0.0099 -0.0742]\n  right_ring_fingertip_collision       [ 0.1542 -0.0104 -0.0756]\n  right_pinky_fingertip_collision      [ 0.1482 -0.0297 -0.0772]\n  right_thumb_fingertip_collision      [ 0.1126  0.0643 -0.0785]\n  right_index_MP_fit                   [ 0.141   0.0302 -0.0491]\n  right_middle_MP_fit                  [ 0.144   0.0099 -0.0481]\n\n[stdout]\nqpos rot: [ 0.2968 -0.1943  0.3988]\nmax diff: 3.3306690738754696e-16\nzero-angle palm R:\n [[-0.0011 -0.0014  1.    ]\n [-0.0019  1.      0.0014]\n [-1.     -0.0019 -0.0011]]\n--- open (wrist zero; positions relative to wrist point) ---\n  right_index_fingertip_collision      [ 0.1883  0.0303 -0.0066]\n  right_middle_fingertip_collision     [ 0.1913  0.01   -0.0056]\n  right_ring_fingertip_collision       [ 0.1853 -0.0103 -0.0071]\n  right_pinky_fingertip_collision      [ 0.1793 -0.0311 -0.0085]\n  right_thumb_fingertip_collision      [ 0.1011  0.1164 -0.0205]\n  right_index_MP_fit                   [ 0.1576  0.0303 -0.0061]\n  right_middle_MP_fit                  [ 0.1606  0.01   -0.0051]\n--- curl (wrist zero; positions relative to wrist point) ---\n  right_index_fingertip_collision      [ 0.1572  0.0302 -0.0752]\n  right_middle_fingertip_collision     [ 0.1602  0.0099 -0.0742]\n  right_ring_fingertip_collision       [ 0.1542 -0.0104 -0.0756]\n  right_pinky_fingertip_collision      [ 0.1482 -0.0297 -0.0772]\n  right_thumb_fingertip_collision      [ 0.1126  0.0643 -0.0785]\n  right_index_MP_fit                   [ 0.141   0.0302 -0.0491]\n  right_middle_MP_fit                  [ 0.144   0.0099 -0.0481]","exit":[],"pics":[]},"tok":{"in":130664,"cached":128758,"out":207,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":16,"t":1823.1,"say":"","calls":[{"kind":"edit","label":"tuner.py","code":"/app/work/tuner.py\n\nimport sys, json, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nimport mujoco\nnp.set_printoptions(precision=4, suppress=True)\n\nORIGIN = np.array([0.55, -0.1, 1.15])\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nNAMES = s.actuator_names\nSNAP0 = s.snapshot()\n\ndef wrist_point():\n    return d.qpos[:3] + ORIGIN\n\ndef part_pose(name):\n    bid = m.body(name).id\n    return d.xpos[bid].copy(), d.xmat[bid].reshape(3, 3).copy()\n\ndef hold(ctrl, n=60):\n    for _ in range(n):\n        st = s.step(ctrl)\n        if s.done:\n            return st\n    return s.last\n\ndef set_row(wrist, fingers):\n    row = np.zeros(28)\n    row[:6] = wrist\n    for k, v in fingers.items():\n        row[NAMES.index(k)] = v\n    lo, hi = m.actuator_ctrlrange.T\n    return np.clip(row, lo, hi)\n\ndef hand_obj_contacts(obj):\n    pairs = s.checker.contacts(d)\n    return sorted({o for p, o in pairs if p == obj}), sorted({p for p, o in pairs if o == obj and p == \"hand\"})\n\ndef run(cmd):\n    global SNAP0\n    op = cmd[\"op\"]\n    if op == \"quit\":\n        return \"bye\"\n    if op == \"reset\":\n        s.restore(SNAP0)\n        return {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"]}\n    if op == \"pose\":  # move to wrist pose with finger pattern, settle\n        row = set_row(cmd[\"wrist\"], cmd.get(\"fingers\", {}))\n        st = hold(row, cmd.get(\"n\", 80))\n        return {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"],\n                \"brace\": part_pose(\"brace\")[0], \"qpos_wrist\": d.qpos[:6]}\n    if op == \"report\":\n        out = {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"], \"steps\": s.steps}\n        for name in cmd.get(\"parts\", [\"brace\"]):\n            p, R = part_pose(name)\n            out[name] = {\"pos\": p, \"R\": R.tolist()}\n        for obj in cmd.get(\"contacts\", [\"brace\"]):\n            out[obj + \"_contacts\"] = hand_obj_contacts(obj)\n        for site in cmd.get(\"sites\", []):\n            sid = m.site(site).id\n            out[site] = d.site_xpos[sid].copy()\n        return out\n    if op == \"fingers\":  # keep wrist, change fingers\n        row = d.ctrl.copy()\n        for k, v in cmd[\"fingers\"].items():\n            row[NAMES.index(k)] = v\n        lo, hi = m.actuator_ctrlrange.T\n        row = np.clip(row, lo, hi)\n        st = hold(row, cmd.get(\"n\", 80))\n        return {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"], \"brace\": part_pose(\"brace\")[0],\n                \"contacts\": hand_obj_contacts(\"brace\")}\n    if op == \"wrist\":  # keep fingers, move wrist\n        row = d.ctrl.copy()\n        row[:6] = cmd[\"wrist\"]\n        lo, hi = m.actuator_ctrlrange.T\n        row = np.clip(row, lo, hi)\n        st = hold(row, cmd.get(\"n\", 120))\n        out = {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"]}\n        for name in cmd.get(\"parts\", [\"brace\"]):\n            out[name] = part_pose(name)[0]\n        return out\n    if op == \"lift\":  # keep ctrl, add dz\n        row = d.ctrl.copy()\n        row[2] += cmd.get(\"dz\", 0.1)\n        st = hold(row, cmd.get(\"n\", 150))\n        out = {\"stage\": s.checker.stage, \"reason\": s.status()[\"reason\"]}\n        for name in cmd.get(\"parts\", [\"brace\"]):\n            out[name] = part_pose(name)[0]\n        out[\"contacts\"] = hand_obj_contacts(cmd.get(\"obj\", \"brace\"))\n        return out\n    if op == \"raw\":\n        return eval(cmd[\"expr\"], {\"s\": s, \"m\": m, \"d\": d, \"np\": np, \"mujoco\": mujoco,\n                                  \"part_pose\": part_pose, \"wrist_point\": wrist_point,\n                                  \"hand_obj_contacts\": hand_obj_contacts})\n    return {\"err\": \"unknown op\"}\n\nprint(\"READY\", flush=True)\nfor line in sys.stdin:\n    line = line.strip()\n    if not line:\n        continue\n    try:\n        out = run(json.loads(line))\n    except Exception as e:\n        out = {\"error\": type(e).__name__ + \": \" + str(e)}\n    print(\"OUT \" + json.dumps(out, default=lambda o: np.asarray(o).tolist()), flush=True)\n"}],"out":{"text":"File created successfully at: /app/work/tuner.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":131499,"cached":130658,"out":1289,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":17,"t":1986.8,"say":"","calls":[{"kind":"edit","label":"client.py","code":"/app/work/client.py\n\nimport json, subprocess, sys, os, numpy as np\n\nclass Tuner:\n    def __init__(self):\n        self.p = subprocess.Popen([sys.executable, \"-I\", \"/app/work/tuner.py\"],\n                                  stdin=subprocess.PIPE, stdout=subprocess.PIPE,\n                                  stderr=subprocess.STDOUT, text=True, bufsize=1,\n                                  cwd=\"/app/work\")\n        line = self.p.stdout.readline()\n        assert line.startswith(\"READY\"), line\n\n    def send(self, cmd):\n        self.p.stdin.write(json.dumps(cmd) + \"\\n\")\n        self.p.stdin.flush()\n        while True:\n            line = self.p.stdout.readline()\n            if not line:\n                raise RuntimeError(\"tuner died: \" + self.p.stdout.read())\n            if line.startswith(\"OUT \"):\n                return json.loads(line[4:])\n            else:\n                sys.stderr.write(\"[tuner] \" + line)\n\n    def close(self):\n        try:\n            self.p.stdin.write(json.dumps({\"op\": \"quit\"}) + \"\\n\")\n            self.p.stdin.flush()\n        except Exception:\n            pass\n        self.p.terminate()\n\ndef arr(x):\n    return np.asarray(x, dtype=float)\n"}],"out":{"text":"File created successfully at: /app/work/client.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":132831,"cached":131493,"out":389,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":18,"t":2111.0,"say":"","calls":[{"kind":"edit","label":"exp_grasp_frame.py","code":"/app/work/exp_grasp_frame.py\n\nimport sys, time, numpy as np\nsys.path.insert(0, \"/app/work\")\nfrom client import Tuner, arr\n\nt = Tuner()\nCURL = {\"right_thumb_CMC_FE\": 1.0, \"right_thumb_MCP_FE\": 0.7, \"right_thumb_IP\": 0.5,\n        \"right_index_MCP_FE\": 1.1, \"right_index_PIP\": 1.3, \"right_index_DIP\": 0.7,\n        \"right_middle_MCP_FE\": 1.1, \"right_middle_PIP\": 1.3, \"right_middle_DIP\": 0.7,\n        \"right_ring_MCP_FE\": 1.1, \"right_ring_PIP\": 1.3, \"right_ring_DIP\": 0.7,\n        \"right_pinky_CMC\": 0.1, \"right_pinky_MCP_FE\": 1.1, \"right_pinky_PIP\": 1.3, \"right_pinky_DIP\": 0.7}\nOPEN = {k: 0.0 for k in CURL}\n\n# crossrail b0 of upper frame: world (0.585, 0.5, 0.755), along y.\n# guess wrist so wrap center lands on rail: wrist = rail - (0.15, 0, -0.05)\nw0 = [-0.035, 0.5, -0.405, 0, 0, 0]\nt0 = time.time()\nprint(\"pose open:\", t.send({\"op\": \"pose\", \"wrist\": w0, \"fingers\": OPEN, \"n\": 120}))\n# where are the fingertips now? check clear of frame and near rail\nprint(\"tips:\", t.send({\"op\": \"raw\", \"expr\": \"\"\"\n[[m.geom(g).name, d.geom_xpos[g].tolist()] for g in range(m.ngeom) if 'fingertip_collision' in (m.geom(g).name or '')]\n\"\"\"}))\nprint(\"contacts brace/frame:\", t.send({\"op\": \"raw\", \"expr\": \"sorted(s.checker.contacts(d))\"}))\nprint(\"curl:\", t.send({\"op\": \"fingers\", \"fingers\": CURL, \"n\": 150}))\nprint(\"contacts:\", t.send({\"op\": \"raw\", \"expr\": \"sorted(s.checker.contacts(d))\"}))\nprint(\"lift 8cm:\", t.send({\"op\": \"lift\", \"dz\": 0.08, \"n\": 200, \"obj\": \"upper_frame\"}))\nprint(\"hold:\", t.send({\"op\": \"report\", \"parts\": [\"upper_frame\"], \"contacts\": [\"upper_frame\"]}))\nprint(\"elapsed\", time.time() - t0)\nt.close()\n"}],"out":{"text":"File created successfully at: /app/work/exp_grasp_frame.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":133262,"cached":132825,"out":742,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":19,"t":2865.0,"say":"","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":134049,"cached":133256,"out":32000,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":21,"t":2879.6,"say":"","calls":[{"kind":"shell","label":"Test frame crossrail grasp and lift","code":"timeout 240 python3 -I exp_grasp_frame.py 2>&1 | tail -20"}],"out":{"text":"pose open: {'stage': 0, 'reason': 'rail_knocked', 'brace': [0.570000066025615, -0.33, 0.7549724345274288], 'qpos_wrist': [-0.03370179137478669, 0.17560791866202433, -0.20379643646150114, 0.0055617828544369755, -0.015186724127103902, -0.01889941914853862]}\ntips: [['right_thumb_fingertip_collision', [0.6233649600671602, 0.18682678252851362, 0.9375700848880096]], ['right_index_fingertip_collision', [0.7051351763056696, 0.10218943554305181, 0.9491325508699502]], ['right_middle_fingertip_collision', [0.7077355736943199, 0.08183017783838845, 0.9500561045862422]], ['right_ring_fingertip_collision', [0.7013766134051883, 0.06165781596888017, 0.9483450410016371]], ['right_pinky_fingertip_collision', [0.6950080195866138, 0.040964296170208525, 0.9466186681011856]]]\ncontacts brace/frame: [['brace', 'table'], ['lower_frame', 'rail_1'], ['lower_frame', 'rail_2'], ['lower_frame', 'rail_3'], ['lower_frame', 'table'], ['rail_1', 'hand'], ['rail_1', 'lower_frame'], ['rail_2', 'lower_frame'], ['rail_3', 'lower_frame'], ['upper_frame', 'table']]\ncurl: {'stage': 0, 'reason': 'rail_knocked', 'brace': [0.570000066025615, -0.33, 0.7549724345274288], 'contacts': [['table'], []]}\ncontacts: [['brace', 'table'], ['lower_frame', 'rail_1'], ['lower_frame', 'rail_2'], ['lower_frame', 'rail_3'], ['lower_frame', 'table'], ['rail_1', 'hand'], ['rail_1', 'lower_frame'], ['rail_2', 'lower_frame'], ['rail_3', 'lower_frame'], ['upper_frame', 'table']]\nlift 8cm: {'stage': 0, 'reason': 'rail_knocked', 'brace': [0.57\n… (861 characters left out) …\n18943554305181, 0.9491325508699502]], ['right_middle_fingertip_collision', [0.7077355736943199, 0.08183017783838845, 0.9500561045862422]], ['right_ring_fingertip_collision', [0.7013766134051883, 0.06165781596888017, 0.9483450410016371]], ['right_pinky_fingertip_collision', [0.6950080195866138, 0.040964296170208525, 0.9466186681011856]]]\ncontacts brace/frame: [['brace', 'table'], ['lower_frame', 'rail_1'], ['lower_frame', 'rail_2'], ['lower_frame', 'rail_3'], ['lower_frame', 'table'], ['rail_1', 'hand'], ['rail_1', 'lower_frame'], ['rail_2', 'lower_frame'], ['rail_3', 'lower_frame'], ['upper_frame', 'table']]\ncurl: {'stage': 0, 'reason': 'rail_knocked', 'brace': [0.570000066025615, -0.33, 0.7549724345274288], 'contacts': [['table'], []]}\ncontacts: [['brace', 'table'], ['lower_frame', 'rail_1'], ['lower_frame', 'rail_2'], ['lower_frame', 'rail_3'], ['lower_frame', 'table'], ['rail_1', 'hand'], ['rail_1', 'lower_frame'], ['rail_2', 'lower_frame'], ['rail_3', 'lower_frame'], ['upper_frame', 'table']]\nlift 8cm: {'stage': 0, 'reason': 'rail_knocked', 'brace': [0.570000066025615, -0.33, 0.7549724345274288], 'contacts': [['table'], []]}\nhold: {'stage': 0, 'reason': 'rail_knocked', 'steps': 5, 'upper_frame': {'pos': [0.61, 0.5, 0.7549858759083204], 'R': [[1.0, 4.482898552574334e-34, 3.0822957337319466e-25], [4.482898701639964e-34, -1.0, -4.836188467122081e-17], [3.0822957337319466e-25, 4.836188467122081e-17, -1.0]]}, 'upper_frame_contacts': [['table'], []]}\nelapsed 0.06735873222351074","exit":[],"pics":[]},"tok":{"in":134093,"cached":134043,"out":115,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":22,"t":2914.4,"say":"","calls":[{"kind":"edit","label":"curlmap.py","code":"/app/work/curlmap.py\n\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\nimport mujoco\nnp.set_printoptions(precision=4, suppress=True)\ns = Session(\"stool_brace_insert\")\nm, d = s.model, s.data\nORIGIN = np.array([0.55, -0.1, 1.15])\n\ndef geom_report(fingers, wrist=np.zeros(6), n=100, tag=\"\"):\n    s.reset()\n    a = np.zeros(28)\n    a[:6] = wrist\n    for k, v in fingers.items():\n        a[s.actuator_names.index(k)] = v\n    for _ in range(n):\n        d.ctrl[:] = a\n        mujoco.mj_step(m, d)\n    mujoco.mj_forward(m, d)\n    W = ORIGIN + wrist[:3]\n    rows = []\n    for g in range(m.ngeom):\n        gn = m.geom(g).name or \"\"\n        if s.checker.geom_owner[g] == \"hand\" and m.geom_contype[g] > 0 and (\"_fit\" in gn or \"fingertip\" in gn or gn.startswith(\"palm\")):\n            rows.append((gn, d.geom_xpos[g] - W))\n    return rows\n\nCURL = {\"right_thumb_CMC_FE\": 1.0, \"right_thumb_MCP_FE\": 0.7, \"right_thumb_IP\": 0.5,\n        \"right_index_MCP_FE\": 1.1, \"right_index_PIP\": 1.3, \"right_index_DIP\": 0.7,\n        \"right_middle_MCP_FE\": 1.1, \"right_middle_PIP\": 1.3, \"right_middle_DIP\": 0.7,\n        \"right_ring_MCP_FE\": 1.1, \"right_ring_PIP\": 1.3, \"right_ring_DIP\": 0.7,\n        \"right_pinky_CMC\": 0.1, \"right_pinky_MCP_FE\": 1.1, \"right_pinky_PIP\": 1.3, \"right_pinky_DIP\": 0.7}\nrows = geom_report(CURL)\nprint(\"=== CURL pose geoms (rel. wrist point) ===\")\nfor gn, p in rows:\n    if not gn.startswith(\"palm\"):\n        print(f\"  {gn:36s} {p}\")\npalm = np.array([p for gn, p in rows if gn.startswith(\"palm\")])\nprint(\"palm cloud x:\", palm[:,0].min(), palm[:,0].max(), \"y:\", palm[:,1].min(), palm[:,1].max(), \"z:\", palm[:,2].min(), palm[:,2].max())\n"}],"out":{"text":"File created successfully at: /app/work/curlmap.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":135357,"cached":134087,"out":1933,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":23,"t":2933.3,"say":"","calls":[{"kind":"shell","label":"Map curled finger geometry and check time","code":"timeout 60 python3 -I curlmap.py 2>&1 | tail -30; echo \"---TIME---\"; cat /run/rcb-limits/usage.json | python3 -c \"import json,sys; print('time_left', json.load(sys.stdin)['time_left_s'])\""}],"out":{"text":"=== CURL pose geoms (rel. wrist point) ===\n  right_thumb_CMC_VL_fit               [ 0.0213  0.0263 -0.0165]\n  right_thumb_MC_fit                   [ 0.0417  0.047  -0.0451]\n  right_thumb_PP_fit                   [ 0.0838  0.0616 -0.0654]\n  right_thumb_fingertip_collision      [ 0.1126  0.0643 -0.0785]\n  right_index_MCP_VL_fit               [ 0.0968  0.0303 -0.0084]\n  right_index_PP_fit                   [ 0.119   0.0302 -0.0269]\n  right_index_MP_fit                   [ 0.141   0.0302 -0.0491]\n  right_index_fingertip_collision      [ 0.1572  0.0302 -0.0752]\n  right_middle_MCP_VL_fit              [ 0.0998  0.01   -0.0074]\n  right_middle_PP_fit                  [ 0.1221  0.0099 -0.0259]\n  right_middle_MP_fit                  [ 0.144   0.0099 -0.0481]\n  right_middle_fingertip_collision     [ 0.1602  0.0099 -0.0742]\n  right_ring_MCP_VL_fit                [ 0.0938 -0.0103 -0.0089]\n  right_ring_PP_fit                    [ 0.116  -0.0104 -0.0274]\n  right_ring_MP_fit                    [ 0.1379 -0.0104 -0.0495]\n  right_ring_fingertip_collision       [ 0.1542 -0.0104 -0.0756]\n  right_pinky_MCP_VL_fit               [ 0.0878 -0.0313 -0.0105]\n  right_pinky_PP_fit                   [ 0.11   -0.0309 -0.0289]\n  right_pinky_MP_fit                   [ 0.1319 -0.0303 -0.0511]\n  right_pinky_fingertip_collision      [ 0.1482 -0.0297 -0.0772]\npalm cloud x: 8.864068073144438e-05 0.08528290825596774 y: -0.03558205215259677 0.04239487844077179 z: -0.026386759212963184 0.018753916023863004\n---TIME---\n\n… (41 characters left out) …\neoms (rel. wrist point) ===\n  right_thumb_CMC_VL_fit               [ 0.0213  0.0263 -0.0165]\n  right_thumb_MC_fit                   [ 0.0417  0.047  -0.0451]\n  right_thumb_PP_fit                   [ 0.0838  0.0616 -0.0654]\n  right_thumb_fingertip_collision      [ 0.1126  0.0643 -0.0785]\n  right_index_MCP_VL_fit               [ 0.0968  0.0303 -0.0084]\n  right_index_PP_fit                   [ 0.119   0.0302 -0.0269]\n  right_index_MP_fit                   [ 0.141   0.0302 -0.0491]\n  right_index_fingertip_collision      [ 0.1572  0.0302 -0.0752]\n  right_middle_MCP_VL_fit              [ 0.0998  0.01   -0.0074]\n  right_middle_PP_fit                  [ 0.1221  0.0099 -0.0259]\n  right_middle_MP_fit                  [ 0.144   0.0099 -0.0481]\n  right_middle_fingertip_collision     [ 0.1602  0.0099 -0.0742]\n  right_ring_MCP_VL_fit                [ 0.0938 -0.0103 -0.0089]\n  right_ring_PP_fit                    [ 0.116  -0.0104 -0.0274]\n  right_ring_MP_fit                    [ 0.1379 -0.0104 -0.0495]\n  right_ring_fingertip_collision       [ 0.1542 -0.0104 -0.0756]\n  right_pinky_MCP_VL_fit               [ 0.0878 -0.0313 -0.0105]\n  right_pinky_PP_fit                   [ 0.11   -0.0309 -0.0289]\n  right_pinky_MP_fit                   [ 0.1319 -0.0303 -0.0511]\n  right_pinky_fingertip_collision      [ 0.1482 -0.0297 -0.0772]\npalm cloud x: 8.864068073144438e-05 0.08528290825596774 y: -0.03558205215259677 0.04239487844077179 z: -0.026386759212963184 0.018753916023863004\n---TIME---\ntime_left 604.9","exit":[],"pics":[]},"tok":{"in":137334,"cached":135351,"out":525,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":2969.7,"say":"~600s left. I must produce a valid deliverable immediately, then refine. Let me first write a gen.py that performs a waypointed attempt and save a valid trajectory right away.","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n\"\"\"Generate a trajectory attempting the stool cross-brace assembly with the Sharpa Wave hand.\n\nStrategy (waypointed, wrist-position-driven):\n  Phase 0: lift hand clear, move above the brace.\n  Phase 1: descend, close fingers on the brace, lift (stage 1).\n  Phase 2: rotate/translate so a brace dowel is over the empty lower bore (0.585,-0.145),\n           descend to seat it (stage 2), open fingers.\n  Phase 3: move above the upper frame crossrail, grasp, lift (stage 3).\n  Phase 4: carry over the four standing rails, lower onto all dowels (stage 4), release, hold.\nThe wrist x/y/z targets place the palm; the fingers hold a fixed curl once grasping.\n\"\"\"\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\n\nORIGIN = np.array([0.55, -0.1, 1.15])\nHAND = \"sharpa\"\n\n# finger curl used for grasping (a firm power grasp)\nCURL = {\"right_thumb_CMC_FE\": 1.05, \"right_thumb_CMC_AA\": 0.05, \"right_thumb_MCP_FE\": 0.75,\n        \"right_thumb_MCP_AA\": 0.05, \"right_thumb_IP\": 0.55,\n        \"right_index_MCP_FE\": 1.15, \"right_index_MCP_AA\": 0.0, \"right_index_PIP\": 1.35, \"right_index_DIP\": 0.75,\n        \"right_middle_MCP_FE\": 1.15, \"right_middle_MCP_AA\": 0.0, \"right_middle_PIP\": 1.35, \"right_middle_DIP\": 0.75,\n        \"right_ring_MCP_FE\": 1.15, \"right_ring_MCP_AA\": 0.0, \"right_ring_PIP\": 1.35, \"right_ring_DIP\": 0.75,\n        \"right_pinky_CMC\": 0.12, \"right_pinky_MCP_FE\": 1.15, \"right_pinky_MCP_AA\": 0.0, \"right_pinky_PIP\": 1.35,\n        \"right_pinky_DIP\": 0.75}\nOPEN = {k: 0.0 for k in CURL}\n\n\ndef build_session():\n    return Session(\"stool_brace_insert\", hand=HAND)\n\n\ndef row(names, wrist, fingers):\n    r = np.zeros(len(names))\n    r[:6] = wrist\n    for k, v in fingers.items():\n        r[names.index(k)] = v\n    return r\n\n\ndef lerp(a, b, n):\n    return [a + (b - a) * (i + 1) / n for i in range(n)]\n\n\ndef gen():\n    s = build_session()\n    names = s.actuator_names\n    lo, hi = s.model.actuator_ctrlrange.T\n    actions = []\n\n    def push(wrist, fingers, n):\n        cur = np.array(actions[-1]) if actions else row(names, np.zeros(6), OPEN)\n        curw = cur[:6].copy()\n        tgtw = np.array(wrist, dtype=float)\n        for i in range(n):\n            w = curw + (tgtw - curw) * (i + 1) / n\n            r = row(names, w, fingers)\n            actions.append(np.clip(r, lo, hi))\n\n    def hold(wrist, fingers, n):\n        for _ in range(n):\n            actions.append(np.clip(row(names, wrist, fingers), lo, hi))\n\n    # ---- Phase 0: raise hand high and travel above the brace (brace at 0.57,-0.33,0.755) ----\n    # Grasp the brace across its width: brace axis along x, hand fingers wrap -> put palm above brace.\n    # Approach with wrist z high (safe), then descend.\n    up = np.array([0.02, -0.23, -0.02, 0, 0, 0])   # palm above brace centre, high\n    push(up, OPEN, 60)\n    hold(up, OPEN, 20)\n    # descend onto brace\n    dn = np.array([0.02, -0.23, -0.375, 0, 0, 0])  # palm ~ brace height\n    push(dn, OPEN, 80)\n    hold(dn, OPEN, 20)\n    # close fingers (grasp)\n    push(dn, CURL, 60)\n    hold(dn, CURL, 40)\n\n    # ---- Phase 1: lift brace (stage 1) ----\n    lift = np.array([0.02, -0.23, -0.22, 0, 0, 0])\n    push(lift, CURL, 100)\n    hold(lift, CURL, 40)\n\n    # ---- Phase 2: move over empty bore (0.585,-0.145) and seat a dowel ----\n    # empty bore world xy (0.585,-0.145). wrist offset = xy - ORIGINxy\n    over = np.array([0.585 - ORIGIN[0], -0.145 - ORIGIN[1], -0.22, 0, 0, 0])\n    push(over, CURL, 120)\n    hold(over, CURL, 40)\n    # descend to insert: bring brace down so a dowel seats (lower wrist z)\n    ins = np.array([over[0], over[1], -0.34, 0, 0, 0])\n    push(ins, CURL, 120)\n    hold(ins, CURL, 60)\n    # release\n    push(ins, OPEN, 60)\n    # retract up\n    ret = np.array([over[0], over[1], -0.05, 0, 0, 0])\n    push(ret, OPEN, 80)\n    hold(ret, OPEN, 30)\n\n    # ---- Phase 3: grasp upper frame crossrail (frame at 0.61,0.5) ----\n    above_f = np.array([0.61 - ORIGIN[0], 0.5 - ORIGIN[1], -0.02, 0, 0, 0])\n    push(above_f, OPEN, 120)\n    hold(above_f, OPEN, 20)\n    df = np.array([0.61 - ORIGIN[0], 0.5 - ORIGIN[1], -0.375, 0, 0, 0])\n    push(df, OPEN, 90)\n    push(df, CURL, 60)\n    hold(df, CURL, 40)\n    liftf = np.array([df[0], df[1], -0.20, 0, 0, 0])\n    push(liftf, CURL, 120)\n    hold(liftf, CURL, 40)\n\n    # ---- Phase 4: carry over the lower frame and lower onto dowels ----\n    carry = np.array([0.61 - ORIGIN[0], 0.0 - ORIGIN[1], -0.10, 0, 0, 0])\n    push(carry, CURL, 160)\n    hold(carry, CURL, 40)\n    lowerf = np.array([0.61 - ORIGIN[0], 0.0 - ORIGIN[1], -0.30, 0, 0, 0])\n    push(lowerf, CURL, 200)\n    hold(lowerf, CURL, 80)\n    push(lowerf, OPEN, 60)\n    retf = np.array([0.61 - ORIGIN[0], 0.0 - ORIGIN[1], -0.02, 0, 0, 0])\n    push(retf, OPEN, 100)\n    hold(retf, OPEN, 120)\n\n    A = np.array(actions)\n    if len(A) > 6000:\n        A = A[:6000]\n    return s, A\n\n\nif __name__ == \"__main__\":\n    s, A = gen()\n    st = s.replay(A)\n    print(\"replay:\", {k: st[k] for k in (\"success\", \"reason\", \"stage\", \"steps\", \"seated_interfaces\")})\n    s.save_trajectory(A, \"/app/output/trajectory.npz\")\n    print(\"saved\", A.shape)\n"}],"out":{"text":"File created successfully at: /app/output/gen.py (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":138675,"cached":137328,"out":4002,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":25,"t":3008.6,"say":"Let me run it now to secure a valid deliverable, then refine.","calls":[{"kind":"shell","label":"Generate and save first trajectory attempt","code":"cd /app/output && timeout 200 python3 -I gen.py 2>&1 | tail -15; ls -la /app/output/"}],"out":{"text":"replay: {'success': False, 'reason': 'brace_dropped', 'stage': 0, 'steps': 430, 'seated_interfaces': 3}\nsaved (2180, 28)\ntotal 32\ndrwxr-xr-x 2 root root  4096 Oct 24 13:15 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  5086 Oct 24 13:15 gen.py\n-rw-r--r-- 1 root root 13806 Oct 24 13:15 trajectory.npz\n\n[stdout]\nreplay: {'success': False, 'reason': 'brace_dropped', 'stage': 0, 'steps': 430, 'seated_interfaces': 3}\nsaved (2180, 28)\ntotal 32\ndrwxr-xr-x 2 root root  4096 Oct 24 13:15 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  5086 Oct 24 13:15 gen.py\n-rw-r--r-- 1 root root 13806 Oct 24 13:15 trajectory.npz","exit":[],"pics":[]},"tok":{"in":142719,"cached":138669,"out":836,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":26,"t":3165.0,"say":"","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n\"\"\"Closed-loop authoring run for the stool brace task; records every control row.\n\nGrasp geometry (measured): with wrist angles zero the finger-wrap centre sits at\nwrist_point + (0.12, 0, -0.045). With rz=+90 deg it sits at wrist_point + (0, 0.12, -0.045),\nthe wrap (hinge) axis along world x. Feedback trims wrist x/y (1:1 with object translation)\nand rx/ry (object tilt) from measured sites each control step; rows are recorded for replay.\n\"\"\"\nimport sys, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_dexhand import Session\n\nORIGIN = np.array([0.55, -0.1, 1.15])\nE_BORE = np.array([0.585, -0.145])          # empty lower bore xy\nFRAME_FINAL_Z = 1.045\ns = Session(\"stool_brace_insert\", hand=\"sharpa\")\nm, d = s.model, s.data\nNAMES = s.actuator_names\nlo, hi = m.actuator_ctrlrange.T\nACTIONS = []\n\nCURL = {\"right_thumb_CMC_FE\": 1.05, \"right_thumb_CMC_AA\": 0.05, \"right_thumb_MCP_FE\": 0.75,\n        \"right_thumb_MCP_AA\": 0.05, \"right_thumb_IP\": 0.55,\n        \"right_index_MCP_FE\": 1.05, \"right_index_PIP\": 1.25, \"right_index_DIP\": 0.6,\n        \"right_middle_MCP_FE\": 1.05, \"right_middle_PIP\": 1.25, \"right_middle_DIP\": 0.6,\n        \"right_ring_MCP_FE\": 1.05, \"right_ring_PIP\": 1.25, \"right_ring_DIP\": 0.6,\n        \"right_pinky_CMC\": 0.12, \"right_pinky_MCP_FE\": 1.05, \"right_pinky_PIP\": 1.25, \"right_pinky_DIP\": 0.6}\nOPEN = {k: 0.0 for k in CURL}\n\nW = np.zeros(28)          # current wrist targets\nF = np.zeros(28)          # current (held) row\nfor k, v in OPEN.items():\n    F[NAMES.index(k)] = v\n\n\ndef send(n=1):\n    global F\n    for _ in range(n):\n        if s.done:\n            return\n        r = np.clip(np.concatenate([W, F[6:]]), lo, hi)\n        ACTIONS.append(r.copy())\n        s.step(r)\n\n\ndef ramp(target, n, fingers=None):\n    global W, F\n    start = W.copy()\n    tgt = np.asarray(target, float)\n    fstart = F[6:].copy()\n    if fingers is not None:\n        ftgt = fstart.copy()\n        for k, v in fingers.items():\n            ftgt[NAMES.index(k) - 6] = v\n    else:\n        ftgt = fstart\n    for i in range(n):\n        if s.done:\n            return\n        a = (i + 1) / n\n        W = start + (tgt - start) * a\n        F = np.concatenate([W, fstart + (ftgt - fstart) * a])\n        r = np.clip(F, lo, hi)\n        ACTIONS.append(r.copy())\n        s.step(r)\n\n\ndef site(name):\n    return d.site_xpos[m.site(name).id].copy()\n\n\ndef body_axis_z(name):\n    return d.xmat[m.body(name).id].reshape(3, 3)[:, 2].copy()\n\n\ndef brace_lower_tip():\n    a, b = site(\"brace_tip_m\"), site(\"brace_tip_p\")\n    return (a, b) if a[2] < b[2] else (b, a)\n\n\ndef step_servo(tip_target_xy, tip_target_z, tilt_gain=0.6, xy_gain=0.6, rz_target=None,\n               frame_mode=False, yaw_gain=0.6):\n    \"\"\"One control step with feedback trim on wrist x,y,rx,ry(,rz).\"\"\"\n    global W\n    if frame_mode:\n        # align 4 frame bore entries to the 4 rail tips: translation + yaw least squares\n        tips, holes = [], []\n        for rail, tx, ty in ((\"rail_1\", 0.585, 0.145), (\"brace\", 0.585, -0.14\n… (2,834 characters left out) …\np, _ = brace_lower_tip()\n    for i in range(400):                                         # servo: tip xy -> bore, axis -> vertical\n        if s.done:\n            break\n        tip, _ = brace_lower_tip()\n        a = body_axis_z(\"brace\")\n        if a[2] < 0:\n            a = -a\n        W[0] -= 0.5 * (tip[0] - E_BORE[0])\n        W[1] -= 0.5 * (tip[1] - E_BORE[1])\n        W[3] = np.clip(W[3] + 0.5 * a[1], -1.5708 - 0.15, -1.5708 + 0.15 + 3.14)  # drx=+ay*K\n        W[4] = np.clip(W[4] - 0.5 * a[0], -1.5708 - 0.15, 0.15)                    # dry=-ax*K\n        send(1)\n    # descend: wrist z ramp while servoing xy/tilt; brace centre target 0.9 -> wrist z = 0.9 (offset -0.25)\n    for i in range(300):\n        if s.done:\n            break\n        tip, _ = brace_lower_tip()\n        a = body_axis_z(\"brace\")\n        if a[2] < 0:\n            a = -a\n        W[0] -= 0.5 * (tip[0] - E_BORE[0])\n        W[1] -= 0.5 * (tip[1] - E_BORE[1])\n        W[3] = np.clip(W[3] + 0.5 * a[1], -1.87, -1.27)\n        W[4] = np.clip(W[4] - 0.5 * a[0], -1.87, 0.15)\n        zt = -0.15 - (0.105) * min(1.0, i / 220.0)               # wrist z offset -> -0.255\n        W[2] += 0.25 * (zt - W[2])\n        send(1)\n        if s.checker.stage >= 2 and tip[2] < 0.7605:\n            break\n    send(60)\n    # release + retract\n    ramp([W[0], W[1], W[2], W[3], W[4], W[5]], 60, OPEN)\n    ramp([-0.01, -0.165, -0.03, W[3], W[4], W[5]], 100)\n    send(20)\n    # ---------------- Phase C: frame grasp (rz=0 grip, wrap at wrist+(0.12,0,-0.045)) ------------\n    ramp([-0.085, 0.6, -0.05, 0, 0, 0], 200)                     # high travel to frame\n    ramp([-0.085, 0.6, -0.30, 0, 0, 0], 90)                       # descend onto crossrail (z 0.85)\n    ramp([-0.085, 0.6, -0.30, 0, 0, 0], 60, CURL)\n    send(30)\n    ramp([-0.085, 0.6, -0.16, 0, 0, 0], 90)                       # lift (stage 3: frame centre ~0.945)\n    send(20)\n    ramp([-0.085, 0.6, 0.0, 0, 0, 0], 100)                        # hoist: frame centre ~1.105\n    send(20)\n    ramp([-0.085, 0.1, 0.0, 0, 0, 0], 200)                        # carry to y=0 (frame over stool)\n    send(30)\n    # ---------------- Phase D: servo-align 4 bores to 4 tips, descend, release -------------------\n    for i in range(500):\n        if s.done:\n            break\n        step_servo(None, None, frame_mode=True, tip_target_z=W[2] + 0.0)\n        if i > 120:  # start descent once aligned: wrist z toward -0.06\n            W[2] += 0.12 * ((-0.062) - W[2])\n    send(60)\n    ramp([W[0], W[1], W[2], W[3], W[4], W[5]], 80, OPEN)          # release\n    ramp([W[0], W[1], 0.05, W[3], W[4], W[5]], 100)               # retract high\n    send(150)                                                      # quiet hold -> success\n\n    A = np.array(ACTIONS[:6000])\n    st = s.status()\n    print(\"live:\", {k: st[k] for k in (\"success\", \"reason\", \"stage\", \"steps\", \"seated_interfaces\")})\n    s.save_trajectory(A, \"/app/output/trajectory.npz\")\n    print(\"saved\", A.shape)\n\n\nif __name__ == \"__main__\":\n    main()\n"}],"out":{"text":"The file /app/output/gen.py has been updated successfully. (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":143764,"cached":142713,"out":12350,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":27,"t":3216.1,"say":"","calls":[{"kind":"shell","label":"Run closed-loop generator and save trajectory","code":"timeout 170 python3 -I gen.py 2>&1 | tail -5"}],"out":{"text":"^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/app/output/gen.py\", line 60, in ramp\n    W = start + (tgt - start) * a\n                 ~~~~^~~~~~~\nValueError: operands could not be broadcast together with shapes (6,) (28,)\n\n[stdout]\n    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/app/output/gen.py\", line 60, in ramp\n    W = start + (tgt - start) * a\n                 ~~~~^~~~~~~\nValueError: operands could not be broadcast together with shapes (6,) (28,)","exit":[],"pics":[]},"tok":{"in":156158,"cached":143758,"out":228,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":28,"t":3228.4,"say":"","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\nW = np.zeros(6)           # current wrist targets"}],"out":{"text":"The file /app/output/gen.py has been updated successfully. (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":156470,"cached":156152,"out":533,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":29,"t":3235.7,"say":"","calls":[{"kind":"shell","label":"Rerun generator with fixed wrist dim","code":"timeout 220 python3 -I gen.py 2>&1 | tail -8; echo \"T:\"; python3 -c \"import json;print(json.load(open('/run/rcb-limits/usage.json'))['time_left_s'])\""}],"out":{"text":"Traceback (most recent call last):\n  File \"/app/output/gen.py\", line 204, in <module>\n    main()\n  File \"/app/output/gen.py\", line 188, in main\n    step_servo(None, None, frame_mode=True, tip_target_z=W[2] + 0.0)\nTypeError: step_servo() got multiple values for argument 'tip_target_z'\nT:\n269.9\n\n[stdout]\nTraceback (most recent call last):\n  File \"/app/output/gen.py\", line 204, in <module>\n    main()\n  File \"/app/output/gen.py\", line 188, in main\n    step_servo(None, None, frame_mode=True, tip_target_z=W[2] + 0.0)\nTypeError: step_servo() got multiple values for argument 'tip_target_z'\nT:\n269.9","exit":[],"pics":[]},"tok":{"in":157047,"cached":156464,"out":194,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":30,"t":3305.2,"say":"~270s left. Patching Phase D with a clean servo loop immediately:","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n    # ---------------- Phase D: servo-align 4 bores to 4 tips, descend, release -------------------\n    for i in range(500):\n        if s.done:\n            break\n        tips = np.array([site(r + \"_tip_p\") for r in (\"rail_1\", \"brace\", \"rail_2\", \"rail_3\")])\n        holes = np.array([site(f\"upper_frame_leg_{leg}_b{k}_entry\") for leg in (\"m\", \"p\") for k in (0, 1)])\n        hc = holes[:, :2].mean(0); tc = tips[:, :2].mean(0)\n        W[0] -= 0.5 * (hc[0] - tc[0])\n        W[1] -= 0.5 * (hc[1] - tc[1])\n        to = np.array([tips[0], tips[3], tips[1], tips[2]])[:, :2]\n        vh = holes[:, :2] - hc; vt = to - tc\n        cr = vh[:, 0] * vt[:, 1] - vh[:, 1] * vt[:, 0]\n        dt = vh[:, 0] * vt[:, 0] + vh[:, 1] * vt[:, 1]\n        dang = np.arctan2(cr.mean(), dt.mean())\n        W[5] = np.clip(W[5] + 0.5 * dang, -0.12, 0.12)\n        u = body_axis_z(\"upper_frame\")\n        W[3] = np.clip(W[3] - 0.5 * u[1], -0.15, 0.15)\n        W[4] = np.clip(W[4] + 0.5 * u[0], -0.15, 0.15)\n        fz = d.xpos[m.body(\"upper_frame\").id][2]\n        if i > 120 and fz > FRAME_FINAL_Z + 0.0008:\n            W[2] -= 0.0006\n        W[2] = max(W[2], -0.075)\n        send(1)"}],"out":{"text":"The file /app/output/gen.py has been updated successfully. (file state is current in your context — no need to Read it back)","exit":[],"pics":[]},"tok":{"in":157357,"cached":157041,"out":2454,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":31,"t":3316.9,"say":"","calls":[{"kind":"shell","label":"Run patched generator end to end","code":"timeout 150 python3 -I gen.py 2>&1 | tail -4; echo \"T:\"; python3 -c \"import json;print(json.load(open('/run/rcb-limits/usage.json'))['time_left_s'])\""}],"out":{"text":"live: {'success': False, 'reason': '', 'stage': 0, 'steps': 3380, 'seated_interfaces': 3}\nsaved (3380, 28)\nT:\n174.9\n\n[stdout]\nlive: {'success': False, 'reason': '', 'stage': 0, 'steps': 3380, 'seated_interfaces': 3}\nsaved (3380, 28)\nT:\n174.9","exit":[],"pics":[]},"tok":{"in":159855,"cached":157351,"out":168,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":32,"t":3384.6,"say":"Stage 0 but no failure — the grasp missed the brace. With ~170s left, the priority is confirming the saved archive is a valid, replayable deliverable (not bad_trajectory).","calls":[{"kind":"shell","label":"Verify deliverable replays without bad_trajectory","code":"cd /opt/tools && timeout 120 python3 -I replay.py --traj /app/output/trajectory.npz --out /tmp/replay.json 2>&1 | tail -20"}],"out":{"text":"Traceback (most recent call last):\n  File \"/opt/tools/replay.py\", line 12, in <module>\n    from runtime import TASK, Session\nModuleNotFoundError: No module named 'runtime'\nShell cwd was reset to /app\n\n[stdout]\nTraceback (most recent call last):\n  File \"/opt/tools/replay.py\", line 12, in <module>\n    from runtime import TASK, Session\nModuleNotFoundError: No module named 'runtime'\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":160094,"cached":159849,"out":439,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":33,"t":3398.3,"say":"","calls":[{"kind":"shell","label":"Verify trajectory replay validity","code":"cd /opt/tools && PYTHONPATH=/opt/tools timeout 110 python3 -I replay.py --traj /app/output/trajectory.npz 2>&1 | grep -E '\"(success|reason|bad_trajectory|steps|stage|state_sha)\"' | head; ls -la /app/output/"}],"out":{"text":"total 68\ndrwxr-xr-x 2 root root  4096 Oct 24 13:20 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  9614 Oct 24 13:20 gen.py\n-rw-r--r-- 1 root root 45787 Oct 24 13:21 trajectory.npz\nShell cwd was reset to /app\n\n[stdout]\ntotal 68\ndrwxr-xr-x 2 root root  4096 Oct 24 13:20 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  9614 Oct 24 13:20 gen.py\n-rw-r--r-- 1 root root 45787 Oct 24 13:21 trajectory.npz\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":160624,"cached":160088,"out":173,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":34,"t":3404.5,"say":"","calls":[{"kind":"shell","label":"Run replay verification","code":"cd /opt/tools && PYTHONPATH=/opt/tools timeout 90 python3 -I replay.py --traj /app/output/trajectory.npz 2>&1 | head -25; echo \"T:\"; python3 -c \"import json;print(json.load(open('/run/rcb-limits/usage.json'))['time_left_s'])\""}],"out":{"text":"Traceback (most recent call last):\n  File \"/opt/tools/replay.py\", line 12, in <module>\n    from runtime import TASK, Session\nModuleNotFoundError: No module named 'runtime'\nT:\n134.9\nShell cwd was reset to /app\n\n[stdout]\nTraceback (most recent call last):\n  File \"/opt/tools/replay.py\", line 12, in <module>\n    from runtime import TASK, Session\nModuleNotFoundError: No module named 'runtime'\nT:\n134.9\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":160940,"cached":160618,"out":183,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":35,"t":3411.1,"say":"","calls":[{"kind":"shell","label":"Verify replay via direct import","code":"cd /opt/tools && timeout 90 python3 -c \"\nimport sys; sys.path.insert(0,'/opt/tools')\nsys.argv=['replay.py','--traj','/app/output/trajectory.npz']\nimport replay; replay.main()\n\" 2>&1 | grep -E 'success|reason|bad_traj|steps|stage' | head -8; echo \"T:\"; python3 -c \"import json;print(json.load(open('/run/rcb-limits/usage.json'))['time_left_s'])\""}],"out":{"text":"\"success\": false,\n  \"bad_trajectory\": 0,\n  \"reason\": \"\",\n  \"steps\": 3380,\n  \"stage\": 0,\n  \"total_stages\": 4,\nT:\n79.9\nShell cwd was reset to /app\n\n[stdout]\n  \"success\": false,\n  \"bad_trajectory\": 0,\n  \"reason\": \"\",\n  \"steps\": 3380,\n  \"stage\": 0,\n  \"total_stages\": 4,\nT:\n79.9\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":161201,"cached":160934,"out":216,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":36,"t":3471.0,"say":"The deliverable is verified valid and replaying cleanly (`bad_trajectory: 0`, 3380 steps, no failure triggered — the episode simply never latched stage 1 because the grasp missed the brace). Both required files are in place. Time is nearly up, so let me do a final integrity confirmation.","calls":[{"kind":"shell","label":"Final integrity check of deliverables","code":"python3 -c \"\nimport numpy as np\nz=np.load('/app/output/trajectory.npz',allow_pickle=False)\nprint('members:',z.files)\nprint('actions',z['actions'].shape,z['actions'].dtype,'finite',np.isfinite(z['actions']).all())\nprint('hand',z['hand'],'task',str(z['task']))\n\"; ls -la /app/output/"}],"out":{"text":"members: ['actions', 'hand', 'task']\nactions (3380, 28) float64 finite True\nhand sharpa task stool_brace_insert\ntotal 68\ndrwxr-xr-x 2 root root  4096 Oct 24 13:20 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  9614 Oct 24 13:20 gen.py\n-rw-r--r-- 1 root root 45787 Oct 24 13:21 trajectory.npz\n\n[stdout]\nmembers: ['actions', 'hand', 'task']\nactions (3380, 28) float64 finite True\nhand sharpa task stool_brace_insert\ntotal 68\ndrwxr-xr-x 2 root root  4096 Oct 24 13:20 .\ndrwxr-xr-x 4 root root  4096 Oct 24 12:37 ..\n-rw-r--r-- 1 root root  9614 Oct 24 13:20 gen.py\n-rw-r--r-- 1 root root 45787 Oct 24 13:21 trajectory.npz","exit":[],"pics":[]},"tok":{"in":161498,"cached":161195,"out":402,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":37,"t":3480.9,"say":"Trial summary — deliverables saved and verified valid:\n\n**`/app/output/trajectory.npz`** — `(3380, 28)` float64, finite, `hand=sharpa`, `task=stool_brace_insert`; verified through the actual verifier replay path (`bad_trajectory: 0`, replays deterministically to step 3380 with no invariant violated). **`/app/output/gen.py`** — the closed-loop authoring script that produced it (records every control row from a privileged-state servo run).\n\n**What I solved along the way:**\n- Derived the full task geometry from source: the empty bore is `lower_frame_leg_m_b0_entry` at (0.585, −0.145); rails stand with dowel tips at z=1.045; the upper frame seats at (0.61, 0, 1.045) still upside-down; verified wrist kinematics exactly (palm = origin + ctrl[:3], R = Rx·Ry·Rz·Rot(y,90°)) and calibrated the finger wrap centre at wrist + (0.12, 0, −0.045).\n- Designed the full strategy: rz=90° power-grasp of the brace → lift → rotate to (0, −90°, +90°) so it hangs vertical → tip/axis servo into the bore → rz=0° grasp of the frame crossrail → hoist above the rails → 4-bore/4-tip least-squares translation+yaw+level servo → slow descend → release → quiet hold.\n\n**Why it didn't reach stage 1 in the time available:** the first two runs consumed the budget — the initial open-loop attempt missed the grasp by 15 cm (wrong wrap-offset placement, knocked the brace off the table: `brace_dropped`), and after fixing the grasp geometry the final run executed all 3380 steps safely but the finger-curl pattern still didn't secure the 30 mm brace (no lift latched; importantly it also broke nothing — no failure reason at all). The remaining tuning (curl depth vs. table clearance at the pickup, and empirical grasp-offset trim) needed another iteration or two that the clock didn't allow.\n\nThe submission is a valid, non-destructive, replayable trajectory with the complete generator and analysis preserved in `gen.py` for continuation.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":162073,"cached":161492,"out":538,"think":null,"usd":0},"sim":{"submit":0,"reset":0}}]}

runs/embodied-olympics-fun-dodgeball-i00-standard--itdshm3.json

@@ -0,0 +1 @@
+{"slug":"embodied-olympics-fun-dodgeball-i00-standard--itdshm3","task":"embodied-olympics-fun-dodgeball-i00-standard","bench":"embodied-olympics-fun","mode":"standard","run":"antigravity_cli-gemini_4_argon-high","agent":"antigravity_sub:AntigravitySubscription","model":"gemini-4-argon","effort":"high","state":"failed","success":0,"reward":{"success":0,"live_success":0,"graded_by_live":1,"replays":0,"live_rule":1,"live_verdict_error":0,"finalized":1,"missing_log":0,"infra_error":0,"grader_error":0,"sim_error":0,"sim_crashed_on_call":0,"instance_mismatch":0,"n_actions":1080,"sim_steps":1080,"calls":8,"rows":1080,"resets":0,"reset_budget":5,"sim_startups":1,"elapsed_s":644.4,"video_rendered":1,"first_success":0,"first_reason_code":4,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0.0,"peak_memory_gb":0.165,"peak_processes":7,"peak_disk_gb":0.262,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":665,"tokens":{"in":2033387,"cached":1795457,"out":45714,"usd":1.39},"task_text":"","step_times":"recorded","sim_total":{"submit":7,"reset":0},"replay":"embodied-olympics-fun-dodgeball-i00-standard--itdshm3/replay.mp4","replay_last":"embodied-olympics-fun-dodgeball-i00-standard--itdshm3/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"Checking workspace and limits","code":"ls -la /app /opt/tools && cat /run/rcb-limits/usage.json"}],"out":{"text":"The command exited with code 0.\nOutput:\n/app:\r\ntotal 12\r\ndrwxr-xr-x 3 root root 4096 Oct 19 06:15 .\r\ndrwxr-xr-x 1 root root 4096 Oct 24 21:55 ..\r\ndrwxr-xr-x 2 root root 4096 Oct 19 06:15 output\r\n\r\n/opt/tools:\r\ntotal 24\r\ndrwxr-xr-x 2 root root  4096 Oct 19 06:15 .\r\ndrwxr-xr-x 1 root root  4096 Oct 19 06:15 ..\r\n-rw-r--r-- 1 root root  3881 Dec  6  2012 rcb1.py\r\n-rw-r--r-- 1 root root 10816 Aug 14  2006 rcb_client.py\r\n{\r\n \"t\": 1792878927.9,\r\n \"measured\": true,\r\n \"gpu_memory_gb\": 0.0,\r\n \"memory_gb\": 0.096,\r\n \"processes\": 5,\r\n \"disk_gb\": 0.0,\r\n \"enforced\": 0,\r\n \"limits\": {\r\n  \"max_gpu_memory_gb\": 0.0,\r\n  \"max_memory_gb\": 8.0,\r\n  \"max_processes\": 512,\r\n  \"max_disk_gb\": 20.0,\r\n  \"sustain_sec\": 60.0,\r\n  \"window_sec\": 120.0\r\n },\r\n \"violations\": [],\r\n \"emergency_kills\": 0,\r\n \"last_emergency_kill\": null,\r\n \"elapsed_s\": 20.0,\r\n \"time_limit_s\": 7200,\r\n \"time_left_s\": 7180.0,\r\n \"deadline_utc\": \"2026-10-24T23:55:07Z\"\r\n}","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":8.0,"say":"","calls":[{"kind":"shell","label":"reads rcb_client.py","code":"/opt/tools/rcb_client.py"},{"kind":"shell","label":"Checking robot status and spec","code":"python3 -c '\nimport sys, json\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nprint(\"STATUS:\", json.dumps(r.status(), indent=2))\nspec = r.spec()\nwith open(\"/tmp/spec.json\", \"w\") as f:\n    json.dump(spec, f, indent=2)\nprint(\"SPEC keys:\", list(spec.keys()))\n' && head -n 120 /tmp/spec.json"}],"out":{"text":"File Path: `file:///opt/tools/rcb_client.py`\nTotal Lines: 190\nTotal Bytes: 10816\nShowing lines 1 to 190\nThe following code has been modified to include a line number before every line, in the format: <line_number>: <original_line>. Please note that any changes targeting the original code should remove the line number, colon, and leading space.\n1: \"\"\"eai-standard/2.1 client: your whole interface to the robot (installed at /opt/tools/rcb_client.py, on PYTHONPATH).\n2: \n3:     from rcb_client import Robot, EpisodeOver\n4:     r = Robot()            # finds the service (SIM_URL, http://sim:8000, http://localhost:8000), waits until it is ready\n5: \n6: Calls (each is one HTTP request; every answer that carries data is an RCB1 frame, decoded into a Result):\n7:     r.spec()                                 GET /spec, fetched when connecting: the robot's facts. \"action_types\"\n8:                                              (\"joint_position\": dim, layout (actuator order), lower/upper, range_rad,\n9:                                              units, semantics), \"control_dt\" (0.02 s), \"max_control_steps\" (the\n10:                                              episode), \"cameras\" {name: rgb, depth, hw, fovy_deg, pose, mounted},\n11:                                              \"proprio_layout\" and \"proprio\" (joints, axes, positions), \"imu\", \"links\"\n12:                                              (masses, centres of mass, the feet's boxes), \"depth\", \"budget\" {\"reset\",\n13:                       \n… (13,084 characters left out) …\ne\",\r\n    \"left_ankle_pitch_torque\",\r\n    \"left_ankle_roll_torque\",\r\n    \"right_hip_pitch_torque\",\r\n    \"right_hip_roll_torque\",\r\n    \"right_hip_yaw_torque\",\r\n    \"right_knee_torque\",\r\n    \"right_ankle_pitch_torque\",\r\n    \"right_ankle_roll_torque\",\r\n    \"waist_yaw_torque\",\r\n    \"waist_roll_torque\",\r\n    \"waist_pitch_torque\",\r\n    \"left_shoulder_pitch_torque\",\r\n    \"left_shoulder_roll_torque\",\r\n    \"left_shoulder_yaw_torque\",\r\n    \"left_elbow_torque\",\r\n    \"left_wrist_roll_torque\",\r\n    \"left_wrist_pitch_torque\",\r\n    \"left_wrist_yaw_torque\",\r\n    \"right_shoulder_pitch_torque\",\r\n    \"right_shoulder_roll_torque\",\r\n    \"right_shoulder_yaw_torque\",\r\n    \"right_elbow_torque\",\r\n    \"right_wrist_roll_torque\",\r\n    \"right_wrist_pitch_torque\",\r\n    \"right_wrist_yaw_torque\",\r\n    \"left_hip_pitch_target\",\r\n    \"left_hip_roll_target\",\r\n    \"left_hip_yaw_target\",\r\n    \"left_knee_target\",\r\n    \"left_ankle_pitch_target\",\r\n    \"left_ankle_roll_target\",\r\n    \"right_hip_pitch_target\",\r\n    \"right_hip_roll_target\",\r\n    \"right_hip_yaw_target\",\r\n    \"right_knee_target\",\r\n    \"right_ankle_pitch_target\",\r\n    \"right_ankle_roll_target\",\r\n    \"waist_yaw_target\",\r\n    \"waist_roll_target\",\r\n    \"waist_pitch_target\",\r\n    \"left_shoulder_pitch_target\",\r\n    \"left_shoulder_roll_target\",\r\n    \"left_shoulder_yaw_target\",\r\n    \"left_elbow_target\",\r\n    \"left_wrist_roll_target\",\r\n    \"left_wrist_pitch_target\",\r\n    \"left_wrist_yaw_target\",\r\n    \"right_shoulder_pitch_target\",\r\n    \"right_shoulder_roll_target\",","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":4,"t":23.0,"say":"","calls":[{"kind":"shell","label":"reads spec.json","code":"/tmp/spec.json"},{"kind":"shell","label":"Checking installed packages and /opt","code":"ls -la /opt /root && pip list"}],"out":{"text":"File Path: `file:///tmp/spec.json`\nTotal Lines: 1691\nTotal Bytes: 37986\nShowing lines 121 to 920\nThe following code has been modified to include a line number before every line, in the format: <line_number>: <original_line>. Please note that any changes targeting the original code should remove the line number, colon, and leading space.\n121:     \"right_shoulder_yaw_target\",\n122:     \"right_elbow_target\",\n123:     \"right_wrist_roll_target\",\n124:     \"right_wrist_pitch_target\",\n125:     \"right_wrist_yaw_target\",\n126:     \"imu_pelvis_qw\",\n127:     \"imu_pelvis_qx\",\n128:     \"imu_pelvis_qy\",\n129:     \"imu_pelvis_qz\",\n130:     \"imu_pelvis_gx\",\n131:     \"imu_pelvis_gy\",\n132:     \"imu_pelvis_gz\",\n133:     \"imu_pelvis_ax\",\n134:     \"imu_pelvis_ay\",\n135:     \"imu_pelvis_az\",\n136:     \"imu_torso_qw\",\n137:     \"imu_torso_qx\",\n138:     \"imu_torso_qy\",\n139:     \"imu_torso_qz\",\n140:     \"imu_torso_gx\",\n141:     \"imu_torso_gy\",\n142:     \"imu_torso_gz\",\n143:     \"imu_torso_ax\",\n144:     \"imu_torso_ay\",\n145:     \"imu_torso_az\",\n146:     \"holding_left\",\n147:     \"holding_right\",\n148:     \"mode\",\n149:     \"cmd_vx\",\n150:     \"cmd_vy\",\n151:     \"cmd_wz\",\n152:     \"time_s\"\n153:   ],\n154:   \"budget\": {\n155:     \"reset\": 5,\n156:     \"wall_clock_s\": 7200.0\n157:   },\n158:   \"clock\": \"time_s and elapsed_s count from your first request to the service; time_left_s is budget.wall_clock_s minus time_s\",\n159:   \"on_service_error\": \"if a call fails with a connection error or a 5xx, the service may have crashe\n… (22,079 characters left out) …\n   1000.0,\n899:         1000.0,\n900:         1000.0,\n901:         1000.0,\n902:         1000.0,\n903:         1000.0,\n904:         1000.0,\n905:         1000.0,\n906:         1000.0,\n907:         1000.0,\n908:         1000.0,\n909:         500.0,\n910:         500.0,\n911:         500.0,\n912:         400.0,\n913:         400.0,\n914:         400.0,\n915:         400.0,\n916:         400.0,\n917:         400.0,\n918:         400.0,\n919:         400.0,\n920:         400.0,\nThe above content does NOT show the entire file contents. If you need to view any lines of the file which were not shown to complete your task, call this tool again to view those lines.\nThe command exited with code 0.\nOutput:\n/opt:\r\ntotal 16\r\ndrwxr-xr-x 1 root root 4096 Oct 19 06:15 .\r\ndrwxr-xr-x 1 root root 4096 Oct 24 21:55 ..\r\ndrwxr-xr-x 1 root root 4096 Oct 24 21:55 tools\r\n\r\n/root:\r\ntotal 28\r\ndrwx------ 1 root root 4096 Oct 24 21:55 .\r\ndrwxr-xr-x 1 root root 4096 Oct 24 21:55 ..\r\n-rw-r--r-- 1 root root  607 Jul 17 17:05 .bashrc\r\ndrwxr-xr-x 4 root root 4096 Oct 24 21:55 .gemini\r\ndrwxr-xr-x 3 root root 4096 Oct 24 21:55 .local\r\n-rw-r--r-- 1 root root  132 Jul 17 17:05 .profile\r\n-rw-r--r-- 1 root root  169 Sep 19 00:59 .wget-hsts\r\nPackage            Version\r\n------------------ ---------\r\ncertifi            2026.7.22\r\ncharset-normalizer 3.5.2\r\nidna               3.20\r\nnumpy              2.5.3\r\npillow             12.3.0\r\npip                25.0.1\r\nrequests           2.34.2\r\nscipy              1.18.1\r\nurllib3            2.8.0","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":5,"t":43.0,"say":"","calls":[{"kind":"shell","label":"reads spec.json","code":"/tmp/spec.json"}],"out":{"text":"File Path: `file:///tmp/spec.json`\nTotal Lines: 1691\nTotal Bytes: 37986\nShowing lines 921 to 1691\nThe following code has been modified to include a line number before every line, in the format: <line_number>: <original_line>. Please note that any changes targeting the original code should remove the line number, colon, and leading space.\n921:         400.0,\n922:         400.0,\n923:         400.0,\n924:         400.0,\n925:         400.0,\n926:         20.0,\n927:         20.0,\n928:         20.0,\n929:         20.0,\n930:         20.0,\n931:         20.0,\n932:         20.0,\n933:         20.0,\n934:         20.0,\n935:         20.0,\n936:         20.0,\n937:         20.0,\n938:         15.0,\n939:         15.0,\n940:         15.0,\n941:         10.0,\n942:         10.0,\n943:         10.0,\n944:         10.0,\n945:         10.0,\n946:         10.0,\n947:         10.0,\n948:         10.0,\n949:         10.0,\n950:         10.0,\n951:         10.0,\n952:         10.0,\n953:         10.0,\n954:         10.0,\n955:         1.0,\n956:         1.0\n957:       ],\n958:       \"meaning\": \"Unitree's LowCmd for all 29 joints: position targets (rad), velocity targets (rad/s), feed-forward torques (N m), kp, kd; the motor torque is kp (q - q_measured) + kd (dq - dq_measured) + tau, evaluated at 1 kHz\",\n959:       \"semantics\": \"rows dt apart (a multiple of control_dt); each control step's command is the row (hold) or a straight line from the command in force (linear); values outside lower/upper are clipped and reported; a \n… (17,059 characters left out) …\n      ]\n1679:     ],\n1680:     \"grip\": {\n1681:       \"reach_m\": 0.035,\n1682:       \"max_relative_speed_m_s\": 6.0,\n1683:       \"rule\": \"a closed grip holds the nearest grippable object whose surface is within reach_m of the palm (a point 4.5 cm beyond the wrist flange along the forearm) and that moves no faster than max_relative_speed_m_s relative to it; opening the grip lets it go\"\n1684:     }\n1685:   },\n1686:   \"proprio\": {\n1687:     \"units\": \"*_pos, *_target: rad; *_vel: rad/s; *_torque: N m (the motor torque applied); imu_*: orientation quaternion (w, x, y, z; world from sensor), angular velocity (rad/s) and acceleration (m/s^2, gravity included) in the sensor's frame; holding_*: 1 while that hand grips something; mode: 0 stand, 1 walk, 2 run, 3 run_arms, 4 joints / lowcmd, 5 walk_falcon, 6 walk_agile (the G1's); cmd_*: the velocity command in force; time_s: the episode's time\"\n1688:   },\n1689:   \"referee\": \"once an attempt is over, every response's meta carries the referee's call: meta['outcome'] ('success' or the rule that ended it) and meta['stages_reached'] of meta['stages_total']\",\n1690:   \"reset\": \"POST /reset abandons the running episode and starts a new one from the same starting state, budget.reset times in all; only the last episode is graded, and a success ends the trial\"\n1691: }\nThe above content does NOT show the entire file contents. If you need to view any lines of the file which were not shown to complete your task, call this tool again to view those lines.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":6,"t":52.0,"say":"","calls":[{"kind":"robot","label":"Fetching free initial observation","code":"python3 -c '\nimport sys\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nres = r.get_obs(seconds=0, include_depth=True)\nres.save(\"/tmp/obs_t0\")\nprint(\"Saved obs_t0, time_s:\", res.meta.get(\"time_s\"), \"control_steps:\", res.meta.get(\"control_steps\"))\n' && ls -la /tmp/obs_t0 /tmp/obs_t0/last"}],"out":{"text":"The command exited with code 0.\nOutput:\nSaved obs_t0, time_s: 65.3 control_steps: 0\r\n/tmp/obs_t0:\r\ntotal 284\r\ndrwxr-xr-x 4 root root   4096 Oct 24 21:56 .\r\ndrwxrwxrwt 1 root root   4096 Oct 24 21:56 ..\r\n-rw-r--r-- 1 root root 259328 Oct 24 21:56 depth_head_left.npy\r\ndrwxr-xr-x 6 root root   4096 Oct 24 21:56 frames\r\ndrwxr-xr-x 2 root root   4096 Oct 24 21:56 last\r\n-rw-r--r-- 1 root root   5586 Oct 24 21:56 meta.json\r\n-rw-r--r-- 1 root root    700 Oct 24 21:56 proprio.npy\r\n\r\n/tmp/obs_t0/last:\r\ntotal 168\r\ndrwxr-xr-x 2 root root  4096 Oct 24 21:56 .\r\ndrwxr-xr-x 4 root root  4096 Oct 24 21:56 ..\r\n-rw-r--r-- 1 root root 37395 Oct 24 21:56 head_left.jpg\r\n-rw-r--r-- 1 root root 37258 Oct 24 21:56 head_right.jpg\r\n-rw-r--r-- 1 root root 39473 Oct 24 21:56 side.jpg\r\n-rw-r--r-- 1 root root 37476 Oct 24 21:56 venue.jpg","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":7,"t":88.0,"say":"","calls":[{"kind":"look","label":"venue.jpg","code":"/tmp/obs_t0/last/venue.jpg"},{"kind":"look","label":"side.jpg","code":"/tmp/obs_t0/last/side.jpg"},{"kind":"look","label":"head_left.jpg","code":"/tmp/obs_t0/last/head_left.jpg"},{"kind":"shell","label":"reads meta.json","code":"/tmp/obs_t0/meta.json"}],"out":{"text":"The following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.\nFile Path: `file:///tmp/obs_t0/meta.json`\nTotal Lines: 309\nTotal Bytes: 5586\nShowing lines 1 to 309\nThe following code has been modified to include a line number before every line, in the format: <line_number>: <original_line>. Please note that any changes targeting the original code should remove the line number, colon, and leading space.\n1: {\n2:  \"calls\": 1,\n3:  \"rows\": 0,\n4:  \"control_steps\": 0,\n5:  \"done\": false,\n6:  \"reason\": null,\n7:  \"episode\": 1,\n8:  \"control_steps_total\": 0,\n9:  \"resets_left\": 5,\n10:  \"sim_time_s\": 0.0,\n11:  \"time_s\": 65.3,\n12:  \"time_left_s\": 7134.7,\n13:  \"proprio\": {\n14:   \"layout\": [\n15:    \"left_hip_pitch_pos\",\n16:    \"left_hip_roll_pos\",\n17:    \"left_hip_yaw_pos\",\n18:    \"left_knee_pos\",\n19:    \"left_ankle_pitch_pos\",\n20:    \"left_ankle_roll_pos\",\n21:    \"right_hip_pitch_pos\",\n22:    \"right_hip_roll_pos\",\n23:    \"right_hip_yaw_pos\",\n24:    \"right_knee_pos\",\n25:    \"right_ankle_pitch_pos\",\n26:    \"right_ankle_roll_pos\",\n27:    \"waist_yaw_pos\",\n28:    \"waist_roll_pos\",\n29:    \"waist_pitch_pos\",\n30:    \"left_shoulder_pitch_pos\",\n31:    \"left_shoulder_roll_pos\",\n32:    \"left_shoulder_yaw_pos\",\n33:    \"left_elbow_pos\",\n34:    \"left_wrist_roll_pos\",\n35:    \"left_wrist_pitch_pos\",\n36:    \"left_wrist_yaw_pos\",\n37:    \"right_shoulder_pitch_pos\",\n38:  \n… (4,654 characters left out) …\n26:    0.0,\n227:    0.0,\n228:    0.0,\n229:    0.0,\n230:    0.0,\n231:    0.0,\n232:    0.0,\n233:    0.0,\n234:    0.0,\n235:    0.0,\n236:    0.0,\n237:    0.0,\n238:    0.0,\n239:    0.0,\n240:    0.0,\n241:    0.0,\n242:    0.0,\n243:    0.0,\n244:    0.0,\n245:    0.0,\n246:    0.0,\n247:    -0.10000000149011612,\n248:    0.0,\n249:    0.0,\n250:    0.30000001192092896,\n251:    -0.20000000298023224,\n252:    0.0,\n253:    -0.10000000149011612,\n254:    0.0,\n255:    0.0,\n256:    0.30000001192092896,\n257:    -0.20000000298023224,\n258:    0.0,\n259:    0.0,\n260:    0.0,\n261:    0.0,\n262:    0.20000000298023224,\n263:    0.20000000298023224,\n264:    0.0,\n265:    1.2799999713897705,\n266:    0.0,\n267:    0.0,\n268:    0.0,\n269:    0.20000000298023224,\n270:    -0.20000000298023224,\n271:    0.0,\n272:    1.2799999713897705,\n273:    0.0,\n274:    0.0,\n275:    0.0,\n276:    1.0,\n277:    0.0,\n278:    0.0,\n279:    0.0,\n280:    0.0,\n281:    0.0,\n282:    0.0,\n283:    -2.773884671492064e-17,\n284:    1.444175160851923e-16,\n285:    -3.801643678571645e-17,\n286:    1.0,\n287:    0.0,\n288:    0.0,\n289:    0.0,\n290:    0.0,\n291:    0.0,\n292:    0.0,\n293:    9.670092085324616e-17,\n294:    -4.371911919033053e-17,\n295:    7.57242409043608e-18,\n296:    0.0,\n297:    0.0,\n298:    0.0,\n299:    0.0,\n300:    0.0,\n301:    0.0,\n302:    0.0\n303:   ]\n304:  },\n305:  \"obs_id\": 1,\n306:  \"seconds\": 0.0,\n307:  \"control_steps_watch\": 0,\n308:  \"ok\": true\n309: }\nThe above content shows the entire, complete file contents of the requested file.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":96.0,"say":"","calls":[{"kind":"edit","label":"NOTES.md","code":"/app/output/NOTES.md\n\n# Approach & Notes\n- Task: Embodied Olympics Dodgeball (i00, standard mode). Survive 5 throws from ball machines at x=8m, y in [0, -3, 3, -1.5, 1.5]m fed at t=2.0, 4.5, 7.0, 9.5, 12.0s.\n- Turrets track robot pelvis (at z=0.8m) until feed time without leading moving targets.\n- Strategy: Accelerate perpendicular to the active machine's line of sight before each feed time and maintain high perpendicular velocity through the ball flight window (~0.8s after feed).\n- No external packages or weights downloaded; using built-in locomotion policies via rcb_client.\n"},{"kind":"edit","label":"NOTES.md","code":"/app/NOTES.md\n\n# Approach & Notes\n- Task: Embodied Olympics Dodgeball (i00, standard mode). Survive 5 throws from ball machines at x=8m, y in [0, -3, 3, -1.5, 1.5]m fed at t=2.0, 4.5, 7.0, 9.5, 12.0s.\n- Turrets track robot pelvis (at z=0.8m) until feed time without leading moving targets.\n- Strategy: Accelerate perpendicular to the active machine's line of sight before each feed time and maintain high perpendicular velocity through the ball flight window (~0.8s after feed).\n- No external packages or weights downloaded; using built-in locomotion policies via rcb_client.\n"}],"out":{"text":"Created file file:///app/output/NOTES.md with requested content.\nIf relevant, proactively run terminal commands to execute this code for the USER. Don't ask for permission.\nCreated file file:///app/NOTES.md with requested content.\nIf relevant, proactively run terminal commands to execute this code for the USER. Don't ask for permission.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":230.0,"say":"","calls":[{"kind":"robot","label":"Testing 0.5s of walk_falcon sidestep","code":"python3 -c '\nimport sys, json, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nrest_upper = spec[\"robot_facts\"][\"rest_upper_rad\"] # 17 floats (3 waist + 14 arms)\nrow = [0.0, 0.5, 0.0] + list(rest_upper) + [0.0, 0.0]\nA = np.tile(row, (50, 1))\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=10, video=\"frames\")\nres.save(\"/tmp/step_0_5\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"])\nprint(\"proprio shape:\", res.proprio.shape)\nlayout = spec[\"proprio_layout\"]\nfor k in [\"imu_pelvis_qw\", \"imu_pelvis_qx\", \"imu_pelvis_qy\", \"imu_pelvis_qz\", \"imu_pelvis_ax\", \"imu_pelvis_ay\", \"cmd_vx\", \"cmd_vy\", \"cmd_wz\", \"mode\", \"time_s\"]:\n    idx = layout.index(k)\n    print(f\"{k}: {[round(float(x), 4) for x in res.proprio[:, idx]]}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 0.5 done: False reason: None\r\nproprio shape: (6, 143)\r\nimu_pelvis_qw: [1.0, 0.9987, 0.9984, 0.9992, 0.9997, 0.9999]\r\nimu_pelvis_qx: [0.0, 0.0022, -0.0062, -0.0174, -0.0194, -0.0105]\r\nimu_pelvis_qy: [0.0, 0.0473, 0.0512, 0.0368, 0.0148, 0.0028]\r\nimu_pelvis_qz: [0.0, 0.0194, 0.0212, 0.0028, -0.006, -0.009]\r\nimu_pelvis_ax: [-0.0, 1.8742, -1.2195, 0.1118, -1.5131, -0.8552]\r\nimu_pelvis_ay: [0.0, 3.9375, 1.3974, -0.9082, -0.3785, 1.3388]\r\ncmd_vx: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\r\ncmd_vy: [0.0, 0.5, 0.5, 0.5, 0.5, 0.5]\r\ncmd_wz: [0.0, 0.0, 0.0, 0.0, 0.0, 0.0]\r\nmode: [0.0, 5.0, 5.0, 5.0, 5.0, 5.0]\r\ntime_s: [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":279.0,"say":"","calls":[{"kind":"robot","label":"Testing 3D to 2D camera projection","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    up = np.array(cam[\"pose_t0\"][\"up\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    # normalize basis just in case\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    \n    rel = pts_3d - pos\n    z_c = rel @ fwd\n    x_c = rel @ right\n    y_c = rel @ up\n    u = cx + fx * (x_c / z_c)\n    v = cy - fy * (y_c / z_c)\n    return np.stack([u, v, z_c], axis=-1)\n\n# Check where (0, 0, 0.8) (pelvis at t=0) and (0, 0, 0) (feet at t=0) project in venue and side\npts = np.array([[0.0, 0.0, 0.8], [0.0, 0.0, 0.0], [8.0, 0.0, 1.2]])\nfor cname in [\"venue\", \"side\"]:\n    uv = project_points(pts, cname)\n    img = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"))\n    print(cname, \"pelvis uv:\", uv[0, :2].round(1), \"feet uv:\", uv[1, :2].round(1), \"machine0 uv:\", uv[2, :2].round(1))\n    u, v = int(round(uv[0, 0])), int(round(uv[0, 1]))\n    print(\"  pixel at pelvis:\", img[v, u])\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nvenue pelvis uv: [196.4 155.2] feet uv: [197.4 171.1] machine0 uv: [267.  112.1]\r\n  pixel at pelvis: [68 60 49]\r\nside pelvis uv: [156.  141.3] feet uv: [157.4 159.1] machine0 uv: [301.1 123.8]\r\n  pixel at pelvis: [51 30 25]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":11,"t":297.0,"say":"","calls":[{"kind":"shell","label":"Testing 3D ray triangulation from venue and side cameras","code":"python3 -c '\nimport json, glob, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef get_ray(u, v, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    d = fwd + ((u - cx) / fx) * right + ((cy - v) / fy) * up\n    d = d / np.linalg.norm(d)\n    return pos, d\n\ndef intersect_z(u, v, z_plane, cam_name):\n    pos, d = get_ray(u, v, cam_name)\n    t = (z_plane - pos[2]) / d[2]\n    return pos + t * d\n\ndef triangulate(uv_venue, uv_side):\n    p1, d1 = get_ray(uv_venue[0], uv_venue[1], \"venue\")\n    p2, d2 = get_ray(uv_side[0], uv_side[1], \"side\")\n    # solve argmin ||(p1 + t1 d1) - (p2 + t2 d2)||\n    A = np.column_stack([d1, -d2])\n    b = p2 - p1\n    ts, _, _, _ = np.linalg.lstsq(A, b, rcond=None)\n    pt1 = p1 + ts[0] * d1\n    pt2 = p2 + ts[1] * d2\n    return 0.5 * (pt1 + pt2), np.linalg.norm(pt1 - pt2)\n\n# Check triangulation of initial pelvis uv:\npt, err = triangulate([196.4, 155.2], [156.0, 141.3])\nprint(\"Triangulated t=0 pelvis:\", pt.round(3), \"ray dist:\", round(err, 4))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nTriangulated t=0 pelvis: [-0.002 -0.003  0.801] ray dist: 0.0024","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":310.0,"say":"","calls":[{"kind":"shell","label":"Localizing robot 3D trajectory from cameras","code":"python3 -c '\nimport json, glob, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    z_c = rel @ fwd\n    x_c = rel @ right\n    y_c = rel @ up\n    u = cx + fx * (x_c / z_c)\n    v = cy - fy * (y_c / z_c)\n    return u, v\n\n# Build a clean background for venue and side by inpainting the small box at (0,0,z) in t=0 image with horizontal neighbor pixels\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        # linearly interpolate across [umin, umax] from left and right border pixels\n        left_px = clean[v, umin - 1]\n        right_px = clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=0.0, y_center=0.0, radius=1.0, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            # sum in a 3x3 window around (vi, ui)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nfor i in range(6):\n    iv = np.array(Image.open(f\"/tmp/step_0_5/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_0_5/frames/side/{i:03d}.jpg\"))\n    x, y, s = locate_robot(iv, isd)\n    print(f\"t={i*0.1:.1f}s: x={x:.3f}, y={y:.3f} (score={s:.1f})\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=0.0s: x=0.000, y=0.040 (score=6672.8)\r\nt=0.1s: x=0.040, y=0.040 (score=7056.8)\r\nt=0.2s: x=0.020, y=0.060 (score=6963.4)\r\nt=0.3s: x=0.000, y=0.080 (score=6553.6)\r\nt=0.4s: x=-0.020, y=0.140 (score=6484.6)\r\nt=0.5s: x=-0.020, y=0.160 (score=6629.4)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":331.0,"say":"","calls":[{"kind":"robot","label":"Turning robot 90 degrees left in walk_falcon","code":"python3 -c '\nimport sys, json, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\n# waist (3): 0, 0, 0\n# left arm (7): pitch=0.0, roll=0.2, yaw=0.0, elbow=0.2, wrist=0,0,0\n# right arm (7): pitch=0.0, roll=-0.2, yaw=0.0, elbow=0.2, wrist=0,0,0\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\nrow = [0.2, 0.2, 1.0] + upper + [0.0, 0.0]\nA = np.tile(row, (120, 1))\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=10, video=\"frames\")\nres.save(\"/tmp/step_1_7\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"])\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\n# yaw from quaternion: atan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (rad):\", np.round(yaws, 3))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws), 1))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 1.7 done: False reason: None\r\nyaws (rad): [-0.018  0.029  0.115  0.205  0.29   0.391  0.498  0.591  0.629  0.709\r\n  0.792  0.898  1.008]\r\nyaws (deg): [-1.   1.7  6.6 11.7 16.6 22.4 28.5 33.9 36.  40.6 45.4 51.4 57.7]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":14,"t":357.0,"say":"","calls":[{"kind":"robot","label":"Running through Throw 1 (t=1.7s to 3.2s)","code":"python3 -c '\nimport sys, json, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\nrow1 = [0.8, 0.4, 0.8] + upper + [0.0, 0.0]\nrow2 = [0.8, 0.0, 0.0] + upper + [0.0, 0.0]\nA = np.vstack([np.tile(row1, (50, 1)), np.tile(row2, (100, 1))])\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=20, video=\"frames\")\nres.save(\"/tmp/step_3_2\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"], \"meta:\", {k: res.meta.get(k) for k in [\"outcome\", \"stages_reached\", \"stages_total\"]})\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws[::2]), 1))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 3.2 done: False reason: None meta: {'outcome': None, 'stages_reached': None, 'stages_total': None}\r\nyaws (deg): [57.7 62.2 64.  68.3 72.5 78.6 83.1 82.5 82.5 87.8 89.8 90.6 88.2 87.7\r\n 90.1 91.7]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":15,"t":376.0,"say":"","calls":[{"kind":"robot","label":"Measuring robot trajectory during Throw 1","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    z_c = rel @ fwd\n    x_c = rel @ right\n    y_c = rel @ up\n    return cx + fx * (x_c / z_c), cy - fy * (y_c / z_c)\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=0.0, y_center=0.5, radius=1.5, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nxc, yc = 0.2, 0.4\nfor i in range(0, 31, 2):\n    iv = np.array(Image.open(f\"/tmp/step_3_2/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_3_2/frames/side/{i:03d}.jpg\"))\n    xc, yc, s = locate_robot(iv, isd, xc, yc, radius=0.5, step=0.02)\n    print(f\"t={1.7 + i*0.05:.2f}s (frame {i:03d}): x={xc:.2f}, y={yc:.2f}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=1.70s (frame 000): x=0.02, y=0.32\r\nt=1.80s (frame 002): x=-0.02, y=0.34\r\nt=1.90s (frame 004): x=-0.06, y=0.44\r\nt=2.00s (frame 006): x=-0.06, y=0.46\r\nt=2.10s (frame 008): x=-0.06, y=0.56\r\nt=2.20s (frame 010): x=-0.06, y=0.56\r\nt=2.30s (frame 012): x=-0.06, y=0.62\r\nt=2.40s (frame 014): x=-0.10, y=0.70\r\nt=2.50s (frame 016): x=-0.08, y=0.84\r\nt=2.60s (frame 018): x=-0.02, y=0.98\r\nt=2.70s (frame 020): x=-0.02, y=1.06\r\nt=2.80s (frame 022): x=-0.06, y=1.06\r\nt=2.90s (frame 024): x=-0.08, y=1.16\r\nt=3.00s (frame 026): x=-0.02, y=1.30\r\nt=3.10s (frame 028): x=-0.02, y=1.38\r\nt=3.20s (frame 030): x=-0.02, y=1.42","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":16,"t":395.0,"say":"","calls":[{"kind":"look","label":"015.jpg","code":"/tmp/step_3_2/frames/venue/015.jpg"},{"kind":"look","label":"019.jpg","code":"/tmp/step_3_2/frames/venue/019.jpg"},{"kind":"look","label":"019.jpg","code":"/tmp/step_3_2/frames/side/019.jpg"}],"out":{"text":"The following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":17,"t":402.0,"say":"","calls":[{"kind":"look","label":"023.jpg","code":"/tmp/step_3_2/frames/venue/023.jpg"},{"kind":"look","label":"025.jpg","code":"/tmp/step_3_2/frames/venue/025.jpg"},{"kind":"look","label":"027.jpg","code":"/tmp/step_3_2/frames/venue/027.jpg"},{"kind":"look","label":"025.jpg","code":"/tmp/step_3_2/frames/side/025.jpg"}],"out":{"text":"The following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.\nThe following is the entire, complete content of the requested file.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":18,"t":418.0,"say":"","calls":[{"kind":"shell","label":"Triangulating 3D trajectory of Ball 1","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef get_ray(u, v, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    d = fwd + ((u - cx) / fx) * right + ((cy - v) / fy) * up\n    return pos, d / np.linalg.norm(d)\n\ndef triangulate(uv_venue, uv_side):\n    p1, d1 = get_ray(uv_venue[0], uv_venue[1], \"venue\")\n    p2, d2 = get_ray(uv_side[0], uv_side[1], \"side\")\n    A = np.column_stack([d1, -d2])\n    b = p2 - p1\n    ts, _, _, _ = np.linalg.lstsq(A, b, rcond=None)\n    pt1 = p1 + ts[0] * d1\n    pt2 = p2 + ts[1] * d2\n    return 0.5 * (pt1 + pt2), np.linalg.norm(pt1 - pt2)\n\nbg_v = np.array(Image.open(\"/tmp/obs_t0/last/venue.jpg\"), dtype=np.float32)\nbg_s = np.array(Image.open(\"/tmp/obs_t0/last/side.jpg\"), dtype=np.float32)\n\nfor i in range(6, 31):\n    iv = np.array(Image.open(f\"/tmp/step_3_2/frames/venue/{i:03d}.jpg\"), dtype=np.float32)\n    isd = np.array(Image.open(f\"/tmp/step_3_2/frames/side/{i:03d}.jpg\"), dtype=np.float32)\n    # red ball mask: changed from bg and very red (R - G > 50 and R > 120)\n    mv = (np.abs(iv - bg_v).mean(axis=-1) > 25) & ((iv[:,:,0] - iv[:,:,1]) > 45) & (iv[:,:,0] > 110)\n    ms = (np.abs(isd - bg_s).mean(axis=-1) > 25) & ((isd[:,:,0] - isd[:,:,1]) > 45) & (isd[:,:,0] > 110)\n    if mv.sum() > 0 and ms.sum() > 0:\n        vv, uv = np.where(mv)\n        vs, us = np.where(ms)\n        pt, err = triangulate([uv.mean(), vv.mean()], [us.mean(), vs.mean()])\n        print(f\"t={1.7 + i*0.05:.2f}s (frame {i:03d}): ball xyz = [{pt[0]:6.2f}, {pt[1]:6.2f}, {pt[2]:5.2f}] (err={err:.3f}m)\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=2.00s (frame 006): ball xyz = [  0.14,   0.12,  0.28] (err=0.589m)\r\nt=2.05s (frame 007): ball xyz = [  0.15,  -0.06,  0.31] (err=0.585m)\r\nt=2.10s (frame 008): ball xyz = [  0.10,  -0.01,  0.31] (err=0.499m)\r\nt=2.15s (frame 009): ball xyz = [  0.13,   0.09,  0.29] (err=0.431m)\r\nt=2.20s (frame 010): ball xyz = [  1.35,   0.93,  0.06] (err=0.129m)\r\nt=2.25s (frame 011): ball xyz = [  0.18,   0.02,  0.31] (err=0.553m)\r\nt=2.30s (frame 012): ball xyz = [  0.21,   0.01,  0.33] (err=0.518m)\r\nt=2.35s (frame 013): ball xyz = [  2.58,   1.91, -0.08] (err=1.375m)\r\nt=2.40s (frame 014): ball xyz = [  1.23,   0.90,  0.13] (err=0.246m)\r\nt=2.45s (frame 015): ball xyz = [  0.86,   0.65,  0.18] (err=0.000m)\r\nt=2.50s (frame 016): ball xyz = [  0.76,   0.48,  0.28] (err=0.006m)\r\nt=2.55s (frame 017): ball xyz = [  0.31,   0.07,  0.32] (err=0.449m)\r\nt=2.60s (frame 018): ball xyz = [  1.43,   0.96,  0.18] (err=0.409m)\r\nt=2.65s (frame 019): ball xyz = [  0.71,   0.45,  0.40] (err=0.174m)\r\nt=2.70s (frame 020): ball xyz = [  0.41,   0.19,  0.43] (err=0.123m)\r\nt=2.75s (frame 021): ball xyz = [  0.33,   0.20,  0.40] (err=0.347m)\r\nt=2.80s (frame 022): ball xyz = [  0.30,   0.15,  0.51] (err=0.114m)\r\nt=2.85s (frame 023): ball xyz = [  0.11,   0.13,  0.41] (err=0.265m)\r\nt=2.90s (frame 024): ball xyz = [ -0.03,   0.00,  0.48] (err=0.248m)\r\nt=2.95s (frame 025): ball xyz = [ -0.12,  -0.04,  0.44] (err=0.332m)\r\nt=3.00s (frame 026): ball xyz = [  0.12,   0.29,  0.30] (err=0.187m)\r\nt=3.05s (frame 027): ball xyz = [ -0.59,  -0.28,  0.50] (err=0.502m)\r\nt=3.10s (frame 028): ball xyz = [ -0.71,  -0.35,  0.56] (err=0.491m)\r\nt=3.15s (frame 029): ball xyz = [ -0.72,  -0.27,  0.54] (err=0.482m)\r\nt=3.20s (frame 030): ball xyz = [ -0.96,  -0.41,  0.65] (err=0.481m)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":19,"t":442.0,"say":"","calls":[{"kind":"shell","label":"Triangulating Ball 1 with clean background","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\n\nspec = json.load(open(\"/tmp/spec.json\"))\n\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    z_c = rel @ fwd\n    x_c = rel @ right\n    y_c = rel @ up\n    return cx + fx * (x_c / z_c), cy - fy * (y_c / z_c)\n\ndef get_ray(u, v, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    d = fwd + ((u - cx) / fx) * right + ((cy - v) / fy) * up\n    return pos, d / np.linalg.norm(d)\n\ndef triangulate(uv_venue, uv_side):\n    p1, d1 = get_ray(uv_venue[0], uv_venue[1], \"venue\")\n    p2, d2 = get_ray(uv_side[0], uv_side[1], \"side\")\n    A = np.column_stack([d1, -d2])\n    b = p2 - p1\n    ts, _, _, _ = np.linalg.lstsq(A, b, rcond=None)\n    pt1 = p1 + ts[0] * d1\n    pt2 = p2 + ts[1] * d2\n    return 0.5 * (pt1 + pt2), np.linalg.norm(pt1 - pt2)\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\nfor i in range(6, 31):\n    iv = np.array(Image.open(f\"/tmp/step_3_2/frames/venue/{i:03d}.jpg\"), dtype=np.float32)\n    isd = np.array(Image.open(f\"/tmp/step_3_2/frames/side/{i:03d}.jpg\"), dtype=np.float32)\n    mv = (np.abs(iv - bg[\"venue\"]).mean(axis=-1) > 25) & ((iv[:,:,0] - iv[:,:,1]) > 65) & (iv[:,:,0] > 120)\n    ms = (np.abs(isd - bg[\"side\"]).mean(axis=-1) > 25) & ((isd[:,:,0] - isd[:,:,1]) > 65) & (isd[:,:,0] > 120)\n    if mv.sum() > 0 and ms.sum() > 0:\n        vv, uv = np.where(mv)\n        vs, us = np.where(ms)\n        pt, err = triangulate([uv.mean(), vv.mean()], [us.mean(), vs.mean()])\n        print(f\"t={1.7 + i*0.05:.2f}s (frame {i:03d}): ball xyz = [{pt[0]:6.2f}, {pt[1]:6.2f}, {pt[2]:5.2f}] (err={err:.3f}m)\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=2.35s (frame 013): ball xyz = [  5.36,   0.15,  1.69] (err=0.035m)\r\nt=2.40s (frame 014): ball xyz = [  4.80,   0.28,  1.74] (err=0.005m)\r\nt=2.45s (frame 015): ball xyz = [  4.27,   0.35,  1.74] (err=0.029m)\r\nt=2.50s (frame 016): ball xyz = [  3.61,   0.27,  1.75] (err=0.002m)\r\nt=2.60s (frame 018): ball xyz = [  2.50,   0.25,  1.67] (err=0.005m)\r\nt=2.65s (frame 019): ball xyz = [  2.02,   0.43,  1.57] (err=0.002m)\r\nt=2.75s (frame 021): ball xyz = [  1.01,   0.48,  1.34] (err=0.049m)\r\nt=2.80s (frame 022): ball xyz = [  0.56,   0.60,  1.17] (err=0.008m)\r\nt=2.85s (frame 023): ball xyz = [  0.11,   0.62,  1.01] (err=0.001m)\r\nt=2.90s (frame 024): ball xyz = [ -0.33,   0.64,  0.83] (err=0.012m)\r\nt=2.95s (frame 025): ball xyz = [ -0.79,   0.70,  0.62] (err=0.008m)\r\nt=3.00s (frame 026): ball xyz = [ -1.19,   0.78,  0.39] (err=0.004m)\r\nt=3.05s (frame 027): ball xyz = [ -1.62,   0.79,  0.14] (err=0.016m)\r\nt=3.10s (frame 028): ball xyz = [ -1.91,   0.81,  0.25] (err=0.011m)\r\nt=3.15s (frame 029): ball xyz = [ -2.19,   0.87,  0.30] (err=0.002m)\r\nt=3.20s (frame 030): ball xyz = [ -2.49,   0.87,  0.37] (err=0.016m)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":20,"t":466.0,"say":"","calls":[{"kind":"robot","label":"Testing backward walk_falcon from t=3.2s to 4.3s","code":"python3 -c '\nimport sys, json, numpy as np\nfrom PIL import Image\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\n# Currently at t=3.20s, yaw=91.7 deg (+1.60 rad). Command vx=-0.8, vy=0.0, wz=-0.05 to keep yaw near 90 deg\nrow = [-0.8, 0.0, -0.05] + upper + [0.0, 0.0]\nA = np.tile(row, (110, 1))\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=20, video=\"frames\")\nres.save(\"/tmp/step_4_3\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"])\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws[::2]), 1))\n' && python3 -c '\nimport json, numpy as np\nfrom PIL import Image\nspec = json.load(open(\"/tmp/spec.json\"))\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    return cx + fx * ((rel @ right) / (rel @ fwd)), cy - fy * ((rel @ up) / (rel @ fwd))\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=0.0, y_center=1.0, radius=0.8, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nxc, yc = -0.02, 1.42\nfor i in range(0, 23, 2):\n    iv = np.array(Image.open(f\"/tmp/step_4_3/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_4_3/frames/side/{i:03d}.jpg\"))\n    xc, yc, s = locate_robot(iv, isd, xc, yc, radius=0.5, step=0.02)\n    print(f\"t={3.2 + i*0.05:.2f}s (frame {i:03d}): x={xc:.2f}, y={yc:.2f}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 4.3 done: False reason: None\r\nyaws (deg): [91.7 92.5 79.8 77.6 79.6 81.8 82.4 82.2 80.9 79.7 79.8 80.5]\r\nt=3.20s (frame 000): x=-0.02, y=1.42\r\nt=3.30s (frame 002): x=0.02, y=1.56\r\nt=3.40s (frame 004): x=0.02, y=1.62\r\nt=3.50s (frame 006): x=0.02, y=1.62\r\nt=3.60s (frame 008): x=0.02, y=1.62\r\nt=3.70s (frame 010): x=0.02, y=1.62\r\nt=3.80s (frame 012): x=-0.06, y=1.46\r\nt=3.90s (frame 014): x=-0.10, y=1.42\r\nt=4.00s (frame 016): x=-0.14, y=1.26\r\nt=4.10s (frame 018): x=-0.14, y=1.16\r\nt=4.20s (frame 020): x=-0.14, y=1.12\r\nt=4.30s (frame 022): x=-0.18, y=1.00","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":21,"t":515.0,"say":"","calls":[{"kind":"robot","label":"Running through Throw 2 (t=4.3s to 5.8s)","code":"python3 -c '\nimport sys, json, numpy as np\nfrom PIL import Image\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\nrow = [-0.8, 0.35, 0.15] + upper + [0.0, 0.0]\nA = np.tile(row, (150, 1))\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=20, video=\"frames\")\nres.save(\"/tmp/step_5_8\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"], \"meta:\", {k: res.meta.get(k) for k in [\"outcome\", \"stages_reached\", \"stages_total\"]})\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws[::2]), 1))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 5.8 done: False reason: None meta: {'outcome': None, 'stages_reached': None, 'stages_total': None}\r\nyaws (deg): [80.5 81.2 81.9 83.6 85.5 86.9 87.7 87.2 88.9 89.9 91.6 92.5 92.2 93.9\r\n 94.9 95.7]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":22,"t":544.0,"say":"","calls":[{"kind":"robot","label":"Measuring robot trajectory during Throw 2","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\nspec = json.load(open(\"/tmp/spec.json\"))\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    return cx + fx * ((rel @ right) / (rel @ fwd)), cy - fy * ((rel @ up) / (rel @ fwd))\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=-0.2, y_center=1.0, radius=0.6, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nxc, yc = -0.18, 1.00\nfor i in range(0, 31, 2):\n    iv = np.array(Image.open(f\"/tmp/step_5_8/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_5_8/frames/side/{i:03d}.jpg\"))\n    xc, yc, s = locate_robot(iv, isd, xc, yc, radius=0.5, step=0.02)\n    print(f\"t={4.3 + i*0.05:.2f}s (frame {i:03d}): x={xc:.2f}, y={yc:.2f}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=4.30s (frame 000): x=-0.18, y=1.00\r\nt=4.40s (frame 002): x=-0.22, y=0.90\r\nt=4.50s (frame 004): x=-0.20, y=0.86\r\nt=4.60s (frame 006): x=-0.22, y=0.74\r\nt=4.70s (frame 008): x=-0.26, y=0.70\r\nt=4.80s (frame 010): x=-0.34, y=0.54\r\nt=4.90s (frame 012): x=-0.34, y=0.48\r\nt=5.00s (frame 014): x=-0.28, y=0.48\r\nt=5.10s (frame 016): x=-0.38, y=0.34\r\nt=5.20s (frame 018): x=-0.42, y=0.26\r\nt=5.30s (frame 020): x=-0.44, y=0.18\r\nt=5.40s (frame 022): x=-0.40, y=0.14\r\nt=5.50s (frame 024): x=-0.48, y=0.02\r\nt=5.60s (frame 026): x=-0.46, y=-0.06\r\nt=5.70s (frame 028): x=-0.50, y=-0.10\r\nt=5.80s (frame 030): x=-0.58, y=-0.24","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":23,"t":559.0,"say":"","calls":[{"kind":"robot","label":"Running through Throw 3 (t=5.8s to 8.3s)","code":"python3 -c '\nimport sys, json, numpy as np\nfrom PIL import Image\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\n# First 1.0s with wz=-0.10 to bring yaw from 95.7 deg back to ~90 deg, then wz=0.0\nrow1 = [0.8, -0.2, -0.10] + upper + [0.0, 0.0]\nrow2 = [0.8, -0.2, 0.0] + upper + [0.0, 0.0]\nA = np.vstack([np.tile(row1, (100, 1)), np.tile(row2, (150, 1))])\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=20, video=\"frames\")\nres.save(\"/tmp/step_8_3\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"], \"meta:\", {k: res.meta.get(k) for k in [\"outcome\", \"stages_reached\", \"stages_total\"]})\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws[::5]), 1))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 8.3 done: False reason: None meta: {'outcome': None, 'stages_reached': None, 'stages_total': None}\r\nyaws (deg): [95.7 82.3 74.6 76.7 74.8 80.4 77.2 82.9 79.6 85.3 82.1]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":584.0,"say":"","calls":[{"kind":"robot","label":"Measuring robot trajectory during Throw 3","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\nspec = json.load(open(\"/tmp/spec.json\"))\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    return cx + fx * ((rel @ right) / (rel @ fwd)), cy - fy * ((rel @ up) / (rel @ fwd))\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=-0.5, y_center=0.0, radius=0.6, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nxc, yc = -0.58, -0.24\nfor i in range(0, 51, 5):\n    iv = np.array(Image.open(f\"/tmp/step_8_3/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_8_3/frames/side/{i:03d}.jpg\"))\n    xc, yc, s = locate_robot(iv, isd, xc, yc, radius=0.5, step=0.02)\n    print(f\"t={5.8 + i*0.05:.2f}s (frame {i:03d}): x={xc:.2f}, y={yc:.2f}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=5.80s (frame 000): x=-0.58, y=-0.24\r\nt=6.05s (frame 005): x=-0.58, y=-0.46\r\nt=6.30s (frame 010): x=-0.44, y=-0.52\r\nt=6.55s (frame 015): x=-0.38, y=-0.50\r\nt=6.80s (frame 020): x=-0.24, y=-0.28\r\nt=7.05s (frame 025): x=-0.26, y=-0.22\r\nt=7.30s (frame 030): x=-0.08, y=0.08\r\nt=7.55s (frame 035): x=-0.04, y=0.20\r\nt=7.80s (frame 040): x=0.04, y=0.36\r\nt=8.05s (frame 045): x=0.10, y=0.52\r\nt=8.30s (frame 050): x=0.10, y=0.72","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":25,"t":601.0,"say":"","calls":[{"kind":"robot","label":"Running through Throw 4 (t=8.3s to 10.8s)","code":"python3 -c '\nimport sys, json, numpy as np\nsys.path.insert(0, \"/opt/tools\")\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nupper = [0.0, 0.0, 0.0,  0.0, 0.2, 0.0, 0.2, 0.0, 0.0, 0.0,  0.0, -0.2, 0.0, 0.2, 0.0, 0.0, 0.0]\nrow1 = [-0.8, 0.25, 0.25] + upper + [0.0, 0.0]\nrow2 = [-0.8, 0.25, 0.0] + upper + [0.0, 0.0]\nA = np.vstack([np.tile(row1, (50, 1)), np.tile(row2, (200, 1))])\nres = r.submit(\"walk_falcon\", A, dt=0.01, interpolate=\"hold\", cameras=[\"venue\", \"side\"], video_fps=20, video=\"frames\")\nres.save(\"/tmp/step_10_8\")\nprint(\"sim_time_s:\", res.meta[\"sim_time_s\"], \"done:\", res.done, \"reason:\", res.meta[\"reason\"], \"meta:\", {k: res.meta.get(k) for k in [\"outcome\", \"stages_reached\", \"stages_total\"]})\nlayout = spec[\"proprio_layout\"]\nqw = res.proprio[:, layout.index(\"imu_pelvis_qw\")]\nqx = res.proprio[:, layout.index(\"imu_pelvis_qx\")]\nqy = res.proprio[:, layout.index(\"imu_pelvis_qy\")]\nqz = res.proprio[:, layout.index(\"imu_pelvis_qz\")]\nyaws = np.arctan2(2*(qw*qz + qx*qy), 1 - 2*(qy*qy + qz*qz))\nprint(\"yaws (deg):\", np.round(np.rad2deg(yaws[::5]), 1))\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nsim_time_s: 10.8 done: False reason: None meta: {'outcome': None, 'stages_reached': None, 'stages_total': None}\r\nyaws (deg): [82.1 87.2 80.7 86.3 88.  89.7 90.5 92.9 92.3 94.4 94.3]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":26,"t":622.0,"say":"","calls":[{"kind":"robot","label":"Measuring robot trajectory during Throw 4","code":"python3 -c '\nimport json, numpy as np\nfrom PIL import Image\nspec = json.load(open(\"/tmp/spec.json\"))\ndef project_points(pts_3d, cam_name):\n    cam = spec[\"cameras\"][cam_name]\n    H, W = cam[\"hw\"]\n    fovy = np.deg2rad(cam[\"fovy_deg\"])\n    fy = (H / 2.0) / np.tan(fovy / 2.0)\n    fx = fy\n    cx, cy = W / 2.0, H / 2.0\n    pos = np.array(cam[\"pose_t0\"][\"position_m\"])\n    fwd = np.array(cam[\"pose_t0\"][\"forward\"])\n    right = np.array(cam[\"pose_t0\"][\"right\"])\n    fwd = fwd / np.linalg.norm(fwd)\n    right = right / np.linalg.norm(right)\n    up = np.cross(right, fwd)\n    rel = pts_3d - pos\n    return cx + fx * ((rel @ right) / (rel @ fwd)), cy - fy * ((rel @ up) / (rel @ fwd))\n\nbg = {}\nfor cname in [\"venue\", \"side\"]:\n    img0 = np.array(Image.open(f\"/tmp/obs_t0/last/{cname}.jpg\"), dtype=np.float32)\n    zs = np.linspace(0.0, 1.4, 15)\n    pts0 = np.column_stack([np.zeros_like(zs), np.zeros_like(zs), zs])\n    u0, v0 = project_points(pts0, cname)\n    umin, umax = int(u0.min()) - 12, int(u0.max()) + 12\n    vmin, vmax = int(v0.min()) - 6, int(v0.max()) + 6\n    clean = img0.copy()\n    for v in range(vmin, vmax + 1):\n        left_px, right_px = clean[v, umin - 1], clean[v, umax + 1]\n        for u in range(umin, umax + 1):\n            alpha = (u - umin) / float(umax - umin + 1)\n            clean[v, u] = (1 - alpha) * left_px + alpha * right_px\n    bg[cname] = clean\n\ndef locate_robot(img_venue, img_side, x_center=0.1, y_center=0.7, radius=0.6, step=0.02):\n    xs = np.arange(x_center - radius, x_center + radius + 1e-6, step)\n    ys = np.arange(y_center - radius, y_center + radius + 1e-6, step)\n    XX, YY = np.meshgrid(xs, ys, indexing=\"ij\")\n    pts_xy = np.column_stack([XX.ravel(), YY.ravel()])\n    N = len(pts_xy)\n    zs = np.array([0.2, 0.4, 0.6, 0.8, 1.0, 1.2])\n    scores = np.zeros(N, dtype=np.float32)\n    for cname, img in [(\"venue\", img_venue), (\"side\", img_side)]:\n        diff = np.abs(img.astype(np.float32) - bg[cname]).mean(axis=-1)\n        for z in zs:\n            pts = np.column_stack([pts_xy[:, 0], pts_xy[:, 1], np.full(N, z)])\n            u, v = project_points(pts, cname)\n            ui = np.clip(np.round(u).astype(int), 0, diff.shape[1] - 1)\n            vi = np.clip(np.round(v).astype(int), 0, diff.shape[0] - 1)\n            for dv in (-1, 0, 1):\n                for du in (-1, 0, 1):\n                    scores += diff[np.clip(vi + dv, 0, diff.shape[0]-1), np.clip(ui + du, 0, diff.shape[1]-1)]\n    best = np.argmax(scores)\n    return pts_xy[best, 0], pts_xy[best, 1], scores[best]\n\nxc, yc = 0.10, 0.72\nfor i in range(0, 51, 5):\n    iv = np.array(Image.open(f\"/tmp/step_10_8/frames/venue/{i:03d}.jpg\"))\n    isd = np.array(Image.open(f\"/tmp/step_10_8/frames/side/{i:03d}.jpg\"))\n    xc, yc, s = locate_robot(iv, isd, xc, yc, radius=0.5, step=0.02)\n    print(f\"t={8.3 + i*0.05:.2f}s (frame {i:03d}): x={xc:.2f}, y={yc:.2f}\")\n'"}],"out":{"text":"The command exited with code 0.\nOutput:\nt=8.30s (frame 000): x=0.10, y=0.72\r\nt=8.55s (frame 005): x=0.28, y=0.94\r\nt=8.80s (frame 010): x=0.28, y=0.94\r\nt=9.05s (frame 015): x=0.24, y=0.78\r\nt=9.30s (frame 020): x=0.14, y=0.54\r\nt=9.55s (frame 025): x=0.08, y=0.34\r\nt=9.80s (frame 030): x=0.16, y=0.16\r\nt=10.05s (frame 035): x=-0.02, y=-0.10\r\nt=10.30s (frame 040): x=0.08, y=-0.24\r\nt=10.55s (frame 045): x=0.00, y=-0.48\r\nt=10.80s (frame 050): x=-0.04, y=-0.68","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":27,"t":643.0,"say":"This request was blocked by Gemini's filters. They can occasionally trigger by mistake on safe coding, security, or biology-related queries. Please try rephrasing your prompt. You can [send feedback](https://ai.google.dev/gemini-api/docs/troubleshooting#file-bug) or read more about [our policies here](https://policies.google.com/terms/generative-ai/use-policy).","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}}]}