Add files using upload-large-folder tool

runs/embodied-olympics-fun-snowboard-i00-standard--sgn4jtj.json

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+{"slug":"embodied-olympics-fun-snowboard-i00-standard--sgn4jtj","task":"embodied-olympics-fun-snowboard-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":949,"sim_steps":949,"calls":21,"rows":949,"resets":0,"reset_budget":5,"sim_startups":1,"elapsed_s":1069.1,"video_rendered":1,"first_success":0,"first_reason_code":2,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0.0,"peak_memory_gb":0.511,"peak_processes":7,"peak_disk_gb":0.336,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":1372,"tokens":{"in":3917363,"cached":3596760,"out":63377,"usd":2.1},"task_text":"","step_times":"recorded","sim_total":{"submit":7,"reset":0},"replay":"embodied-olympics-fun-snowboard-i00-standard--sgn4jtj/replay.mp4","replay_last":"embodied-olympics-fun-snowboard-i00-standard--sgn4jtj/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"Checking directory contents and limits","code":"ls -la /app /opt /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 22:03 ..\r\ndrwxr-xr-x 2 root root 4096 Oct 19 06:15 output\r\n\r\n/opt:\r\ntotal 12\r\ndrwxr-xr-x 1 root root 4096 Oct 19 06:15 .\r\ndrwxr-xr-x 1 root root 4096 Oct 24 22:03 ..\r\ndrwxr-xr-x 2 root root 4096 Oct 19 06:15 tools\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\": 1792879390.01,\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\": \"2026-10-25T00:02:50Z\"\r\n}","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":10.0,"say":"","calls":[{"kind":"shell","label":"Fetching robot spec and status","code":"python3 -c \"\nimport json\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nstatus = r.status()\nwith open('/tmp/spec.json', 'w') as f:\n    json.dump(spec, f, indent=2)\nprint('STATUS:', json.dumps(status, indent=2))\nprint('SPEC KEYS:', list(spec.keys()))\n\" && head -n 120 /tmp/spec.json"}],"out":{"text":"The command exited with code 0.\nOutput:\nSTATUS: {\r\n  \"calls\": 0,\r\n  \"rows\": 0,\r\n  \"control_steps\": 0,\r\n  \"done\": false,\r\n  \"reason\": null,\r\n  \"episode\": 1,\r\n  \"control_steps_total\": 0,\r\n  \"resets_left\": 5,\r\n  \"elapsed_s\": 0.0\r\n}\r\nSPEC KEYS: ['protocol', 'control_dt', 'max_control_steps', 'max_chunk_s', 'max_watch_s', 'max_video_fps', 'max_frames_per_call', 'proprio_layout', 'budget', 'clock', 'on_service_error', 'simulator', 'robot', 'task_text', 'rules', 'episode', 'action_types', 'start_command', 'units', 'cameras', 'depth', 'robot_facts', 'proprio', 'referee', 'reset']\r\n{\r\n  \"protocol\": \"eai-standard/2.1\",\r\n  \"control_dt\": 0.01,\r\n  \"max_control_steps\": 9000,\r\n  \"max_chunk_s\": 10.0,\r\n  \"max_watch_s\": 30.0,\r\n  \"max_video_fps\": 30,\r\n  \"max_frames_per_call\": 3000,\r\n  \"proprio_layout\": [\r\n    \"left_hip_pitch_pos\",\r\n    \"left_hip_roll_pos\",\r\n    \"left_hip_yaw_pos\",\r\n    \"left_knee_pos\",\r\n    \"left_ankle_pitch_pos\",\r\n    \"left_ankle_roll_pos\",\r\n    \"right_hip_pitch_pos\",\r\n    \"right_hip_roll_pos\",\r\n    \"right_hip_yaw_pos\",\r\n    \"right_knee_pos\",\r\n    \"right_ankle_pitch_pos\",\r\n    \"right_ankle_roll_pos\",\r\n    \"waist_yaw_pos\",\r\n    \"waist_roll_pos\",\r\n    \"waist_pitch_pos\",\r\n    \"left_shoulder_pitch_pos\",\r\n    \"left_shoulder_roll_pos\",\r\n    \"left_shoulder_yaw_pos\",\r\n    \"left_elbow_pos\",\r\n    \"left_wrist_roll_pos\",\r\n    \"left_wrist_pitch_pos\",\r\n    \"left_wrist_yaw_pos\",\r\n    \"right_shoulder_pitch_pos\",\r\n    \"right_shoulder_roll_pos\",\r\n    \"right_shoulder_yaw_pos\",\r\n    \"right_elbow_\n… (997 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":19.0,"say":"","calls":[{"kind":"shell","label":"reads spec.json","code":"/tmp/spec.json"}],"out":{"text":"File Path: `file:///tmp/spec.json`\nTotal Lines: 1658\nTotal Bytes: 38088\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… (21,934 characters left out) …\n37.0,\n854:         37.0,\n855:         37.0,\n856:         37.0,\n857:         37.0,\n858:         37.0,\n859:         22.0,\n860:         22.0,\n861:         37.0,\n862:         37.0,\n863:         37.0,\n864:         37.0,\n865:         37.0,\n866:         22.0,\n867:         22.0,\n868:         88.0,\n869:         139.0,\n870:         88.0,\n871:         139.0,\n872:         50.0,\n873:         50.0,\n874:         88.0,\n875:         139.0,\n876:         88.0,\n877:         139.0,\n878:         50.0,\n879:         50.0,\n880:         88.0,\n881:         50.0,\n882:         50.0,\n883:         25.0,\n884:         25.0,\n885:         25.0,\n886:         25.0,\n887:         25.0,\n888:         5.0,\n889:         5.0,\n890:         25.0,\n891:         25.0,\n892:         25.0,\n893:         25.0,\n894:         25.0,\n895:         5.0,\n896:         5.0,\n897:         1000.0,\n898:         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.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":5,"t":23.0,"say":"","calls":[{"kind":"shell","label":"reads spec.json","code":"/tmp/spec.json"}],"out":{"text":"File Path: `file:///tmp/spec.json`\nTotal Lines: 1658\nTotal Bytes: 38088\nShowing lines 921 to 1658\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… (16,254 characters left out) …\n      ]\n1646:     ],\n1647:     \"grip\": {\n1648:       \"reach_m\": 0.035,\n1649:       \"max_relative_speed_m_s\": 6.0,\n1650:       \"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\"\n1651:     }\n1652:   },\n1653:   \"proprio\": {\n1654:     \"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\"\n1655:   },\n1656:   \"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']\",\n1657:   \"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\"\n1658: }\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":27.0,"say":"","calls":[{"kind":"robot","label":"Getting initial observations and checking packages","code":"python3 -c \"\nfrom rcb_client import Robot\nimport json, numpy as np\nfrom PIL import Image\n\nr = Robot()\nobs = r.get_obs(cameras=['head_left', 'head_right', 'venue'], seconds=0, include_depth=True)\nprint('META keys:', list(obs.meta.keys()))\nprint('META without proprio:', {k: v for k, v in obs.meta.items() if k != 'proprio'})\nprop = obs.meta['proprio']['now']\nspec = r.spec()\nlayout = spec['proprio_layout']\nfor k, v in zip(layout, prop):\n    if 'imu' in k or 'pos' in k or k in ['holding_left', 'holding_right', 'mode', 'time_s']:\n        print(f'{k}: {v:.4f}')\nfor cam, img in obs.last.items():\n    Image.fromarray(img).save(f'/tmp/{cam}_t0.png')\n    print(f'Saved /tmp/{cam}_t0.png shape={img.shape}')\n\" && pip list"}],"out":{"text":"The command exited with code 0.\nOutput:\nMETA keys: ['calls', 'rows', 'control_steps', 'done', 'reason', 'episode', 'control_steps_total', 'resets_left', 'sim_time_s', 'time_s', 'time_left_s', 'proprio', 'obs_id', 'seconds', 'control_steps_watch', 'ok']\r\nMETA without proprio: {'calls': 1, 'rows': 0, 'control_steps': 0, 'done': False, 'reason': None, 'episode': 1, 'control_steps_total': 0, 'resets_left': 5, 'sim_time_s': 0.0, 'time_s': 21.16, 'time_left_s': 7178.8, 'obs_id': 1, 'seconds': 0.0, 'control_steps_watch': 0, 'ok': True}\r\nleft_hip_pitch_pos: -0.1000\r\nleft_hip_roll_pos: 0.1398\r\nleft_hip_yaw_pos: 0.0000\r\nleft_knee_pos: 0.3000\r\nleft_ankle_pitch_pos: -0.2000\r\nleft_ankle_roll_pos: -0.1398\r\nright_hip_pitch_pos: -0.1469\r\nright_hip_roll_pos: -0.1103\r\nright_hip_yaw_pos: 0.0759\r\nright_knee_pos: 0.3515\r\nright_ankle_pitch_pos: -0.2137\r\nright_ankle_roll_pos: 0.1232\r\nwaist_yaw_pos: 0.0000\r\nwaist_roll_pos: 0.0000\r\nwaist_pitch_pos: 0.0000\r\nleft_shoulder_pitch_pos: 0.2000\r\nleft_shoulder_roll_pos: 0.2000\r\nleft_shoulder_yaw_pos: 0.0000\r\nleft_elbow_pos: 1.2800\r\nleft_wrist_roll_pos: 0.0000\r\nleft_wrist_pitch_pos: 0.0000\r\nleft_wrist_yaw_pos: 0.0000\r\nright_shoulder_pitch_pos: 0.2000\r\nright_shoulder_roll_pos: -0.2000\r\nright_shoulder_yaw_pos: 0.0000\r\nright_elbow_pos: 1.2800\r\nright_wrist_roll_pos: 0.0000\r\nright_wrist_pitch_pos: 0.0000\r\nright_wrist_yaw_pos: 0.0000\r\nimu_pelvis_qw: 0.6981\r\nimu_pelvis_qx: -0.1124\r\nimu_pelvis_qy: 0.1124\r\nimu_pelvis_qz: -0.6981\r\nimu_pelvis_gx: 0.0000\r\nimu_pelvis_gy: 0.0000\r\nimu_pelvis_gz: 0.0000\r\nimu_pelvis_ax: 0.0000\r\nimu_pelvis_ay: -0.0000\r\nimu_pelvis_az: 0.0000\r\nimu_torso_qw: 0.6981\r\nimu_torso_qx: -0.1124\r\nimu_torso_qy: 0.1124\r\nimu_torso_qz: -0.6981\r\nimu_torso_gx: 0.0000\r\nimu_torso_gy: 0.0000\r\nimu_torso_gz: 0.0000\r\nimu_torso_ax: -0.0000\r\nimu_torso_ay: 0.0000\r\nimu_torso_az: 0.0000\r\nholding_left: 0.0000\r\nholding_right: 0.0000\r\nmode: 0.0000\r\ntime_s: 0.0000\r\nSaved /tmp/head_left_t0.png shape=(270, 480, 3)\r\nSaved /tmp/head_right_t0.png shape=(270, 480, 3)\r\nSaved /tmp/venue_t0.png shape=(270, 480, 3)\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":7,"t":40.0,"say":"","calls":[{"kind":"look","label":"venue_t0.png","code":"/tmp/venue_t0.png"},{"kind":"look","label":"head_left_t0.png","code":"/tmp/head_left_t0.png"},{"kind":"robot","label":"Printing full initial proprioception state","code":"python3 -c \"\nfrom rcb_client import Robot\nr = Robot()\nobs = r.get_obs(cameras=[], seconds=0)\nprop = obs.meta['proprio']['now']\nspec = r.spec()\nfor i, (k, v) in enumerate(zip(spec['proprio_layout'], prop)):\n    print(f'{i:3d} {k:30s}: {v:10.4f}')\n\""}],"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 command exited with code 0.\nOutput:\n  0 left_hip_pitch_pos            :    -0.1000\r\n  1 left_hip_roll_pos             :     0.1398\r\n  2 left_hip_yaw_pos              :     0.0000\r\n  3 left_knee_pos                 :     0.3000\r\n  4 left_ankle_pitch_pos          :    -0.2000\r\n  5 left_ankle_roll_pos           :    -0.1398\r\n  6 right_hip_pitch_pos           :    -0.1469\r\n  7 right_hip_roll_pos            :    -0.1103\r\n  8 right_hip_yaw_pos             :     0.0759\r\n  9 right_knee_pos                :     0.3515\r\n 10 right_ankle_pitch_pos         :    -0.2137\r\n 11 right_ankle_roll_pos          :     0.1232\r\n 12 waist_yaw_pos                 :     0.0000\r\n 13 waist_roll_pos                :     0.0000\r\n 14 waist_pitch_pos               :     0.0000\r\n 15 left_shoulder_pitch_pos       :     0.2000\r\n 16 left_shoulder_roll_pos        :     0.2000\r\n 17 left_shoulder_yaw_pos         :     0.0000\r\n 18 left_elbow_pos                :     1.2800\r\n 19 left_wrist_roll_pos           :     0.0000\r\n 20 left_wrist_pitch_pos          :     0.0000\r\n 21 left_wrist_yaw_pos            :     0.0000\r\n 22 right_shoulder_pitch_pos      :     0.2000\r\n 23 right_shoulder_roll_pos       :    -0.2000\r\n 24 right_shoulder_yaw_pos        :     0.0000\r\n 25 right_elbow_pos               :     1.2800\r\n 26 right_wrist_roll_pos          :     0.0000\r\n 27 right_wrist_pitch_pos \n… (4,040 characters left out) …\n:     0.0000\r\n112 right_elbow_target            :     1.2800\r\n113 right_wrist_roll_target       :     0.0000\r\n114 right_wrist_pitch_target      :     0.0000\r\n115 right_wrist_yaw_target        :     0.0000\r\n116 imu_pelvis_qw                 :     0.6981\r\n117 imu_pelvis_qx                 :    -0.1124\r\n118 imu_pelvis_qy                 :     0.1124\r\n119 imu_pelvis_qz                 :    -0.6981\r\n120 imu_pelvis_gx                 :     0.0000\r\n121 imu_pelvis_gy                 :     0.0000\r\n122 imu_pelvis_gz                 :     0.0000\r\n123 imu_pelvis_ax                 :     0.0000\r\n124 imu_pelvis_ay                 :    -0.0000\r\n125 imu_pelvis_az                 :     0.0000\r\n126 imu_torso_qw                  :     0.6981\r\n127 imu_torso_qx                  :    -0.1124\r\n128 imu_torso_qy                  :     0.1124\r\n129 imu_torso_qz                  :    -0.6981\r\n130 imu_torso_gx                  :     0.0000\r\n131 imu_torso_gy                  :     0.0000\r\n132 imu_torso_gz                  :     0.0000\r\n133 imu_torso_ax                  :    -0.0000\r\n134 imu_torso_ay                  :     0.0000\r\n135 imu_torso_az                  :     0.0000\r\n136 holding_left                  :     0.0000\r\n137 holding_right                 :     0.0000\r\n138 mode                          :     0.0000\r\n139 cmd_vx                        :     0.0000\r\n140 cmd_vy                        :     0.0000\r\n141 cmd_wz                        :     0.0000\r\n142 time_s                        :     0.0000","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":50.0,"say":"","calls":[{"kind":"shell","label":"Reading rcb_client.py and searching container files","code":"cat /opt/tools/rcb_client.py && find / -name \"*olympics*\" -o -name \"*g1*\" -o -name \"*mujoco*\" 2>/dev/null"}],"out":{"text":"The command exited with code 0.\nOutput:\n<truncated 38 lines>\n    res.last[cam]            uint8 H x W x 3: the last frame, always\r\n    res.frames[cam]          uint8 N x H x W x 3 (video=\"frames\"/\"both\")     res.video[cam]   mp4 bytes\r\n    res.depth[cam]           float16 N x H x W, metres, 0 = nothing in range (include_depth)\r\n    res.proprio              float32 rows of spec()[\"proprio_layout\"]: one at the call's start, one every 1/video_fps s,\r\n                             one at its end\r\n    res.done                 the episode is over\r\n    res.save(dir)            meta.json, <cam>.mp4, last/<cam>.jpg, frames/<cam>/NNN.jpg, depth_<cam>.npy, proprio.npy\r\n\r\nErrors: ValueError -- refused, nothing ran (400: wrong type or shape, NaN, a bad dt, too many frames, an unknown\r\ncamera; or a request over 64 MB, refused before it is sent); EpisodeOver -- the episode, or the trial, is over (409);\r\nRuntimeError -- the service failed (5xx: see spec()[\"on_service_error\"]) or the endpoint does not exist in this run\r\n(404).\r\n\"\"\"\r\nfrom __future__ import annotations\r\n\r\nimport json\r\nimport os\r\nimport pathlib\r\nimport time\r\n\r\nimport numpy as np\r\nimport requests\r\n\r\nimport rcb1\r\n\r\nPROTOCOLS = (\"eai-standard/2.\", \"rcb-limited/2.\")   # any 2.x service, under either name (rcb-limited is the old one)\r\nMAX_BODY = 64 * 1024 * 1024                          # the protocol's request limit: a larger request is refused\r\n\r\n\r\nclass EpisodeOver(RuntimeError):\r\n    pass\r\n\r\n\r\nclass Result:\r\n    \"\"\"A decoded RCB1 \n… (5,105 characters left out) …\n/x-rcb1\"},\r\n                          timeout=(5, timeout))\r\n        if r.headers.get(\"Content-Type\", \"\").startswith(\"application/x-rcb1\") and r.status_code == 200:\r\n            return Result(*rcb1.decode(r.content))\r\n        try:\r\n            err = r.json()\r\n        except ValueError:\r\n            err = {\"error\": r.text[:300]}\r\n        msg = f\"{r.status_code} {path}: {err.get('error')}\" + (f\" ({err['detail']})\" if err.get(\"detail\") else \"\")\r\n        if r.status_code == 409:\r\n            raise EpisodeOver(msg + (f\"; reason {err['reason']}\" if err.get(\"reason\") else \"\")\r\n                              + (f\"; resets_left {err['resets_left']}\" if \"resets_left\" in err else \"\"))\r\n        if r.status_code in (400, 413):\r\n            raise ValueError(msg)\r\n        raise RuntimeError(msg)\r\n\r\n\r\ndef _names(cameras) -> list[str] | None:\r\n    return None if cameras is None else [cameras] if isinstance(cameras, str) else list(cameras)\r\n/usr/local/lib/python3.12/site-packages/pillow.libs/libpng16-abb096d5.so.16.58.0\r\n/usr/local/lib/python3.12/site-packages/numpy/_core/tests…\r\n/usr/local/lib/python3.12/site-packages/numpy/_core/tests…\r\n/usr/local/lib/python3.12/site-packages/scipy/sparse/tests/__pycache__/test_indexing1d.cpython-312.pyc\r\n/usr/local/lib/python3.12/site-packages/scipy/sparse/tests/test_indexing1d.py\r\n/usr/local/lib/python3.12/site-packages/scipy/special/tests/__pycache__/test_log1mexp.cpython-312.pyc\r\n/usr/local/lib/python3.12/site-packages/scipy/special/tests/test_log1mexp.py","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":71.0,"say":"","calls":[{"kind":"shell","label":"Analyzing initial IMU orientation","code":"python3 -c \"\nimport numpy as np\nfrom scipy.spatial.transform import Rotation as R\n\nq = [-0.1124, 0.1124, -0.6981, 0.6981] # scipy uses [x, y, z, w]\nrot = R.from_quat(q)\nprint('Rotation matrix (world from sensor):')\nprint(np.round(rot.as_matrix(), 4))\nprint('Euler XYZ (deg):', np.round(rot.as_euler('xyz', degrees=True), 2))\nprint('Euler ZYX (yaw, pitch, roll deg):', np.round(rot.as_euler('zyx', degrees=True), 2))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nRotation matrix (world from sensor):\r\n[[ 0.      0.9495  0.3139]\r\n [-1.      0.      0.    ]\r\n [ 0.     -0.3139  0.9495]]\r\nEuler XYZ (deg): [-18.29   0.   -90.  ]\r\nEuler ZYX (yaw, pitch, roll deg): [-90.    18.29  -0.  ]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":126.0,"say":"","calls":[{"kind":"robot","label":"Analyzing depth image from head_left at t=0","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\n\nr = Robot()\nobs = r.get_obs(cameras=['head_left', 'venue'], seconds=0, include_depth=True)\nd = obs.depth['head_left'][0]\nprint('Depth shape:', d.shape, 'min:', d.min(), 'max:', d.max())\n# Sample depth across vertical and horizontal lines\nfor v in [50, 100, 135, 180, 220, 260]:\n    row = d[v, [60, 140, 240, 340, 420]]\n    print(f'row {v:3d}:', [round(float(x), 3) for x in row])\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDepth shape: (270, 480) min: 0.0 max: 10.0\r\nrow  50: [0.0, 2.365, 0.0, 0.0, 0.0]\r\nrow 100: [3.994, 4.297, 6.621, 0.0, 0.0]\r\nrow 135: [2.561, 2.928, 4.023, 6.648, 0.0]\r\nrow 180: [1.869, 2.123, 2.676, 3.627, 5.066]\r\nrow 220: [1.528, 1.709, 2.061, 2.582, 3.238]\r\nrow 260: [1.298, 1.439, 1.676, 2.006, 2.381]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":11,"t":165.0,"say":"","calls":[{"kind":"robot","label":"Reconstructing 3D points from head_left depth","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\n\nr = Robot()\nspec = r.spec()\ncam = spec['cameras']['head_left']\nobs = r.get_obs(cameras=['head_left'], seconds=0, include_depth=True)\nd = obs.depth['head_left'][0].astype(np.float64)\nH, W = d.shape\nfovy = np.deg2rad(cam['fovy_deg'])\nfy = (H / 2.0) / np.tan(fovy / 2.0)\nfx = fy\npos = np.array(cam['pose_t0']['position_m'])\nfwd = np.array(cam['pose_t0']['forward'])\nup = np.array(cam['pose_t0']['up'])\nright = np.array(cam['pose_t0']['right'])\n\n# Check a few pixels on the floor (row 250, cols 100..400)\npts = []\nfor v in range(200, 265, 10):\n    for u in range(50, 430, 20):\n        z = d[v, u]\n        if 0.5 < z < 8.0:\n            x_cam = (u - W/2.0) / fx * z\n            y_cam = -(v - H/2.0) / fy * z\n            p = pos + z * fwd + x_cam * right + y_cam * up\n            pts.append((u, v, z, p[0], p[1], p[2]))\npts = np.array(pts)\nprint('Sample 3D points in pose_t0 frame (u, v, depth, X, Y, Z):')\nfor row in pts[:15]:\n    print(f'u={row[0]:3.0f} v={row[1]:3.0f} d={row[2]:.2f} -> X={row[3]:6.3f}, Y={row[4]:6.3f}, Z={row[5]:6.3f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nSample 3D points in pose_t0 frame (u, v, depth, X, Y, Z):\r\nu= 50 v=200 d=1.66 -> X= 1.483, Y= 1.080, Z= 0.591\r\nu= 70 v=200 d=1.70 -> X= 1.518, Y= 0.970, Z= 0.601\r\nu= 90 v=200 d=1.75 -> X= 1.559, Y= 0.857, Z= 0.608\r\nu=110 v=200 d=1.80 -> X= 1.604, Y= 0.737, Z= 0.615\r\nu=130 v=200 d=1.86 -> X= 1.657, Y= 0.612, Z= 0.617\r\nu=150 v=200 d=1.93 -> X= 1.709, Y= 0.477, Z= 0.623\r\nu=170 v=200 d=2.01 -> X= 1.778, Y= 0.334, Z= 0.619\r\nu=190 v=200 d=2.09 -> X= 1.848, Y= 0.178, Z= 0.620\r\nu=210 v=200 d=2.18 -> X= 1.924, Y= 0.009, Z= 0.619\r\nu=230 v=200 d=2.28 -> X= 2.005, Y=-0.176, Z= 0.620\r\nu=250 v=200 d=2.38 -> X= 2.096, Y=-0.377, Z= 0.620\r\nu=270 v=200 d=2.50 -> X= 2.196, Y=-0.598, Z= 0.620\r\nu=290 v=200 d=2.63 -> X= 2.305, Y=-0.843, Z= 0.620\r\nu=310 v=200 d=2.77 -> X= 2.426, Y=-1.113, Z= 0.620\r\nu=330 v=200 d=2.93 -> X= 2.560, Y=-1.414, Z= 0.621","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":222.0,"say":"","calls":[{"kind":"shell","label":"Cropping and zooming in on robot at t=0","code":"python3 -c \"\nfrom PIL import Image\nimg = Image.open('/tmp/venue_t0.png')\ncrop = img.crop((0, 110, 120, 260)).resize((480, 600), Image.NEAREST)\ncrop.save('/tmp/robot_zoom_t0.png')\n\""}],"out":{"text":"The command exited with code 0.\nStdout:\n\nStderr:","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":236.0,"say":"","calls":[{"kind":"look","label":"robot_zoom_t0.png","code":"/tmp/robot_zoom_t0.png"}],"out":{"text":"The 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":14,"t":248.0,"say":"","calls":[{"kind":"robot","label":"Checking 3D surface geometry from depth map","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\n\nr = Robot()\nspec = r.spec()\ncam = spec['cameras']['head_left']\nobs = r.get_obs(cameras=['head_left'], seconds=0, include_depth=True)\nd = obs.depth['head_left'][0].astype(np.float64)\nH, W = d.shape\nfovy = np.deg2rad(cam['fovy_deg'])\nfy = (H / 2.0) / np.tan(fovy / 2.0)\nfx = fy\npos = np.array(cam['pose_t0']['position_m'])\nfwd = np.array(cam['pose_t0']['forward'])\nup = np.array(cam['pose_t0']['up'])\nright = np.array(cam['pose_t0']['right'])\n\n# Let's check v=120..260 across u=20..460\nfor u in [40, 120, 200, 280, 360, 440]:\n    line = []\n    for v in [120, 160, 200, 240]:\n        z = d[v, u]\n        if z > 0:\n            x_cam = (u - W/2.0) / fx * z\n            y_cam = -(v - H/2.0) / fy * z\n            p = pos + z * fwd + x_cam * right + y_cam * up\n            line.append(f'v={v}:({p[0]:.2f},{p[1]:.2f},{p[2]:.2f})')\n    print(f'u={u:3d}: ' + '  '.join(line))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nu= 40: v=120:(2.90,2.19,0.38)  v=160:(1.94,1.48,0.54)  v=200:(1.47,1.13,0.59)  v=240:(1.16,0.91,0.60)\r\nu=120: v=120:(2.58,1.15,0.82)  v=160:(2.18,0.93,0.60)  v=200:(1.63,0.68,0.62)  v=240:(1.28,0.51,0.62)\r\nu=200: v=120:(3.98,0.43,0.62)  v=160:(2.61,0.21,0.62)  v=200:(1.88,0.09,0.62)  v=240:(1.44,0.02,0.62)\r\nu=280: v=120:(5.81,-1.31,0.62)  v=160:(3.32,-0.89,0.62)  v=200:(2.25,-0.72,0.62)  v=240:(1.65,-0.62,0.62)\r\nu=360: v=160:(4.59,-2.86,0.62)  v=200:(2.80,-1.94,0.62)  v=240:(1.95,-1.50,0.62)\r\nu=440: v=200:(3.71,-3.98,0.62)  v=240:(2.37,-2.78,0.62)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":15,"t":271.0,"say":"","calls":[{"kind":"edit","label":"NOTES.md","code":"/app/NOTES.md\n\n# Approach & Notes\n- Task: Embodied Olympics Snowboard Parallel Slalom (18 gates, 256m slope at 18.3 deg).\n- Initial inspection: Robot stands on snowboard at start platform (0.3m behind start line).\n- Control strategy: Closed-loop balance and steering controller using proprioception (IMU + joint states) and visual/depth feedback.\n- Packages installed: None yet (using pre-installed numpy, scipy, pillow, requests).\n"},{"kind":"edit","label":"NOTES.md","code":"/app/output/NOTES.md\n\n# Approach & Notes\n- Task: Embodied Olympics Snowboard Parallel Slalom (18 gates, 256m slope at 18.3 deg).\n- Initial inspection: Robot stands on snowboard at start platform (0.3m behind start line).\n- Control strategy: Closed-loop balance and steering controller using proprioception (IMU + joint states) and visual/depth feedback.\n- Packages installed: None yet (using pre-installed numpy, scipy, pillow, requests).\n"},{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n#!/usr/bin/env python3\n\"\"\"Snowboard parallel slalom controller for Unitree G1.\"\"\"\nfrom rcb_client import Robot\n\n\ndef main():\n    r = Robot()\n    print(\"Status:\", r.status())\n\n\nif __name__ == \"__main__\":\n    main()\n"}],"out":{"text":"Created 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.\nCreated 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/output/gen.py 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":16,"t":406.0,"say":"","calls":[{"kind":"robot","label":"Stepping Episode 1 by 0.2s in stand mode","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nstart_row = spec['start_command']['row']\nres = r.submit('stand', [start_row]*20, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=30, include_depth=True)\nprint('Done:', res.done, 'Meta:', {k: v for k, v in res.meta.items() if k != 'proprio'})\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\nfor row in res.proprio:\n    t = row[idx['time_s']]\n    qw, qx, qy, qz = row[idx['imu_pelvis_qw']], row[idx['imu_pelvis_qx']], row[idx['imu_pelvis_qy']], row[idx['imu_pelvis_qz']]\n    gx, gy, gz = row[idx['imu_pelvis_gx']], row[idx['imu_pelvis_gy']], row[idx['imu_pelvis_gz']]\n    ax, ay, az = row[idx['imu_pelvis_ax']], row[idx['imu_pelvis_ay']], row[idx['imu_pelvis_az']]\n    l_hr = row[idx['left_hip_roll_pos']]\n    r_hr = row[idx['right_hip_roll_pos']]\n    l_ar = row[idx['left_ankle_roll_pos']]\n    r_ar = row[idx['right_ankle_roll_pos']]\n    print(f't={t:.3f} q=({qw:.3f},{qx:.3f},{qy:.3f},{qz:.3f}) g=({gx:.2f},{gy:.2f},{gz:.2f}) a=({ax:.1f},{ay:.1f},{az:.1f}) hr=({l_hr:.3f},{r_hr:.3f}) ar=({l_ar:.3f},{r_ar:.3f})')\nfor cam, img in res.last.items():\n    Image.fromarray(img).save(f'/tmp/{cam}_t02.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: False Meta: {'calls': 6, 'rows': 20, 'control_steps': 20, 'done': False, 'reason': None, 'episode': 1, 'control_steps_total': 20, 'resets_left': 5, 'sim_time_s': 0.2, 'time_s': 431.12, 'time_left_s': 6768.9, 'chunk_id': 6, 'type': 'stand', 'executed_rows': 20, 'control_steps_chunk': 20, 'clipped': [], 'n_clipped': 0, 'ok': True}\r\nt=0.000 q=(0.698,-0.112,0.112,-0.698) g=(0.00,0.00,0.00) a=(0.0,-0.0,0.0) hr=(0.140,-0.110) ar=(-0.140,0.123)\r\nt=0.030 q=(0.702,-0.113,0.112,-0.694) g=(0.13,-0.17,0.42) a=(-1.6,-3.4,2.6) hr=(0.143,-0.109) ar=(-0.140,0.123)\r\nt=0.060 q=(0.706,-0.109,0.106,-0.691) g=(0.74,-0.10,0.27) a=(-0.8,-3.3,5.4) hr=(0.141,-0.111) ar=(-0.137,0.125)\r\nt=0.090 q=(0.710,-0.100,0.096,-0.691) g=(1.12,-0.05,0.16) a=(-0.5,-0.6,4.4) hr=(0.139,-0.113) ar=(-0.136,0.125)\r\nt=0.120 q=(0.713,-0.084,0.080,-0.691) g=(1.64,-0.06,0.05) a=(-0.2,-4.4,8.7) hr=(0.126,-0.126) ar=(-0.129,0.133)\r\nt=0.150 q=(0.716,-0.066,0.062,-0.693) g=(1.72,-0.05,0.03) a=(-0.3,-1.4,5.4) hr=(0.124,-0.128) ar=(-0.127,0.134)\r\nt=0.180 q=(0.717,-0.047,0.042,-0.694) g=(1.94,-0.05,0.03) a=(-0.1,-1.4,3.8) hr=(0.124,-0.128) ar=(-0.128,0.133)\r\nt=0.200 q=(0.718,-0.033,0.028,-0.694) g=(2.11,-0.06,0.01) a=(-0.1,-1.4,3.0) hr=(0.124,-0.128) ar=(-0.128,0.133)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":17,"t":450.0,"say":"","calls":[{"kind":"robot","label":"Checking leg targets and IMU at t=0.2s","code":"python3 -c \"\nfrom rcb_client import Robot\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nprop = obs.meta['proprio']['now']\nfor i, (k, v) in enumerate(zip(spec['proprio_layout'], prop)):\n    if 'hip' in k or 'knee' in k or 'ankle' in k or 'imu_pelvis' in k:\n        print(f'{k:30s}: {v:10.4f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nleft_hip_pitch_pos            :    -0.1027\r\nleft_hip_roll_pos             :     0.1243\r\nleft_hip_yaw_pos              :    -0.0344\r\nleft_knee_pos                 :     0.3023\r\nleft_ankle_pitch_pos          :    -0.1956\r\nleft_ankle_roll_pos           :    -0.1280\r\nright_hip_pitch_pos           :    -0.0995\r\nright_hip_roll_pos            :    -0.1275\r\nright_hip_yaw_pos             :     0.0386\r\nright_knee_pos                :     0.2929\r\nright_ankle_pitch_pos         :    -0.1898\r\nright_ankle_roll_pos          :     0.1328\r\nleft_hip_pitch_vel            :     0.0053\r\nleft_hip_roll_vel             :     0.0001\r\nleft_hip_yaw_vel              :    -0.0292\r\nleft_knee_vel                 :    -0.0625\r\nleft_ankle_pitch_vel          :     0.1181\r\nleft_ankle_roll_vel           :    -0.0117\r\nright_hip_pitch_vel           :    -0.0185\r\nright_hip_roll_vel            :     0.0075\r\nright_hip_yaw_vel             :    -0.0128\r\nright_knee_vel                :     0.0166\r\nright_ankle_pitch_vel         :     0.0675\r\nright_ankle_roll_vel          :    -0.0187\r\nleft_hip_pitch_torque         :     1.3456\r\nleft_hip_roll_torque          :   -63.9395\r\nleft_hip_yaw_torque           :    10.8230\r\nleft_knee_torque              :    -6.7225\r\nleft_ankle_pitch_torque       :     4.5966\r\nleft_ankle_roll_torque        :    50.0000\r\nright_hip_pitch_torque        :    -1.5992\r\nright_hip_roll_torque         :    73.6430\r\nright_hip_yaw_torque          :   -15.3073\r\nright_knee_torque             :     4.2387\r\nright_ankle_pitch_torque      :    -0.5720\r\nright_ankle_roll_torque       :   -49.6000\r\nleft_hip_pitch_target         :    -0.1000\r\nleft_hip_roll_target          :     0.0000\r\nleft_hip_yaw_target           :     0.0000\r\nleft_knee_target              :     0.3000\r\nleft_ankle_pitch_target       :    -0.2000\r\nleft_ankle_roll_target        :     0.0000\r\nright_hip_pitch_target        :    -0.1000\r\nright_hip_roll_target         :     0.0000\r\nright_hip_yaw_target          :     0.0000\r\nright_knee_target             :     0.3000\r\nright_ankle_pitch_target      :    -0.2000\r\nright_ankle_roll_target       :     0.0000\r\nimu_pelvis_qw                 :     0.7185\r\nimu_pelvis_qx                 :    -0.0330\r\nimu_pelvis_qy                 :     0.0277\r\nimu_pelvis_qz                 :    -0.6942\r\nimu_pelvis_gx                 :     2.1105\r\nimu_pelvis_gy                 :    -0.0606\r\nimu_pelvis_gz                 :     0.0124\r\nimu_pelvis_ax                 :    -0.0723\r\nimu_pelvis_ay                 :    -1.3702\r\nimu_pelvis_az                 :     2.9917","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":18,"t":472.0,"say":"","calls":[{"kind":"robot","label":"Stepping Episode 1 from 0.2s to 1.0s in joints mode","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nprop = obs.meta['proprio']['now']\n# Use current measured joint positions as targets in 'joints' mode\nq_init = list(prop[:29])\nrow = q_init + [0.0, 0.0]\nres = r.submit('joints', [row]*80, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=30)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'), 'Outcome:', res.meta.get('outcome'))\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\nfor p in res.proprio:\n    t = p[idx['time_s']]\n    qw, qx, qy, qz = p[idx['imu_pelvis_qw']], p[idx['imu_pelvis_qx']], p[idx['imu_pelvis_qy']], p[idx['imu_pelvis_qz']]\n    gx, gy, gz = p[idx['imu_pelvis_gx']], p[idx['imu_pelvis_gy']], p[idx['imu_pelvis_gz']]\n    ax, ay, az = p[idx['imu_pelvis_ax']], p[idx['imu_pelvis_ay']], p[idx['imu_pelvis_az']]\n    print(f't={t:.3f} q=({qw:.3f},{qx:.3f},{qy:.3f},{qz:.3f}) g=({gx:6.2f},{gy:6.2f},{gz:6.2f}) a=({ax:5.1f},{ay:5.1f},{az:5.1f})')\nfor cam, img in res.last.items():\n    Image.fromarray(img).save(f'/tmp/{cam}_t10.png')\n\""}],"out":{"text":"Tool is running as a background task with task id: 1a94ba03-4d1c-4817-a7ce-156455ee1db5/task-38\nTask Description: python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nprop = obs.meta['proprio']['now']\n# Use current measured joint positions as targets in 'joints' mode\nq_init = list(prop[:29])\nrow = q_init + [0.0, 0.0]\nres = r.submit('joints', [row]*80, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=30)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'), 'Outcome:', res.meta.get('outcome'))\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\nfor p in res.proprio:\n    t = p[idx['time_s']]\n    qw, qx, qy, qz = p[idx['imu_pelvis_qw']], p[idx['imu_pelvis_qx']], p[idx['imu_pelvis_qy']], p[idx['imu_pelvis_qz']]\n    gx, gy, gz = p[idx['imu_pelvis_gx']], p[idx['imu_pelvis_gy']], p[idx['imu_pelvis_gz']]\n    ax, ay, az = p[idx['imu_pelvis_ax']], p[idx['imu_pelvis_ay']], p[idx['imu_pelvis_az']]\n    print(f't={t:.3f} q=({qw:.3f},{qx:.3f},{qy:.3f},{qz:.3f}) g=({gx:6.2f},{gy:6.2f},{gz:6.2f}) a=({ax:5.1f},{ay:5.1f},{az:5.1f})')\nfor cam, img in res.last.items():\n    Image.fromarray(img).save(f'/tmp/{cam}_t10.png')\n\"\nTask logs are available at: file:///root/.gemini/antigravity-cli/brain/1a94ba03-4d1c-4817-a7ce-156455ee1db5/.system_generated/tasks/task-38.log\nYOU MUST TAKE ONE OF THE FOLLOWING TWO ACTIONS: A) either proceed to other relevant work (if any) or, B) simply update the user with a short message (that you have launched the command and will wait for it to finish) and end the turn.\n DO NOTHING ELSE.\n When updating the user, always respond in the language of the user (defaulting to English). Never mix two or more languages in the same response.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":19,"t":502.0,"say":"I have inspected the robot specification, initial proprioception, and camera views, created the initial `/app/output/gen.py` and `/app/NOTES.md` files, and launched a short step test on the simulator to observe the board-platform settling dynamics. Waiting for the command to complete.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":21,"t":508.0,"say":"","calls":[{"kind":"look","label":"venue_t10.png","code":"/tmp/venue_t10.png"},{"kind":"look","label":"head_left_t10.png","code":"/tmp/head_left_t10.png"}],"out":{"text":"The 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":22,"t":514.0,"say":"","calls":[{"kind":"shell","label":"Comparing robot position at t=0 and t=1.0s","code":"python3 -c \"\nfrom PIL import Image\nimport numpy as np\n\nv0 = np.array(Image.open('/tmp/venue_t0.png'))\nv1 = np.array(Image.open('/tmp/venue_t10.png'))\n# Find red line pixels in venue camera and robot pixels\ndiff = np.abs(v1.astype(int) - v0.astype(int)).max(axis=2)\nys, xs = np.where(diff > 20)\nprint('Changed bbox in venue:', xs.min(), ys.min(), xs.max(), ys.max())\n\n# Check red line in head_left_t10.png\nh1 = np.array(Image.open('/tmp/head_left_t10.png'))\nred = (h1[:,:,0] > 180) & (h1[:,:,1] < 50) & (h1[:,:,2] < 50)\nry, rx = np.where(red)\nprint('Red line in head_left_t10:', 'u range:', rx.min(), rx.max(), 'v range:', ry.min(), ry.max())\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nChanged bbox in venue: 11 167 45 199\r\nRed line in head_left_t10: u range: 144 213 v range: 140 269","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":23,"t":531.0,"say":"","calls":[{"kind":"robot","label":"Checking distance to red start line at t=1.0s","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\n\nr = Robot()\nspec = r.spec()\ncam = spec['cameras']['head_left']\nobs = r.get_obs(cameras=['head_left'], seconds=0, include_depth=True)\nd = obs.depth['head_left'][0].astype(np.float64)\n# In head_left_t10, we found red line pixels at u=144..213, v=140..269.\n# Let's check the depth of the red line pixels at t=1.0 vs t=0.0!\nfrom PIL import Image\nh0 = np.array(Image.open('/tmp/head_left_t0.png'))\nh1 = np.array(Image.open('/tmp/head_left_t10.png'))\nred0 = (h0[:,:,0] > 180) & (h0[:,:,1] < 50) & (h0[:,:,2] < 50)\nred1 = (h1[:,:,0] > 180) & (h1[:,:,1] < 50) & (h1[:,:,2] < 50)\nprint('Red line pixel count t=0:', red0.sum(), 't=1.0:', red1.sum())\nfor v in [160, 200, 240, 265]:\n    u0 = np.where(red0[v])[0]\n    u1 = np.where(red1[v])[0]\n    print(f'v={v}: u0={u0.mean() if len(u0) else -1:.1f}, u1={u1.mean() if len(u1) else -1:.1f}, d1={d[v, int(u1.mean())]:.3f}' if len(u1) else f'v={v}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nRed line pixel count t=0: 1797 t=1.0: 1607\r\nv=160: u0=175.5, u1=201.0, d1=2.611\r\nv=200: u0=153.0, u1=183.5, d1=1.960\r\nv=240: u0=131.0, u1=165.5, d1=1.568\r\nv=265: u0=116.5, u1=154.5, d1=1.395","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":621.0,"say":"","calls":[{"kind":"robot","label":"Computing red start line position in robot frame","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\nfrom scipy.spatial.transform import Rotation as R\n\nr = Robot()\nspec = r.spec()\ncam = spec['cameras']['head_left']\nobs = r.get_obs(cameras=['head_left'], seconds=0, include_depth=True)\nd = obs.depth['head_left'][0].astype(np.float64)\nh1 = obs.last['head_left']\nred1 = (h1[:,:,0] > 180) & (h1[:,:,1] < 50) & (h1[:,:,2] < 50)\n\nH, W = d.shape\nfovy = np.deg2rad(cam['fovy_deg'])\nfy = (H / 2.0) / np.tan(fovy / 2.0)\nfx = fy\n\n# In camera frame: fwd = [0, 0, 1], right = [1, 0, 0], up = [0, 1, 0]\n# At t=1.0, the robot is upright on the flat platform!\n# In robot frame at rest (upright, waist=0):\n# Let's get camera vectors in robot frame by undoing the 18.29 deg roll at t=0:\nrot_x = R.from_euler('x', 18.288, degrees=True).as_matrix()\nfwd_rob = rot_x @ np.array(cam['pose_t0']['forward'])\nup_rob = rot_x @ np.array(cam['pose_t0']['up'])\nright_rob = rot_x @ np.array(cam['pose_t0']['right'])\npos_rob = rot_x @ (np.array(cam['pose_t0']['position_m']) - np.array([0, 0, 0.62]))\nprint('Camera in upright robot frame: pos=', np.round(pos_rob, 3), 'fwd=', np.round(fwd_rob, 3), 'right=', np.round(right_rob, 3))\n\nfor v in [160, 200, 240, 265]:\n    u = int(np.where(red1[v])[0].mean())\n    z = d[v, u]\n    x_cam = (u - W/2.0) / fx * z\n    y_cam = -(v - H/2.0) / fy * z\n    p_rob = pos_rob + z * fwd_rob + x_cam * right_rob + y_cam * up_rob\n    print(f'v={v} u={u} z={z:.3f} -> p_rob = {np.round(p_rob, 3)}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nCamera in upright robot frame: pos= [ 0.076 -0.26   1.296] fwd= [ 0.939 -0.    -0.343] right= [ 0. -1.  0.]\r\nv=160 u=201 z=2.611 -> p_rob = [2.437 0.158 0.149]\r\nv=200 u=183 z=1.960 -> p_rob = [1.738 0.199 0.133]\r\nv=240 u=165 z=1.568 -> p_rob = [1.317 0.223 0.123]\r\nv=265 u=154 z=1.395 -> p_rob = [1.131 0.232 0.119]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":25,"t":636.0,"say":"","calls":[{"kind":"robot","label":"Testing downhill lean maneuver from t=1.0s to t=2.0s","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nq0 = np.array(obs.meta['proprio']['now'][:29], dtype=float)\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\n\nrows = []\n# 100 steps (1.0s): lean downhill toward nose (+y_robot)\nfor step in range(100):\n    alpha = min(1.0, (step + 1) / 40.0)\n    q = q0.copy()\n    # Shift pelvis toward +y (left foot / nose) and lean torso toward +y\n    q[idx['left_hip_roll_pos']] = 0.124 - 0.18 * alpha\n    q[idx['right_hip_roll_pos']] = -0.128 - 0.18 * alpha\n    q[idx['left_ankle_roll_pos']] = -0.128 + 0.25 * alpha\n    q[idx['right_ankle_roll_pos']] = 0.133 + 0.25 * alpha\n    q[idx['waist_roll_pos']] = -0.45 * alpha\n    q[idx['left_shoulder_roll_pos']] = 0.2 + 1.4 * alpha\n    rows.append(list(q) + [0.0, 0.0])\n\nres = r.submit('joints', rows, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=20, include_depth=True)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'))\nfor p in res.proprio[::2]:\n    t = p[idx['time_s']]\n    qw, qx, qy, qz = p[idx['imu_pelvis_qw']], p[idx['imu_pelvis_qx']], p[idx['imu_pelvis_qy']], p[idx['imu_pelvis_qz']]\n    gx, gy, gz = p[idx['imu_pelvis_gx']], p[idx['imu_pelvis_gy']], p[idx['imu_pelvis_gz']]\n    ax, ay, az = p[idx['imu_pelvis_ax']], p[idx['imu_pelvis_ay']], p[idx['imu_pelvis_az']]\n    print(f't={t:.2f} q=({qw:.3f},{qx:.3f},{qy:.3f},{qz:.3f}) g=({gx:6.2f},{gy:6.2f},{gz:6.2f}) a=({ax:5.1f},{ay:5.1f},{az:5.1f})')\nfor cam, img in res.last.items():\n    Image.fromarray(img).save(f'/tmp/{cam}_t20.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: False Reason: None\r\nt=1.00 q=(0.727,0.008,0.009,-0.686) g=(  0.00,  0.00,  0.00) a=( -0.3, -0.0,  9.8)\r\nt=1.10 q=(0.731,0.015,0.004,-0.682) g=(  0.24,  0.08,  0.11) a=( -0.1,  0.7,  9.8)\r\nt=1.20 q=(0.734,0.027,0.000,-0.679) g=(  0.17,  0.12,  0.07) a=( -0.2,  1.5,  9.8)\r\nt=1.30 q=(0.736,0.038,-0.002,-0.676) g=(  0.17,  0.13,  0.08) a=( -0.4,  2.1,  9.8)\r\nt=1.40 q=(0.738,0.050,-0.004,-0.673) g=(  0.18,  0.11,  0.07) a=( -0.6,  1.5,  9.9)\r\nt=1.50 q=(0.737,0.055,-0.002,-0.674) g=(  0.00,  0.10, -0.02) a=( -0.8,  0.1,  9.8)\r\nt=1.60 q=(0.736,0.058,0.001,-0.674) g=(  0.00,  0.07, -0.01) a=( -1.0,  0.3,  9.8)\r\nt=1.70 q=(0.736,0.059,0.003,-0.675) g=(  0.00,  0.03, -0.01) a=( -1.0,  0.4,  9.8)\r\nt=1.80 q=(0.736,0.060,0.003,-0.675) g=( -0.00, -0.00,  0.00) a=( -1.0,  0.7,  9.8)\r\nt=1.90 q=(0.736,0.059,0.002,-0.675) g=( -0.00, -0.03,  0.00) a=( -1.0,  0.8,  9.7)\r\nt=2.00 q=(0.736,0.058,0.001,-0.675) g=( -0.00, -0.05,  0.01) a=( -0.9,  0.8,  9.7)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":26,"t":709.0,"say":"","calls":[{"kind":"robot","label":"Checking if robot moved toward start line at t=2.0s","code":"python3 -c \"\nfrom PIL import Image\nimport numpy as np\n\nh1 = np.array(Image.open('/tmp/head_left_t10.png'))\nh2 = np.array(Image.open('/tmp/head_left_t20.png'))\nred1 = (h1[:,:,0] > 180) & (h1[:,:,1] < 50) & (h1[:,:,2] < 50)\nred2 = (h2[:,:,0] > 180) & (h2[:,:,1] < 50) & (h2[:,:,2] < 50)\nfor v in [160, 200, 240, 265]:\n    u1 = np.where(red1[v])[0]\n    u2 = np.where(red2[v])[0]\n    print(f'v={v}: u1={u1.mean() if len(u1) else -1:.1f}, u2={u2.mean() if len(u2) else -1:.1f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nv=160: u1=201.0, u2=170.5\r\nv=200: u1=183.5, u2=140.0\r\nv=240: u1=165.5, u2=109.5\r\nv=265: u1=154.5, u2=90.0","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":27,"t":726.0,"say":"","calls":[{"kind":"shell","label":"Measuring snowboard position in fixed venue camera","code":"python3 -c \"\nfrom PIL import Image\nimport numpy as np\n\nfor name in ['venue_t0', 'venue_t10', 'venue_t20']:\n    img = np.array(Image.open(f'/tmp/{name}.png'))\n    # Snowboard is blue: high B, lower R\n    blue = (img[:,:,2].astype(int) - img[:,:,0].astype(int) > 30) & (img[:,:,2] > 100)\n    by, bx = np.where(blue)\n    print(f'{name}: blue pixels={len(bx)}, x_mean={bx.mean():.2f}, y_mean={by.mean():.2f}, x_range=({bx.min()},{bx.max()}), y_range=({by.min()},{by.max()})')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nvenue_t0: blue pixels=1337, x_mean=218.43, y_mean=8.19, x_range=(0,462), y_range=(0,195)\r\nvenue_t10: blue pixels=1343, x_mean=217.75, y_mean=9.02, x_range=(0,462), y_range=(0,199)\r\nvenue_t20: blue pixels=1337, x_mean=218.56, y_mean=8.22, x_range=(0,462), y_range=(0,199)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":28,"t":736.0,"say":"","calls":[{"kind":"shell","label":"Measuring snowboard pixels in venue crop","code":"python3 -c \"\nfrom PIL import Image\nimport numpy as np\n\nfor name in ['venue_t0', 'venue_t10', 'venue_t20']:\n    img = np.array(Image.open(f'/tmp/{name}.png'))\n    sub = img[140:230, 0:90]\n    blue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\n    by, bx = np.where(blue)\n    print(f'{name}: board pixels={len(bx)}, x_mean={bx.mean():.2f}, y_mean={by.mean()+140:.2f}, x_range=({bx.min()},{bx.max()}), y_range=({by.min()+140},{by.max()+140})')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nvenue_t0: board pixels=46, x_mean=26.54, y_mean=191.35, x_range=(11,41), y_range=(186,195)\r\nvenue_t10: board pixels=48, x_mean=30.96, y_mean=192.19, x_range=(17,44), y_range=(184,199)\r\nvenue_t20: board pixels=45, x_mean=30.82, y_mean=192.33, x_range=(17,44), y_range=(184,199)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":29,"t":744.0,"say":"","calls":[{"kind":"shell","label":"Checking rotation matrix at t=2.0s","code":"python3 -c \"\nimport numpy as np\nfrom scipy.spatial.transform import Rotation as R\nrot = R.from_quat([0.058, 0.001, -0.675, 0.736])\nprint(np.round(rot.as_matrix(), 3))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\n[[ 0.089  0.993 -0.077]\r\n [-0.993  0.083 -0.087]\r\n [-0.08   0.084  0.993]]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":30,"t":810.0,"say":"","calls":[{"kind":"robot","label":"Testing dynamic pump maneuver from t=2.0s to t=4.0s","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\nfrom scipy.spatial.transform import Rotation as R\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nq0 = np.array(obs.meta['proprio']['now'][:29], dtype=float)\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\n\n# Let's test 2 seconds (200 steps): lean onto front foot (left knee bent, right knee straight, pelvis tilted downhill)\n# and do a dynamic pump (crouch/unweight while pulling board forward, then extend slowly)\nrows = []\nfor step in range(200):\n    t = step * 0.01\n    q = q0.copy()\n    # Base stance: shift weight to front foot (left) and tilt pelvis downhill (nose down)\n    # To tilt pelvis downhill (nose down, gx < 0), foot must tilt +x relative to pelvis -> hip_roll + ankle_roll < 0\n    # And left leg shorter (left_knee = 0.55), right leg longer (right_knee = 0.10)\n    phase = (t % 0.6) / 0.6 # 0.6s pump cycle\n    if phase < 0.25:\n        # Fast unweight & throw CoM backward/uphill relative to board (pushes board forward/downhill!)\n        s = np.sin(phase / 0.25 * np.pi)\n        knee_add = 0.5 * s\n        shift = 0.20 * s # hip_roll > 0 shifts pelvis uphill (-y), pushing board downhill (+y)!\n        w_roll = 0.4 * s\n    else:\n        # Slow recovery forward/downhill while weighted\n        s = 1.0 - (phase - 0.25) / 0.75\n        knee_add = 0.1 * s\n        shift = -0.10 * (1.0 - s)\n        w_roll = -0.45\n\n    q[idx['left_knee_pos']] = 0.45 + knee_add\n    q[idx['right_knee_pos']] = 0.15 + knee_add\n    q[idx['left_hip_pitch_pos']] = -0.22 - 0.5 * knee_add\n    q[idx['right_hip_pitch_pos']] = -0.08 - 0.5 * knee_add\n    q[idx['left_ankle_pitch_pos']] = -0.23 - 0.5 * knee_add\n    q[idx['right_ankle_pitch_pos']] = -0.07 - 0.5 * knee_add\n\n    q[idx['left_hip_roll_pos']] = 0.05 + shift\n    q[idx['right_hip_roll_pos']] = -0.20 + shift\n    q[idx['left_ankle_roll_pos']] = -0.15 - shift\n    q[idx['right_ankle_roll_pos']] = 0.10 - shift\n    q[idx['waist_roll_pos']] = w_roll\n    q[idx['left_shoulder_roll_pos']] = 1.6\n    q[idx['right_shoulder_roll_pos']] = -0.2\n    rows.append(list(q) + [0.0, 0.0])\n\nres = r.submit('joints', rows, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=10)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'))\nimg = res.last['venue']\nImage.fromarray(img).save('/tmp/venue_t40.png')\nsub = img[140:230, 0:120]\nblue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\nby, bx = np.where(blue)\nprint(f'venue_t40: board pixels={len(bx)}, x_mean={bx.mean():.2f}, y_mean={by.mean()+140:.2f}, x_range=({bx.min()},{bx.max()})')\nfor p in res.proprio[::3]:\n    t = p[idx['time_s']]\n    rot = R.from_quat([p[idx['imu_pelvis_qx']], p[idx['imu_pelvis_qy']], p[idx['imu_pelvis_qz']], p[idx['imu_pelvis_qw']]])\n    z_axis = rot.as_matrix()[:, 2]\n    print(f't={t:.2f} z_axis=({z_axis[0]:.3f},{z_axis[1]:.3f},{z_axis[2]:.3f}) a=({p[idx[\\\"imu_pelvis_ax\\\"]]:5.1f},{p[idx[\\\"imu_pelvis_ay\\\"]]:5.1f},{p[idx[\\\"imu_pelvis_az\\\"]]:5.1f})')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: False Reason: None\r\nvenue_t40: board pixels=47, x_mean=27.98, y_mean=192.66, x_range=(14,41)\r\nt=2.00 z_axis=(-0.076,-0.087,0.993) a=( -0.9,  0.8,  9.7)\r\nt=2.30 z_axis=(-0.068,-0.078,0.995) a=( -0.3,  1.9, 12.4)\r\nt=2.60 z_axis=(-0.029,0.037,0.999) a=(  0.5, -0.8,  9.4)\r\nt=2.90 z_axis=(-0.077,0.005,0.997) a=( -0.5, -1.1,  7.6)\r\nt=3.20 z_axis=(-0.019,-0.058,0.998) a=( -1.3, -0.7,  9.3)\r\nt=3.50 z_axis=(-0.078,-0.026,0.997) a=( -0.7, -1.1,  7.4)\r\nt=3.80 z_axis=(-0.024,-0.018,1.000) a=( -0.4, -0.8,  9.4)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":31,"t":855.0,"say":"","calls":[{"kind":"robot","label":"Testing reversed pump maneuver from t=4.0s to t=7.0s","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nq0 = np.array(obs.meta['proprio']['now'][:29], dtype=float)\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\n\nrows = []\nfor step in range(300):\n    t = step * 0.01\n    q = q0.copy()\n    phase = (t % 0.6) / 0.6\n    if phase < 0.25:\n        # Fast crouch: move CoM toward +y (downhill) while weighted at bottom of crouch\n        s = np.sin(phase / 0.25 * np.pi)\n        knee_add = 0.55 * s\n        shift = -0.18 * s\n        w_roll = -0.48 * s\n        l_sh = 1.8 * s\n        r_sh = -0.2\n    else:\n        # Unweighted extension: move CoM toward -y (uphill) -> pushes unweighted board toward +y (downhill)!\n        s = 1.0 - (phase - 0.25) / 0.75\n        knee_add = 0.1 * s\n        shift = 0.14 * (1.0 - s)\n        w_roll = 0.35 * (1.0 - s)\n        l_sh = 0.2\n        r_sh = -1.4 * (1.0 - s)\n\n    q[idx['left_knee_pos']] = 0.25 + knee_add\n    q[idx['right_knee_pos']] = 0.35 + knee_add\n    q[idx['left_hip_pitch_pos']] = -0.12 - 0.5 * knee_add\n    q[idx['right_hip_pitch_pos']] = -0.18 - 0.5 * knee_add\n    q[idx['left_ankle_pitch_pos']] = -0.13 - 0.5 * knee_add\n    q[idx['right_ankle_pitch_pos']] = -0.17 - 0.5 * knee_add\n\n    q[idx['left_hip_roll_pos']] = 0.12 + shift\n    q[idx['right_hip_roll_pos']] = -0.12 + shift\n    q[idx['left_ankle_roll_pos']] = -0.12 - shift\n    q[idx['right_ankle_roll_pos']] = 0.12 - shift\n    q[idx['waist_roll_pos']] = w_roll\n    q[idx['left_shoulder_roll_pos']] = l_sh\n    q[idx['right_shoulder_roll_pos']] = r_sh\n    rows.append(list(q) + [0.0, 0.0])\n\nres = r.submit('joints', rows, dt=0.01, cameras=['head_left', 'venue'], video='frames', video_fps=10)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'))\nfor i, img in enumerate(res.frames['venue'][::5]):\n    sub = img[140:230, 0:150]\n    blue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\n    by, bx = np.where(blue)\n    if len(bx):\n        print(f'frame {i*5:2d} (t={4.0+i*0.5:.1f}s): x_mean={bx.mean():.2f}, y_mean={by.mean()+140:.2f}, x_range=({bx.min()},{bx.max()})')\nImage.fromarray(res.last['venue']).save('/tmp/venue_t70.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: False Reason: None\r\nframe  0 (t=4.0s): x_mean=27.98, y_mean=192.66, x_range=(14,41)\r\nframe  5 (t=4.5s): x_mean=25.96, y_mean=193.68, x_range=(13,40)\r\nframe 10 (t=5.0s): x_mean=26.40, y_mean=193.38, x_range=(13,39)\r\nframe 15 (t=5.5s): x_mean=25.74, y_mean=193.72, x_range=(13,37)\r\nframe 20 (t=6.0s): x_mean=24.06, y_mean=195.34, x_range=(13,34)\r\nframe 25 (t=6.5s): x_mean=24.21, y_mean=194.71, x_range=(13,33)\r\nframe 30 (t=7.0s): x_mean=24.98, y_mean=195.06, x_range=(15,34)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":32,"t":889.0,"say":"","calls":[{"kind":"robot","label":"Cropping venue image at t=7.0s","code":"python3 -c \"\nfrom PIL import Image\nimg = Image.open('/tmp/venue_t70.png')\ncrop = img.crop((0, 110, 120, 260)).resize((480, 600), Image.NEAREST)\ncrop.save('/tmp/robot_zoom_t70.png')\n\""}],"out":{"text":"The command exited with code 0.\nStdout:\n\nStderr:","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":33,"t":914.0,"say":"","calls":[{"kind":"look","label":"robot_zoom_t70.png","code":"/tmp/robot_zoom_t70.png"}],"out":{"text":"The 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":34,"t":925.0,"say":"","calls":[{"kind":"robot","label":"Testing walk_agile with vy=0.5 on start platform","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\n# walk_agile layout: vx, vy, wz, waist(3), arms(14), grip(2) = 22\nrest_upper = spec['robot_facts']['rest_upper_rad']\nrow = [0.0, 0.5, 0.0] + list(rest_upper) + [0.0, 0.0]\nres = r.submit('walk_agile', [row]*150, dt=0.01, cameras=['venue'], video='frames', video_fps=10)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'), 'Outcome:', res.meta.get('outcome'))\nfor i, img in enumerate(res.frames['venue'][::3]):\n    sub = img[140:230, 0:150]\n    blue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\n    by, bx = np.where(blue)\n    if len(bx):\n        print(f'frame {i*3:2d}: x_mean={bx.mean():.2f}, y_mean={by.mean()+140:.2f}, x_range=({bx.min()},{bx.max()})')\nImage.fromarray(res.last['venue']).save('/tmp/venue_t85.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: False Reason: None Outcome: None\r\nframe  0: x_mean=24.98, y_mean=195.06, x_range=(15,34)\r\nframe  3: x_mean=24.50, y_mean=196.13, x_range=(15,32)\r\nframe  6: x_mean=23.98, y_mean=196.57, x_range=(14,31)\r\nframe  9: x_mean=24.36, y_mean=195.92, x_range=(14,32)\r\nframe 12: x_mean=24.31, y_mean=195.69, x_range=(15,32)\r\nframe 15: x_mean=23.94, y_mean=195.83, x_range=(14,32)","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":35,"t":959.0,"say":"","calls":[{"kind":"robot","label":"Measuring signed distance to red start line in venue camera","code":"python3 -c \"\nfrom PIL import Image\nimport numpy as np\n\nv0 = np.array(Image.open('/tmp/venue_t0.png'))\n# Red line in venue_t0:\nred = (v0[:,:,0].astype(int) - v0[:,:,1].astype(int) > 100) & (v0[:,:,0] > 150) & (np.arange(270)[:,None] > 150)\nry, rx = np.where(red)\n# Fit line y = m*x + b\nm, b = np.polyfit(rx, ry, 1)\nprint(f'Red start line in venue: y = {m:.4f} * x + {b:.2f}')\n# Normal pointing downhill (up-right in image, i.e. +x, -y? Wait: let's check where gates are!)\n# Gates are at x=150..350, y=100..150 -> For gates, m*x + b - y > 0!\nnorm = np.hypot(m, 1.0)\nfor name in ['venue_t0', 'venue_t10', 'venue_t20', 'venue_t40', 'venue_t70', 'venue_t85']:\n    img = np.array(Image.open(f'/tmp/{name}.png'))\n    sub = img[140:230, 0:120]\n    blue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\n    by, bx = np.where(blue)\n    by = by + 140\n    # Signed distance toward downhill (positive = past start line, negative = behind start line)\n    dist = (m * bx + b - by) / norm\n    # Also position along the start line:\n    along = (bx + m * (by - b)) / norm\n    print(f'{name:10s}: dist_to_line_mean={dist.mean():6.2f} (max={dist.max():6.2f}, min={dist.min():6.2f}), along_line={along.mean():6.2f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nRed start line in venue: y = 0.6824 * x + 155.87\r\nvenue_t0  : dist_to_line_mean=-14.34 (max= -2.34, min=-25.56), along_line= 41.92\r\nvenue_t10 : dist_to_line_mean=-12.55 (max=  1.57, min=-25.48), along_line= 46.04\r\nvenue_t20 : dist_to_line_mean=-12.75 (max=  1.57, min=-25.48), along_line= 46.01\r\nvenue_t40 : dist_to_line_mean=-14.62 (max= -0.69, min=-28.00), along_line= 43.85\r\nvenue_t70 : dist_to_line_mean=-18.29 (max= -6.55, min=-30.48), along_line= 42.73\r\nvenue_t85 : dist_to_line_mean=-19.52 (max= -7.68, min=-31.87), along_line= 42.30","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":36,"t":979.0,"say":"","calls":[{"kind":"robot","label":"Testing nose-down press and pump from t=8.5s to t=11.5s","code":"python3 -c \"\nfrom rcb_client import Robot\nimport numpy as np\nfrom PIL import Image\n\nr = Robot()\nspec = r.spec()\nobs = r.get_obs(cameras=[], seconds=0)\nq0 = np.array(obs.meta['proprio']['now'][:29], dtype=float)\nlayout = spec['proprio_layout']\nidx = {k: i for i, k in enumerate(layout)}\n\nrows = []\nfor step in range(300):\n    t = step * 0.01\n    alpha = min(1.0, (step + 1) / 30.0)\n    pump = 0.15 * np.sin(2 * np.pi * t / 0.5)\n    q = q0.copy()\n    # Left (front/nose) leg EXTENDED to push nose DOWN; Right (back/tail) leg BENT to lift tail UP!\n    q[idx['left_knee_pos']] = (1 - alpha) * q0[idx['left_knee_pos']] + alpha * (0.12 + max(0, pump))\n    q[idx['right_knee_pos']] = (1 - alpha) * q0[idx['right_knee_pos']] + alpha * (0.75 + pump)\n    q[idx['left_hip_pitch_pos']] = -0.06\n    q[idx['right_hip_pitch_pos']] = -0.38\n    q[idx['left_ankle_pitch_pos']] = -0.06\n    q[idx['right_ankle_pitch_pos']] = -0.38\n\n    # Hip roll and ankle roll to shift pelvis toward +y (nose) and torque nose down (roll < 0)\n    q[idx['left_hip_roll_pos']] = 0.25\n    q[idx['right_hip_roll_pos']] = 0.05\n    q[idx['left_ankle_roll_pos']] = -0.26\n    q[idx['right_ankle_roll_pos']] = -0.05\n\n    # Torso and arms leaning toward +y (downhill/nose)\n    q[idx['waist_roll_pos']] = -0.50\n    q[idx['waist_pitch_pos']] = 0.0\n    q[idx['left_shoulder_pitch_pos']] = 0.0\n    q[idx['left_shoulder_roll_pos']] = 2.0\n    q[idx['left_elbow_pos']] = 0.2\n    q[idx['right_shoulder_pitch_pos']] = 0.0\n    q[idx['right_shoulder_roll_pos']] = 0.5\n    q[idx['right_elbow_pos']] = 1.5\n    rows.append(list(q) + [0.0, 0.0])\n\nres = r.submit('joints', rows, dt=0.01, cameras=['venue', 'head_left'], video='frames', video_fps=10)\nprint('Done:', res.done, 'Reason:', res.meta.get('reason'), 'Outcome:', res.meta.get('outcome'))\nm, b = 0.6824, 155.87\nnorm = np.hypot(m, 1.0)\nfor i, img in enumerate(res.frames['venue'][::5]):\n    sub = img[130:250, 0:200]\n    blue = (sub[:,:,2].astype(int) - sub[:,:,0].astype(int) > 25)\n    by, bx = np.where(blue)\n    if len(bx):\n        by = by + 130\n        dist = (m * bx + b - by) / norm\n        print(f'frame {i*5:2d} (t={8.5+i*0.5:.1f}s): dist_to_line_mean={dist.mean():6.2f} (max={dist.max():6.2f}), x_mean={bx.mean():.2f}, y_mean={by.mean():.2f}')\nImage.fromarray(res.last['venue']).save('/tmp/venue_t115.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDone: True Reason: failed Outcome: fell\r\nframe  0 (t=8.5s): dist_to_line_mean=-19.52 (max= -7.68), x_mean=23.94, y_mean=195.83\r\nframe  5 (t=9.0s): dist_to_line_mean=-15.65 (max= -5.16), x_mean=27.82, y_mean=193.80\r\nframe 10 (t=9.5s): dist_to_line_mean=-19.48 (max= -6.59), x_mean=22.76, y_mean=194.99","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":37,"t":1088.0,"say":"","calls":[{"kind":"robot","label":"Cropping venue image at end of Episode 1","code":"python3 -c \"\nfrom PIL import Image\nimg = Image.open('/tmp/venue_t115.png')\ncrop = img.crop((0, 110, 120, 260)).resize((480, 600), Image.NEAREST)\ncrop.save('/tmp/robot_zoom_t115.png')\n\""}],"out":{"text":"The command exited with code 0.\nStdout:\n\nStderr:","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":38,"t":1102.0,"say":"","calls":[{"kind":"look","label":"robot_zoom_t115.png","code":"/tmp/robot_zoom_t115.png"}],"out":{"text":"The 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":39,"t":1130.0,"say":"","calls":[{"kind":"shell","label":"Installing mujoco 3.3.7 and opencv","code":"pip install -q mujoco==3.3.7 opencv-python-headless && python3 -c \"import mujoco; print('MuJoCo version:', mujoco.__version__)\""}],"out":{"text":"The command exited with code 0.\nOutput:\nWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.\r\n\r\n[notice] A new release of pip is available: 25.0.1 -> 26.2.2\r\n[notice] To update, run: pip install --upgrade pip\r\nMuJoCo version: 3.3.7","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":40,"t":1153.0,"say":"","calls":[{"kind":"robot","label":"Checking referee call at end of Episode 1","code":"python3 -c \"\nfrom rcb_client import Robot\nimport json\nr = Robot()\nobs = r.get_obs(cameras=[], seconds=0)\nprint(json.dumps({k: v for k, v in obs.meta.items() if k != 'proprio'}, indent=2))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\n{\r\n  \"calls\": 21,\r\n  \"rows\": 949,\r\n  \"control_steps\": 949,\r\n  \"done\": true,\r\n  \"reason\": \"failed\",\r\n  \"episode\": 1,\r\n  \"control_steps_total\": 949,\r\n  \"resets_left\": 5,\r\n  \"sim_time_s\": 9.49,\r\n  \"time_s\": 1149.39,\r\n  \"time_left_s\": 6050.6,\r\n  \"outcome\": \"fell\",\r\n  \"stages_reached\": 0,\r\n  \"stages_total\": 20,\r\n  \"obs_id\": 21,\r\n  \"seconds\": 0.0,\r\n  \"control_steps_watch\": 0,\r\n  \"ok\": true\r\n}","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":41,"t":1168.0,"say":"","calls":[{"kind":"shell","label":"Checking CHIGUI0/roboolympics PR #259 ski-snow model","code":"python3 -c \"\nimport requests\n# Check CHIGUI0/roboolympics PR 259 or repo contents via GitHub API\nr = requests.get('https://api.github.com/repos/CHIGUI0/roboolympics/pulls/259', timeout=10)\nprint('PR 259 status:', r.status_code)\nif r.status_code == 200:\n    data = r.json()\n    print('Title:', data.get('title'))\n    print('Body:', (data.get('body') or '')[:500])\nr2 = requests.get('https://api.github.com/repos/CHIGUI0/roboolympics/pulls/259/files', timeout=10)\nif r2.status_code == 200:\n    for f in r2.json():\n        print('File:', f['filename'], f['raw_url'])\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nPR 259 status: 404","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":42,"t":1180.0,"say":"","calls":[{"kind":"shell","label":"Downloading unitree_g1 model from mujoco_menagerie","code":"git clone --depth 1 --filter=blob:none --sparse https://github.com/google-deepmind/mujoco_menagerie.git /tmp/menagerie && git -C /tmp/menagerie sparse-checkout set unitree_g1 && ls -la /tmp/menagerie/unitree_g1"}],"out":{"text":"The command exited with code 127.\nOutput:\nbash: line 1: git: command not found","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":43,"t":1190.0,"say":"","calls":[{"kind":"shell","label":"Downloading unitree_g1 files via Python requests","code":"python3 -c \"\nimport os, requests\n\ndef download_dir(api_url, local_dir):\n    os.makedirs(local_dir, exist_ok=True)\n    r = requests.get(api_url, timeout=15)\n    r.raise_for_status()\n    for item in r.json():\n        if item['type'] == 'file':\n            content = requests.get(item['download_url'], timeout=30).content\n            with open(os.path.join(local_dir, item['name']), 'wb') as f:\n                f.write(content)\n        elif item['type'] == 'dir':\n            download_dir(item['url'], os.path.join(local_dir, item['name']))\n\ndownload_dir('https://api.github.com/repos/google-deepmind/mujoco_menagerie/contents/unitree_g1', '/tmp/unitree_g1')\nprint('Downloaded files:', os.listdir('/tmp/unitree_g1'))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nDownloaded files: ['g1_mjx.xml', 'scene_mjx.xml', 'README.md', 'LICENSE', 'scene.xml', 'g1_mjx_colliders.png', 'scene_with_hands.xml', 'g1_with_hands.png', 'CHANGELOG.md', 'g1.xml', 'g1.png', 'g1_with_hands.xml', 'assets', 'g1_mjlab.xml']","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":44,"t":1205.0,"say":"","calls":[{"kind":"shell","label":"reads g1.xml","code":"/tmp/unitree_g1/g1.xml"}],"out":{"text":"File Path: `file:///tmp/unitree_g1/g1.xml`\nTotal Lines: 351\nTotal Bytes: 23446\nShowing lines 1 to 250\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: <mujoco model=\"g1_29dof_rev_1_0\">\n2:   <compiler angle=\"radian\" meshdir=\"assets\"/>\n3: \n4:   <option integrator=\"implicitfast\"/>\n5: \n6:   <default>\n7:     <default class=\"g1\">\n8:       <site rgba=\"1 0 0 1\" size=\"0.01\" group=\"5\"/>\n9:       <joint armature=\"0.01\" frictionloss=\"0.3\"/>\n10:       <position kp=\"500\" dampratio=\"1\" inheritrange=\"1\"/>\n11:       <default class=\"visual\">\n12:         <geom group=\"2\" type=\"mesh\" contype=\"0\" conaffinity=\"0\" density=\"0\" material=\"metal\"/>\n13:       </default>\n14:       <default class=\"collision\">\n15:         <geom group=\"3\" type=\"mesh\"/>\n16:         <default class=\"foot\">\n17:           <geom type=\"sphere\" size=\"0.005\" priority=\"1\" friction=\"0.6\" condim=\"3\"/>\n18:         </default>\n19:       </default>\n20:     </default>\n21:   </default>\n22: \n23:   <asset>\n24:     <material name=\"black\" rgba=\"0.2 0.2 0.2 1\"/>\n25:     <material name=\"metal\" rgba=\"0.7 0.7 0.7 1\"/>\n26: \n27:     <mesh file=\"pelvis.STL\"/>\n28:     <mesh file=\"pelvis_contour_link.STL\"/>\n29:     <mesh file=\"left_hip_pitch_link.STL\"/>\n30:     <mesh file=\"left_hip_roll_link.STL\"/>\n31:     <mesh file=\"left_hip_yaw_link.STL\"/>\n32:     <mesh file=\"\n… (15,323 characters left out) …\ns=\"collision\" mesh=\"left_wrist_yaw_link\"/>\n233:                           <geom pos=\"0.0415 0.003 0\" quat=\"1 0 0 0\" class=\"visual\" mesh=\"left_rubber_hand\"/>\n234:                         </body>\n235:                       </body>\n236:                     </body>\n237:                   </body>\n238:                 </body>\n239:               </body>\n240:             </body>\n241:             <body name=\"right_shoulder_pitch_link\" pos=\"0.0039563 -0.10021 0.24778\"\n242:               quat=\"0.990264 -0.139201 1.38722e-05 9.86868e-05\">\n243:               <inertial pos=\"0 -0.035892 -0.011628\" quat=\"0.68225 -0.326267 0.0130458 0.654152\" mass=\"0.718\"\n244:                 diaginertia=\"0.000465864 0.000432842 0.000406394\"/>\n245:               <joint name=\"right_shoulder_pitch_joint\" axis=\"0 1 0\" range=\"-3.0892 2.6704\" actuatorfrcrange=\"-25 25\"/>\n246:               <geom class=\"visual\" mesh=\"right_shoulder_pitch_link\"/>\n247:               <geom size=\"0.03 0.025\" pos=\"0 -0.04 -0.01\" quat=\"0.707107 0 0.707107 0\" type=\"cylinder\"\n248:                 rgba=\"0.7 0.7 0.7 1\" class=\"collision\"/>\n249:               <body name=\"right_shoulder_roll_link\" pos=\"0 -0.038 -0.013831\" quat=\"0.990268 0.139172 0 0\">\n250:                 <inertial pos=\"-0.000227 -0.00727 -0.063243\" quat=\"0.712604 -0.00710317 -0.0196223 0.701256\"\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":45,"t":1276.0,"say":"","calls":[{"kind":"shell","label":"Computing forward kinematics of G1 feet at t=0 pose","code":"python3 -c \"\nimport mujoco, numpy as np\n\nm = mujoco.MjModel.from_xml_path('/tmp/unitree_g1/g1.xml')\nd = mujoco.MjData(m)\nq0 = [-0.1, 0.1398, 0.0, 0.3, -0.2, -0.1398, -0.1469, -0.1103, 0.0759, 0.3515, -0.2137, 0.1232,\n      0.0, 0.0, 0.0, 0.2, 0.2, 0.0, 1.28, 0.0, 0.0, 0.0, 0.2, -0.2, 0.0, 1.28, 0.0, 0.0, 0.0]\nd.qpos[7:] = q0\n# First in upright robot frame (quat = [1, 0, 0, 0], pos = [0, 0, 0.793])\nd.qpos[:3] = [0, 0, 0.793]\nd.qpos[3:7] = [1, 0, 0, 0]\nmujoco.mj_forward(m, d)\nlf_id = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_BODY, 'left_ankle_roll_link')\nrf_id = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_BODY, 'right_ankle_roll_link')\nprint('Left ankle pos (upright):', np.round(d.xpos[lf_id], 4))\nprint('Right ankle pos (upright):', np.round(d.xpos[rf_id], 4))\nprint('Diff (left - right):', np.round(d.xpos[lf_id] - d.xpos[rf_id], 4))\nprint('Left ankle xmat:\\n', np.round(d.xmat[lf_id].reshape(3,3), 4))\nprint('Right ankle xmat:\\n', np.round(d.xmat[rf_id].reshape(3,3), 4))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nLeft ankle pos (upright): [-0.0276  0.2     0.0496]\r\nRight ankle pos (upright): [-0.0125 -0.1997  0.0517]\r\nDiff (left - right): [-0.0151  0.3998 -0.0021]\r\nLeft ankle xmat:\r\n [[ 0.9993 -0.0378 -0.0027]\r\n [ 0.0378  0.9993  0.0052]\r\n [ 0.0025 -0.0053  1.    ]]\r\nRight ankle xmat:\r\n [[ 0.9993 -0.0378 -0.0027]\r\n [ 0.0378  0.9993  0.0052]\r\n [ 0.0025 -0.0053  1.    ]]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":46,"t":1293.0,"say":"","calls":[{"kind":"shell","label":"Testing 12-DOF closed-chain snowboard IK solver","code":"python3 -c \"\nimport mujoco, numpy as np\nfrom scipy.spatial.transform import Rotation as R\n\nm = mujoco.MjModel.from_xml_path('/tmp/unitree_g1/g1.xml')\nd = mujoco.MjData(m)\nlf_id = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_BODY, 'left_ankle_roll_link')\nrf_id = mujoco.mj_name2id(m, mujoco.mjtObj.mjOBJ_BODY, 'right_ankle_roll_link')\n\ndef solve_ik(p_pos, p_euler_xyz, q_init=None):\n    # Board frame: origin midway between feet, +x toe-side, +y nose, +z up.\n    # Left foot target in board frame: [0, +0.20, 0], R = I\n    # Right foot target in board frame: [0, -0.20, 0], R = I\n    # Place pelvis at p_pos, p_rot in world(=board) frame:\n    d.qpos[:3] = p_pos\n    rot_p = R.from_euler('xyz', p_euler_xyz)\n    q_xyzw = rot_p.as_quat()\n    d.qpos[3:7] = [q_xyzw[3], q_xyzw[0], q_xyzw[1], q_xyzw[2]]\n    if q_init is not None:\n        d.qpos[7:19] = q_init\n    else:\n        d.qpos[7:19] = [-0.1, 0.14, 0, 0.3, -0.2, -0.14, -0.14, -0.11, 0.08, 0.35, -0.21, 0.12]\n    \n    p_lf_target = np.array([0.0, 0.20, 0.0])\n    p_rf_target = np.array([0.0, -0.20, 0.0])\n    \n    for _ in range(30):\n        mujoco.mj_forward(m, d)\n        # Left foot error (6D)\n        err_lf_pos = p_lf_target - d.xpos[lf_id]\n        R_lf = d.xmat[lf_id].reshape(3, 3)\n        err_lf_rot = R.from_matrix(R_lf.T).as_rotvec() # in local or world? R_target = I -> world rotvec is R.from_matrix(I @ R_lf.T).as_rotvec()\n        \n        err_rf_pos = p_rf_target - d.xpos[rf_id]\n        R_rf = d.xmat[rf_id].reshape(3, 3)\n        err_rf_rot = R.from_matrix(R_rf.T).as_rotvec()\n        \n        if np.linalg.norm(err_lf_pos) < 1e-5 and np.linalg.norm(err_rf_pos) < 1e-5 and np.linalg.norm(err_lf_rot) < 1e-5 and np.linalg.norm(err_rf_rot) < 1e-5:\n            break\n            \n        jacp = np.zeros((3, m.nv))\n        jacr = np.zeros((3, m.nv))\n        mujoco.mj_jacBody(m, d, jacp, jacr, lf_id)\n        J_l = np.vstack([jacp[:, 6:12], jacr[:, 6:12]])\n        dq_l = np.linalg.lstsq(J_l, np.concatenate([err_lf_pos, err_lf_rot]), rcond=1e-4)[0]\n        \n        mujoco.mj_jacBody(m, d, jacp, jacr, rf_id)\n        J_r = np.vstack([jacp[:, 12:18], jacr[:, 12:18]])\n        dq_r = np.linalg.lstsq(J_r, np.concatenate([err_rf_pos, err_rf_rot]), rcond=1e-4)[0]\n        \n        d.qpos[7:13] += dq_l\n        d.qpos[13:19] += dq_r\n    return d.qpos[7:19].copy()\n\n# Test recovering the t=0 pose!\n# At t=0 pose, feet were at [-0.020, +-0.20, 0.050] with yaw = +0.0378 rad -> so pelvis in board frame is at [+0.020, 0.0, 0.743] with yaw = -0.0378!\nq_sol = solve_ik([0.020, 0.0, 0.743], [0.0, 0.0, -0.0378])\nprint('Solved q_legs:', np.round(q_sol, 4))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nSolved q_legs: [-0.1056  0.1383 -0.0007  0.3115 -0.2035 -0.1331 -0.1313 -0.1125  0.0748\r\n  0.3177 -0.1931  0.1296]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":47,"t":1347.0,"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}}]}

runs/libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-privileged--czd5im8.json

@@ -0,0 +1 @@
+{"slug":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-privileged--czd5im8","task":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-privileged","bench":"libero-max","mode":"privileged","run":"claude_code-opus_5_5-high","agent":"claude-code","model":"claude-opus-5-5","effort":"high","state":"success","success":1,"reward":{"success":1,"deterministic":1,"missing_trajectory":0,"invalid_trajectory":0,"grader_error":0,"infra_error":0,"n_actions":123,"sim_steps":246,"event_fired":1,"video_rendered":1,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0.0,"peak_memory_gb":5.49,"peak_processes":22,"peak_disk_gb":0.25,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":1048,"tokens":{"in":758796,"cached":721197,"out":19075,"usd":0.83},"task_text":"# LIBERO-MAX · libero_spatial · sensor-noise onset — instance i01\n\nA **Franka Panda** arm (LIBERO on robosuite / MuJoCo) at a table. **Task: Pick the akita black bowl on the cookies box and place it on the plate.** LIBERO-PRO's initial-pose variant moved the target bowl (`akita_black_bowl_1`, the goal's) 0.17 m away from the robot and 0.06 m to the robot's right of where the sentence puts it, and turned it 45 degrees: it starts on the table, not on the cookies box (no bowl is on the box). The bowl to move is still that one; the other black bowl stands on top of the wooden cabinet.\nThe scene is one frozen LIBERO-MAX case: a LIBERO-PRO variant of a libero_spatial task (initial_pose_position_angle), with one online\nevent: the first time the gripper comes within 0.18 m of `akita_black_bowl_1`, LIBERO-MAX changes the scene\nonce (the camera images get noise (std 36 on 0..255) and a blocked patch (16% of the image)). You have the full simulator state, so you can see the change happen (`s.state()[\"event_fired\"]`).\n\n## What you hand in\n`/app/output/trajectory.npz` with key `actions`: LIBERO's native control steps, shape `(T, 7)`, 1 ≤ T ≤ 220\n(the libero_spatial step limit), one row per control step (1/20 s), starting after LIBERO's 10 warm-up steps (no-ops with the\ngripper open, already part of the frozen start). Write it with `s.save_trajectory()` so the format is right. Leave the\nscript that produced it at `/app/output/gen.py`.\n\n## Success\nThe verifier replays your actions from the frozen start in a separate sandbox (twice, each in a fresh process; the\nevent is applied by the same trigger), and applies LIBERO's own success check: the task's goal, all of\n- `akita_black_bowl_1` is on `plate_1` (LIBERO's On: `akita_black_bowl_1`'s origin is no lower than `plate_1`'s, less than 3 cm from it horizontally, and the two touch)\nThe episode ends the moment the check holds, so the trajectory must end there: actions after that make it invalid.\n`s.check()` computes exactly this check on the current state.\n\n## Tooling (`/opt/tools/lmx_tool.py`, importable as `lmx_tool`)\n```python\nimport numpy as np, lmx_tool\ns = lmx_tool.Session(\"/app/instance.json\")  # builds the frozen scene; ONE Session per Python process\nst = s.state()        # eef {pos, quat_wxyz}, gripper_qpos, joint_pos/vel, objects / fixtures {name: pos, quat_wxyz},\n                      #   articulations {joint: position} (drawer slides in m, door and knob hinges in rad),\n                      #   goal, instruction, success, done, event_fired, event_step, control_steps, steps_left\nr = s.step([dx, dy, dz, drx, dry, drz, grip])   # one control step -> {\"success\", \"done\", \"event_fired\", ...}\ns.check()             # LIBERO's success check on the current state\ns.save_trajectory()   # the actions so far -> /app/output/trajectory.npz\nlmx_tool.replay_fresh(A)   # replay A in a NEW process (what the verifier does) -> {\"success\", \"state_sha\", ...}\nimg = s.render(\"agentview\", 256)   # RGB, upright; cameras \"agentview\" \n… (651 characters left out) …\ntres; the robot's base is at (-0.66, 0, 0.912) facing +x: x forward (across the table), y to the robot's\n  left, z up; quaternions are w x y z.\n- Everything in `s.env` (robosuite's LIBERO environment) and `s.sim` is readable (privileged mode).\n\n## Rules\n- Write your own controller. Do not use LIBERO's demonstrations, LIBERO-MAX's policies or any published solution.\n- Only the actions count: editing the simulator state while debugging changes nothing in the replay.\n- Save a working trajectory early, then improve it; do not stop early.\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 4 cores for your container; the cap only slows you down.\n\n## Time limit\nYou have 1800 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":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-privileged--czd5im8/replay.mp4","replay_last":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-privileged--czd5im8/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"shell","label":"s=lmx_tool.Session(\"/app/instance.json\")","code":"cd /app; ls; cat instance.json | head -50; cat /run/rcb-limits/usage.json; cat > /tmp/probe.py <<'EOF'\nimport lmx_tool, json\ns=lmx_tool.Session(\"/app/instance.json\")\nst=s.state()\nprint(json.dumps({k:v for k,v in st.items() if k not in ('joint_pos','joint_vel')},indent=1,default=str))\nEOF\ntime python /tmp/probe.py"}],"out":{"text":"instance.json\noutput\n{\n \"case\": {\n  \"case_id\": \"pro-initial-pose-position-angle-spatial-t03-i00-sensor_noise_onset-d1-p195\",\n  \"dynamic_phase\": \"pre_grasp_proximity\",\n  \"init_state_index\": 0,\n  \"policy_seed\": 195,\n  \"scenario\": {\n   \"base_task_id\": \"libero-pro/initial_pose_position_angle/libero_spatial/task_3\",\n   \"change\": {\n    \"noise_std\": 36.0,\n    \"occlusion_fraction\": 0.16,\n    \"operation\": \"set_sensor_corruption\",\n    \"seed\": 677605823\n   },\n   \"change_family\": \"OBS\",\n   \"change_type\": \"sensor_noise_onset\",\n   \"expected_response_mode\": \"continue\",\n   \"randomization\": {\n    \"draw_id\": 1,\n    \"sampler\": \"libero-max-pro-hard-v1.0\",\n    \"seed\": 677605823\n   },\n   \"safety_constraints\": [\n    \"task_remains_feasible\",\n    \"no_simulator_error\",\n    \"no_new_unrelated_collision\"\n   ],\n   \"scenario_id\": \"pro-initial-pose-position-angle-spatial-t03-i00-sensor_noise_onset-d1\",\n   \"seed\": 677605823,\n   \"severity\": \"high\",\n   \"trigger\": {\n    \"distance_m\": 0.18,\n    \"type\": \"on_proximity\",\n    \"value\": \"akita_black_bowl_1\"\n   }\n  },\n  \"substrate_category\": \"LIBERO-PRO/initial_pose_position_angle\",\n  \"substrate_difficulty\": null,\n  \"substrate_variant\": {\n   \"bddl_file\": \"07_initial_pose_position_angle/bddl/libero_spatial/pick_up_the_black_bowl_on_the_cookie_box_and_place_it_on_the_plate.bddl\",\n   \"benchmark\": \"LIBERO-PRO\",\n   \"category\": \"initial_pose_position_angle\",\n   \"init_reference_bddl_file\": \"libero_spatial_lan/pick_up_the_black_bowl_on_the_cookie_box_and_place_it_on_the_plate.\n… (7,225 characters left out) …\n \"quat_wxyz\": \"[ 9.23879534e-01 -2.42950082e-05  1.36982171e-05  3.82683427e-01]\"\n  },\n  \"akita_black_bowl_2\": {\n   \"pos\": \"[ 0.02249322 -0.28417435  1.12639997]\",\n   \"quat_wxyz\": \"[ 7.07106783e-01 -1.49896965e-07  1.80135560e-08  7.07106780e-01]\"\n  },\n  \"cookies_1\": {\n   \"pos\": \"[0.06784034 0.02390589 0.90937071]\",\n   \"quat_wxyz\": \"[7.07106781e-01 6.20444782e-18 6.20444782e-18 7.07106781e-01]\"\n  },\n  \"glazed_rim_porcelain_ramekin_1\": {\n   \"pos\": \"[-0.21386081  0.21090334  0.89934112]\",\n   \"quat_wxyz\": \"[ 7.07106784e-01 -6.45442339e-08  1.61230065e-07  7.07106778e-01]\"\n  },\n  \"plate_1\": {\n   \"pos\": \"[0.06976893 0.19004477 0.90249958]\",\n   \"quat_wxyz\": \"[ 7.07106809e-01 -2.66056356e-05  1.20596073e-05  7.07106753e-01]\"\n  }\n },\n \"fixtures\": {\n  \"wooden_cabinet_1\": {\n   \"pos\": \"[ 0.0349183  -0.26615669  0.905     ]\",\n   \"quat_wxyz\": \"[0.22426622 0.         0.         0.97452792]\"\n  },\n  \"flat_stove_1\": {\n   \"pos\": \"[-0.41800477 -0.13723675  0.905     ]\",\n   \"quat_wxyz\": \"[1. 0. 0. 0.]\"\n  }\n },\n \"articulations\": {\n  \"wooden_cabinet_1_top_level\": 0.0,\n  \"wooden_cabinet_1_middle_level\": 0.0,\n  \"wooden_cabinet_1_bottom_level\": 0.0,\n  \"flat_stove_1_button\": 0.0\n },\n \"goal\": [\n  [\n   \"on\",\n   \"akita_black_bowl_1\",\n   \"plate_1\"\n  ]\n ],\n \"instruction\": \"Pick the akita black bowl on the cookies box and place it on the plate\",\n \"success\": false,\n \"done\": false,\n \"control_steps\": 0,\n \"event_fired\": false,\n \"event_step\": null,\n \"steps_left\": 220\n}\n\nreal\t1m40.897s\nuser\t0m41.966s\nsys\t0m3.406s","exit":[],"pics":[]},"tok":{"in":24288,"cached":18236,"out":246,"think":null,"usd":0.0388},"sim":{"submit":0,"reset":0}},{"id":3,"t":136.7,"say":"","calls":[{"kind":"robot","label":"mkdir -p /app/output; cat > /app/output/gen.py <<'EOF'","code":"mkdir -p /app/output; cat > /app/output/gen.py <<'EOF'\nimport numpy as np, lmx_tool, sys, time\ns = lmx_tool.Session(\"/app/instance.json\")\nsim = s.sim\ndef P(): return np.array(s.state()[\"eef\"][\"pos\"])\ndef Q(): return np.array(s.state()[\"eef\"][\"quat_wxyz\"])\ndef obj(n): return np.array(s.state()[\"objects\"][n][\"pos\"])\ndef q2m(q):\n    w,x,y,z=q\n    return np.array([[1-2*(y*y+z*z),2*(x*y-z*w),2*(x*z+y*w)],[2*(x*y+z*w),1-2*(x*x+z*z),2*(y*z-x*w)],[2*(x*z-y*w),2*(y*z+x*w),1-2*(x*x+y*y)]])\ndef m2aa(R):\n    c=np.clip((np.trace(R)-1)/2,-1,1); a=np.arccos(c)\n    if a<1e-6: return np.zeros(3)\n    v=np.array([R[2,1]-R[1,2],R[0,2]-R[2,0],R[1,0]-R[0,1]])/(2*np.sin(a))\n    return v*a\ndef Rz(t): c,s_=np.cos(t),np.sin(t); return np.array([[c,-s_,0],[s_,c,0],[0,0,1]])\n# finger closing axis\ntry:\n    import mujoco\n    m=sim.model._model if hasattr(sim.model,'_model') else sim.model\n    d=sim.data._data if hasattr(sim.data,'_data') else sim.data\n    bl=mujoco.mj_name2id(m,mujoco.mjtObj.mjOBJ_BODY,\"gripper0_leftfinger\"); br=mujoco.mj_name2id(m,mujoco.mjtObj.mjOBJ_BODY,\"gripper0_rightfinger\")\n    dv=d.xpos[bl]-d.xpos[br]; phi=np.arctan2(dv[1],dv[0])\n    # bowl xy extent\n    bb=mujoco.mj_name2id(m,mujoco.mjtObj.mjOBJ_BODY,\"akita_black_bowl_1_main\")\n    pts=[]\n    for g in range(m.ngeom):\n        if m.geom_bodyid[g]==bb and m.geom_type[g]==mujoco.mjtGeom.mjGEOM_MESH:\n            mi=m.geom_dataid[g]; v=m.mesh_vert[m.mesh_vertadr[mi]:m.mesh_vertadr[mi]+m.mesh_vertnum[mi]]\n            pts.append(v@d.geom_xmat[g].reshape(3,3).T+d.geom_xpos[g])\n    pts=np.vstack(pts); print(\"bowl extents\", pts.min(0), pts.max(0), file=sys.stderr)\n    bc=obj(\"akita_black_bowl_1\"); rad=float(np.max(np.linalg.norm(pts[:,:2]-bc[:2],axis=1))); ztop=pts[:,2].max()\nexcept Exception as e:\n    print(\"geom fail\",e,file=sys.stderr); phi=np.pi/2; rad=0.065; ztop=0.95\nprint(\"phi\",phi,\"rad\",rad,\"ztop\",ztop,file=sys.stderr)\ndl=-phi\nwhile dl>np.pi/2: dl-=np.pi\nwhile dl<-np.pi/2: dl+=np.pi\nR0=q2m(Q()); Rt=Rz(dl)@R0\ngrip=-1.0\ndef go(target, tol=0.01, maxn=80, kp=12.0, cond=None):\n    for i in range(maxn):\n        p=P(); e=target-p\n        rot=m2aa(Rt@q2m(Q()).T)\n        a=np.concatenate([np.clip(kp*e,-1,1),np.clip(rot/0.5*2.0,-1,1),[grip]])\n        r=s.step(a)\n        if r[\"success\"]: return \"succ\"\n        if cond and cond(): return \"cond\"\n        if np.linalg.norm(e)<tol and np.linalg.norm(rot)<0.05: return \"ok\"\n    return \"max\"\ndef hold(n):\n    for i in range(n):\n        p=P(); rot=m2aa(Rt@q2m(Q()).T)\n        r=s.step(np.concatenate([np.zeros(3),np.clip(rot/0.5*2,-1,1),[grip]]))\n        if r[\"success\"]: return \"succ\"\nbc=obj(\"akita_black_bowl_1\")\ngp=bc+np.array([-(rad-0.012),0,0])\nzg=ztop-0.03\nprint(go(np.array([gp[0],gp[1],ztop+0.08]),tol=0.015), P(), s.state()[\"control_steps\"],file=sys.stderr)\nprint(go(np.array([gp[0],gp[1],zg]),tol=0.008), P(), s.state()[\"control_steps\"],file=sys.stderr)\ngrip=1.0; hold(12)\nprint(\"closed\",s.state()[\"gripper_qpos\"],file=sys.stderr)\nprint(go(np.array([gp[0],gp[1],1.12]),tol=0.03), P(), obj(\"akita_black_bowl_1\"), s.state()[\"control_steps\"],file=sys.stderr)\noff=P()-obj(\"akita_black_bowl_1\")\npl=obj(\"plate_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])\nprint(go(tgt,tol=0.02), P(), obj(\"akita_black_bowl_1\"), s.state()[\"control_steps\"],file=sys.stderr)\noff=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],pl[2]+off[2]+0.0])\nres=go(tgt,tol=0.003,maxn=60,kp=5)\nprint(res, P(), obj(\"akita_black_bowl_1\"), s.state()[\"control_steps\"],file=sys.stderr)\nif res!=\"succ\":\n    grip=-1.0; res=hold(20)\nprint(\"final\",res,s.check(),s.state()[\"control_steps\"],file=sys.stderr)\nif s.check():\n    s.save_trajectory(); print(\"SAVED\",file=sys.stderr)\n    if len(sys.argv)>1:\n        A=np.load(\"/app/output/trajectory.npz\")[\"actions\"]; print(lmx_tool.replay_fresh(A),file=sys.stderr)\nEOF\ncd /tmp && time python /app/output/gen.py 2>&1 | grep -v -i warn"}],"out":{"text":"Command did not complete within its 120s timeout and was moved to the background (ID: bavpywdnw). Output is being written to: /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output. You will be notified when it completes. If it is still running after 10m in the background, it will be stopped and you will be notified. To check interim output, use Read on that file path.\nSession cwd remains /app; directory changes made by the backgrounded command do not apply to subsequent commands.","exit":[],"pics":[]},"tok":{"in":27187,"cached":24286,"out":5338,"think":null,"usd":0.1261},"sim":{"submit":0,"reset":0}},{"id":4,"t":275.8,"say":"","calls":[{"kind":"shell","label":"sleep 45; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output","code":"sleep 45; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output"}],"out":{"text":"Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.\nPlease upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.\nSee the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.15425154 -0.0326429   0.99594104] 80\nmax [ 0.14830352 -0.03236469  0.91305255] 160\nclosed [ 0.00198813 -0.02510356]\nmax [ 0.15448947 -0.03296132  1.08059948] [ 0.22082457 -0.03333226  1.07066723] 252\n\n[stdout]\nGym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.\nPlease upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.\nSee the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.15425154 -0.0326429   0.99594104] 80\nmax [ 0.14830352 -0.03236469  0.91305255] 160\nclosed [ 0.00198813 -0.02510356]\nmax [ 0.15448947 -0.03296132  1.08059948] [ 0.22082457 -0.03333226  1.07066723] 252","exit":[],"pics":[]},"tok":{"in":32736,"cached":27185,"out":109,"think":null,"usd":0.0354},"sim":{"submit":0,"reset":0}},{"id":5,"t":330.8,"say":"","calls":[{"kind":"shell","label":"sleep 20; tail -5 /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output","code":"sleep 20; tail -5 /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output"}],"out":{"text":"real\t3m5.182s\nuser\t5m10.075s\nsys\t0m9.792s\n\n[exited with code 0]\n\n[stdout]\nreal\t3m5.182s\nuser\t5m10.075s\nsys\t0m9.792s\n\n[exited with code 0]","exit":[],"pics":[]},"tok":{"in":33201,"cached":32734,"out":809,"think":null,"usd":0.0251},"sim":{"submit":0,"reset":0}},{"id":6,"t":353.7,"say":"","calls":[{"kind":"shell","label":"grep -v -i warn /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output | tail -8; grep","code":"grep -v -i warn /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output | tail -8; grep time_left /run/rcb-limits/usage.json"}],"out":{"text":"raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")\nValueError: a trajectory has 1..220 actions, got 319\n\nreal\t3m5.182s\nuser\t5m10.075s\nsys\t0m9.792s\n\n[exited with code 0]\n \"time_left_s\": 1355.0,\n\n[stdout]\n    raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")\nValueError: a trajectory has 1..220 actions, got 319\n\nreal\t3m5.182s\nuser\t5m10.075s\nsys\t0m9.792s\n\n[exited with code 0]\n \"time_left_s\": 1355.0,","exit":[],"pics":[]},"tok":{"in":36736,"cached":33199,"out":134,"think":null,"usd":0.027},"sim":{"submit":0,"reset":0}},{"id":7,"t":355.9,"say":"","calls":[{"kind":"shell","label":"grep -v -i warn /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output | grep -E \"max|","code":"grep -v -i warn /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bavpywdnw.output | grep -E \"max|ok|succ|final|cond|closed\""}],"out":{"text":"max [ 0.15425154 -0.0326429   0.99594104] 80\nmax [ 0.14830352 -0.03236469  0.91305255] 160\nclosed [ 0.00198813 -0.02510356]\nmax [ 0.15448947 -0.03296132  1.08059948] [ 0.22082457 -0.03333226  1.07066723] 252\nok [-0.00796075  0.18621635  1.11006711] [0.05755785 0.18666393 1.09450975] 282\nsucc [0.00328055 0.19044891 0.93219916] [0.06690778 0.19079017 0.9134021 ] 319\nfinal succ True 319\n    raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")\n\n[stdout]\nmax [ 0.15425154 -0.0326429   0.99594104] 80\nmax [ 0.14830352 -0.03236469  0.91305255] 160\nclosed [ 0.00198813 -0.02510356]\nmax [ 0.15448947 -0.03296132  1.08059948] [ 0.22082457 -0.03333226  1.07066723] 252\nok [-0.00796075  0.18621635  1.11006711] [0.05755785 0.18666393 1.09450975] 282\nsucc [0.00328055 0.19044891 0.93219916] [0.06690778 0.19079017 0.9134021 ] 319\nfinal succ True 319\n    raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")","exit":[],"pics":[]},"tok":{"in":37055,"cached":36734,"out":131,"think":null,"usd":0.0116},"sim":{"submit":0,"reset":0}},{"id":8,"t":364.3,"say":"","calls":[{"kind":"shell","label":"src=open('gen.py').read()","code":"cd /app/output && python - <<'EOF'\nsrc=open('gen.py').read()\nstart=src.index('bc=obj(\"akita_black_bowl_1\")\\ngp=')\nend=src.index('print(\"final\"')\nnew='''bc=obj(\"akita_black_bowl_1\")\ngp=bc+np.array([-(rad-0.012),0,0])\nzg=ztop-0.035\ndef lg(t): print(t, P(), obj(\"akita_black_bowl_1\"), s.state()[\"control_steps\"], file=sys.stderr)\nlg(go(np.array([gp[0],gp[1],ztop+0.06]),tol=0.02,maxn=35,cond=lambda: np.linalg.norm((P()-gp)[:2])<0.045))\nlg(go(np.array([gp[0],gp[1],zg]),tol=0.008,maxn=30,cond=lambda: P()[2]<zg+0.008))\ngrip=1.0; hold(9)\nprint(\"closed\",s.state()[\"gripper_qpos\"],file=sys.stderr)\npl=obj(\"plate_1\")\nlg(go(np.array([P()[0],P()[1],1.10]),maxn=25,cond=lambda: P()[2]>1.03))\noff=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],1.07])\nlg(go(tgt,tol=0.02,maxn=45,cond=lambda: np.linalg.norm((P()-tgt)[:2])<0.012))\noff=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],pl[2]+off[2]-0.01])\nres=go(tgt,tol=0.002,maxn=50,kp=8)\nlg(res)\nif res!=\"succ\":\n    grip=-1.0; res=hold(20)\n'''\nopen('gen.py','w').write(src[:start]+new+src[end:])\nEOF\ncd /tmp && timeout 600 python /app/output/gen.py replay 2>&1 | grep -v -i -E \"warn|gym|migration\""}],"out":{"text":"Command running in background with ID: belaoca97. Output is being written to: /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/belaoca97.output. You will be notified when it completes. To check interim output, use Read on that file path.\nSession cwd remains /app; directory changes made by the backgrounded command do not apply to subsequent commands.","exit":[],"pics":[]},"tok":{"in":37468,"cached":37053,"out":1273,"think":null,"usd":0.0349},"sim":{"submit":0,"reset":0}},{"id":9,"t":369.8,"say":"","calls":[{"kind":"shell","label":"sleep 150; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/belaoca97.output","code":"sleep 150; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/belaoca97.output"}],"out":{"text":"Exit code 143\nCommand timed out after 2m 0s\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":38906,"cached":37466,"out":107,"think":null,"usd":0.0168},"sim":{"submit":0,"reset":0}},{"id":10,"t":492.0,"say":"","calls":[{"kind":"shell","label":"cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/belaoca97.output; ls -la /app/output; grep t","code":"cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/belaoca97.output; ls -la /app/output; grep time_left /run/rcb-limits/usage.json"}],"out":{"text":"bowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13389491 -0.03575205  1.03175857] [ 0.21373241 -0.03721981  1.02943863] 59\nmax [0.07061878 0.21015436 1.13227633] [0.14406268 0.20751117 1.11088681] 104\nmax [0.08492838 0.21304747 0.98023548] [0.15651672 0.20982137 0.95728448] 154\nfinal None False 174\n\n[exited with code 0]\ntotal 12\ndrwxr-xr-x 2 root root 4096 Oct 16 01:24 .\ndrwxr-xr-x 3 root root 4096 Oct 16 01:19 ..\n-rw-r--r-- 1 root root 3688 Oct 16 01:28 gen.py\n \"time_left_s\": 1215.0,\n\n[stdout]\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13389491 -0.03575205  1.03175857] [ 0.21373241 -0.03721981  1.02943863] 59\nmax [0.07061878 0.21015436 1.13227633] [0.14406268 0.20751117 1.11088681] 104\nmax [0.08492838 0.21304747 0.98023548] [0.15651672 0.20982137 0.95728448] 154\nfinal None False 174\n\n[exited with code 0]\ntotal 12\ndrwxr-xr-x 2 root root 4096 Oct 16 01:24 .\ndrwxr-xr-x 3 root root 4096 Oct 16 01:19 ..\n-rw-r--r-- 1 root root 3688 Oct 16 01:28 gen.py\n \"time_left_s\": 1215.0,","exit":[],"pics":[]},"tok":{"in":40147,"cached":38904,"out":130,"think":null,"usd":0.0166},"sim":{"submit":0,"reset":0}},{"id":11,"t":509.2,"say":"","calls":[{"kind":"shell","label":"cd /app/output && sed -i 's/lg(go(np.array(\\[P()\\[0\\],P()\\[1\\],1.10\\]),maxn=25,cond=lambda: P()\\[2\\]>1.03))/lg","code":"cd /app/output && sed -i 's/lg(go(np.array(\\[P()\\[0\\],P()\\[1\\],1.10\\]),maxn=25,cond=lambda: P()\\[2\\]>1.03))/lg(go(np.array([P()[0],P()[1],1.14]),maxn=30,cond=lambda: P()[2]>1.08))/; s/tgt=np.array(\\[pl\\[0\\]+off\\[0\\],pl\\[1\\]+off\\[1\\],1.07\\])/tgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])/' gen.py && grep -n \"1.14\\|1.12\" gen.py && cd /tmp && timeout 600 python /app/output/gen.py replay 2>&1 | grep -v -i -E \"warn|gym|migration\""},{"kind":"shell","label":"sleep 110; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/b*.output | tail -12","code":"sleep 110; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/b*.output | tail -12"}],"out":{"text":"Command running in background with ID: bo5oazp62. Output is being written to: /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bo5oazp62.output. You will be notified when it completes. To check interim output, use Read on that file path.\nSession cwd remains /app; directory changes made by the backgrounded command do not apply to subsequent commands.\nfinal None False 174\n\n[exited with code 0]\n64:lg(go(np.array([P()[0],P()[1],1.14]),maxn=30,cond=lambda: P()[2]>1.08))\n66:tgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nmax [0.06410557 0.20886135 1.17960581] [0.13735326 0.20609238 1.15837196] 108\n\n[stdout]\nfinal None False 174\n\n[exited with code 0]\n64:lg(go(np.array([P()[0],P()[1],1.14]),maxn=30,cond=lambda: P()[2]>1.08))\n66:tgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nmax [0.06410557 0.20886135 1.17960581] [0.13735326 0.20609238 1.15837196] 108","exit":[],"pics":[]},"tok":{"in":40766,"cached":40145,"out":1797,"think":null,"usd":0.0471},"sim":{"submit":0,"reset":0}},{"id":12,"t":641.1,"say":"","calls":[{"kind":"shell","label":"src=open('gen.py').read()","code":"cd /app/output && python - <<'EOF'\nsrc=open('gen.py').read()\nsrc=src.replace('''off=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])''','''print(\"rot\",m2aa(Rt@q2m(Q()).T),\"q\",np.round(s.state()[\"joint_pos\"],2),file=sys.stderr)\nRt=q2m(Q())\noff=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],1.12])''')\nsrc=src.replace('''lg(go(tgt,tol=0.02,maxn=45,''','''lg(go(tgt,tol=0.02,maxn=45,kp=8,''')\nsrc=src.replace('''off=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],pl[2]''','''print(\"q\",np.round(s.state()[\"joint_pos\"],2),file=sys.stderr)\noff=P()-obj(\"akita_black_bowl_1\")\ntgt=np.array([pl[0]+off[0],pl[1]+off[1],pl[2]''')\nopen('gen.py','w').write(src)\nEOF\ncd /tmp && timeout 600 python /app/output/gen.py replay 2>&1 | grep -v -i -E \"warn|gym|migration\""},{"kind":"shell","label":"sleep 115; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bo5oazp62.output | tail -4; echo ","code":"sleep 115; cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bo5oazp62.output | tail -4; echo ----; ls -t /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/ | head -1 | xargs -I{} cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/{}"}],"out":{"text":"Command running in background with ID: bv2cy9jei. Output is being written to: /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bv2cy9jei.output. You will be notified when it completes. To check interim output, use Read on that file path.\nSession cwd remains /app; directory changes made by the backgrounded command do not apply to subsequent commands.\nExit code 123\nmax [0.08504793 0.2132321  0.98220055] [0.15642796 0.20977899 0.95877401] 158\nfinal None False 178\n\n[exited with code 0]\n----\ncat: /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bd599mxxo.output: input file is output file\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":43216,"cached":40764,"out":2148,"think":null,"usd":0.0634},"sim":{"submit":0,"reset":0}},{"id":13,"t":761.8,"say":"","calls":[{"kind":"shell","label":"cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bv2cy9jei.output; grep time_left /run/rcb-li","code":"cat /tmp/claude-0/-app/6c2679f6-9aa4-4878-bb99-2319ab1e62b1/tasks/bv2cy9jei.output; grep time_left /run/rcb-limits/usage.json"}],"out":{"text":"bowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nrot [-0.00031763 -0.00493944 -0.00054157] q [-0.06  1.44 -0.02 -0.11  0.08  1.54  2.3 ]\nmax [0.07017731 0.20789677 1.1871578 ] [0.14407263 0.20536665 1.168153  ] 108\nq [ 0.26  1.32  0.01 -0.07  0.05  1.3   2.63]\nmax [0.08417892 0.21248605 0.97959653] [0.15550909 0.20925505 0.95589351] 158\nfinal None False 178\n\n[exited with code 0]\n \"time_left_s\": 945.0,\n\n[stdout]\nbowl extents [ 0.18185331 -0.09212782  0.89839675] [0.29388491 0.01930791 0.95104244]\nphi -1.5716353303044588 rad 0.05624479217185134 ztop 0.9510424390496106\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nrot [-0.00031763 -0.00493944 -0.00054157] q [-0.06  1.44 -0.02 -0.11  0.08  1.54  2.3 ]\nmax [0.07017731 0.20789677 1.1871578 ] [0.14407263 0.20536665 1.168153  ] 108\nq [ 0.26  1.32  0.01 -0.07  0.05  1.3   2.63]\nmax [0.08417892 0.21248605 0.97959653] [0.15550909 0.20925505 0.95589351] 158\nfinal None False 178\n\n[exited with code 0]\n \"time_left_s\": 945.0,","exit":[],"pics":[]},"tok":{"in":47205,"cached":43214,"out":124,"think":null,"usd":0.0311},"sim":{"submit":0,"reset":0}},{"id":14,"t":816.1,"say":"","calls":[{"kind":"shell","label":"grep -n \"def save_trajectory\" -A12 /opt/tools/lmx_tool.py | head -30","code":"grep -n \"def save_trajectory\" -A12 /opt/tools/lmx_tool.py | head -30"}],"out":{"text":"241:    def save_trajectory(self, actions=None, path=\"/app/output/trajectory.npz\", meta: dict | None = None) -> str:\n242-        a = as_actions(self.actions if actions is None else actions)\n243-        if not 1 <= len(a) <= self.max_steps:\n244-            raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")\n245-        Path(path).parent.mkdir(parents=True, exist_ok=True)\n246-        np.savez(path, actions=a, meta=np.array(canonical(meta or {})))\n247-        return str(path)\n248-\n249-    # -- state ---------------------------------------------------------------------------------------------------\n250-    def state_sha(self) -> str:\n251-        return _integration_sha(self.sim)\n252-\n253-    def entity_pose(self, name: str) -> dict:\n\n[stdout]\n241:    def save_trajectory(self, actions=None, path=\"/app/output/trajectory.npz\", meta: dict | None = None) -> str:\n242-        a = as_actions(self.actions if actions is None else actions)\n243-        if not 1 <= len(a) <= self.max_steps:\n244-            raise ValueError(f\"a trajectory has 1..{self.max_steps} actions, got {len(a)}\")\n245-        Path(path).parent.mkdir(parents=True, exist_ok=True)\n246-        np.savez(path, actions=a, meta=np.array(canonical(meta or {})))\n247-        return str(path)\n248-\n249-    # -- state ---------------------------------------------------------------------------------------------------\n250-    def state_sha(self) -> str:\n251-        return _integration_sha(self.sim)\n252-\n253-    def entity_pose(self, name: str) -> dict:","exit":[],"pics":[]},"tok":{"in":47816,"cached":47203,"out":4398,"think":null,"usd":0.1005},"sim":{"submit":0,"reset":0}},{"id":15,"t":818.4,"say":"","calls":[{"kind":"shell","label":"src=open('gen.py').read()","code":"cd /app/output && python - <<'EOF'\nsrc=open('gen.py').read()\nsrc=src.replace('import numpy as np, lmx_tool, sys, time','import numpy as np, lmx_tool, sys, time, os\\nVAR=os.environ.get(\"VAR\",\"A\")')\n# approach clip for C\nsrc=src.replace('gp=bc+np.array([-(rad-0.012),0,0])','gp=bc+np.array([-(rad-0.012),0,0])\\nif VAR==\"C\": gp[0]=min(gp[0],0.165)')\nsrc=src.replace('lg(go(np.array([P()[0],P()[1],1.14]),maxn=30,cond=lambda: P()[2]>1.08))',\n'''lx=gp[0] if VAR==\"A\" else P()[0]\nlg(go(np.array([lx,P()[1],1.14]),maxn=30,cond=lambda: P()[2]>1.08))''')\nsrc=src.replace('''Rt=q2m(Q())\noff=P()-obj(\"akita_black_bowl_1\")''','''Rt=q2m(Q())\nif VAR==\"B\":\n    t0=P()+np.array([-0.07,0.03,-0.03]); lg(go(t0,tol=0.015,maxn=25,kp=8))\noff=P()-obj(\"akita_black_bowl_1\")''')\nsrc=src.replace('''    s.save_trajectory(); print(\"SAVED\",file=sys.stderr)\n    if len(sys.argv)>1:\n        A=np.load(\"/app/output/trajectory.npz\")[\"actions\"]; print(lmx_tool.replay_fresh(A),file=sys.stderr)''',\n'''    out=\"/app/output/trajectory.npz\" if len(sys.argv)<2 else f\"/tmp/traj_{VAR}.npz\"\n    s.save_trajectory(path=out); print(\"SAVED\",out,file=sys.stderr)''')\nopen('gen.py','w').write(src)\nEOF\ncd /tmp; for v in A B C; do (VAR=$v timeout 400 python /app/output/gen.py x 2>&1 | grep -v -i -E \"warn|gym|migration\" > /tmp/run_$v.log) & done; sleep 5; grep -n VAR /app/output/gen.py"}],"out":{"text":"2:VAR=os.environ.get(\"VAR\",\"A\")\n58:if VAR==\"C\": gp[0]=min(gp[0],0.165)\n66:lx=gp[0] if VAR==\"A\" else P()[0]\n70:if VAR==\"B\":\n84:    out=\"/app/output/trajectory.npz\" if len(sys.argv)<2 else f\"/tmp/traj_{VAR}.npz\"\nShell cwd was reset to /app\n\n[stdout]\n2:VAR=os.environ.get(\"VAR\",\"A\")\n58:if VAR==\"C\": gp[0]=min(gp[0],0.165)\n66:lx=gp[0] if VAR==\"A\" else P()[0]\n70:if VAR==\"B\":\n84:    out=\"/app/output/trajectory.npz\" if len(sys.argv)<2 else f\"/tmp/traj_{VAR}.npz\"\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":52538,"cached":47814,"out":867,"think":null,"usd":0.0505},"sim":{"submit":0,"reset":0}},{"id":16,"t":831.6,"say":"","calls":[{"kind":"shell","label":"sleep 100; tail -n +3 /tmp/run_*.log; grep time_left /run/rcb-limits/usage.json","code":"sleep 100; tail -n +3 /tmp/run_*.log; grep time_left /run/rcb-limits/usage.json"}],"out":{"text":"==> /tmp/run_A.log <==\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.1502084  -0.03099434  1.08251352] [ 0.22829923 -0.03330485  1.08061743] 74\nrot [0.0044412  0.06552832 0.00339084] q [-0.03  1.1  -0.04 -0.77  0.1   1.93  2.28]\nok [-0.01492662  0.18151617  1.1098894 ] [0.06167107 0.17890341 1.10366119] 104\nq [ 0.17  0.48  0.11 -1.78 -0.03  2.34  2.64]\nsucc [-0.01077036  0.19179695  0.92732656] [0.06444333 0.18851027 0.91830835] 123\nfinal succ True 123\nSAVED /tmp/traj_A.npz\n\n==> /tmp/run_B.log <==\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nrot [-0.00031763 -0.00493944 -0.00054157] q [-0.06  1.44 -0.02 -0.11  0.08  1.54  2.3 ]\nmax [ 0.11679466 -0.01035023  1.09935752] [ 0.19274801 -0.0123257   1.08482458] 88\nmax [0.07114426 0.20809317 1.1854663 ] [0.14369866 0.20537703 1.16430726] 133\n\n==> /tmp/run_C.log <==\ncond [ 0.12327906 -0.03579123  1.00116329] [ 0.23771632 -0.03629153  0.89840415] 33\nmax [ 0.14351611 -0.03631476  0.92550084] [ 0.23795128 -0.03591101  0.91006682] 63\nclosed [ 0.00658627 -0.01223809]\ncond [ 0.12556233 -0.03565062  1.08533983] [ 0.23687968 -0.03595878  0.898403\n… (503 characters left out) …\n099434  1.08251352] [ 0.22829923 -0.03330485  1.08061743] 74\nrot [0.0044412  0.06552832 0.00339084] q [-0.03  1.1  -0.04 -0.77  0.1   1.93  2.28]\nok [-0.01492662  0.18151617  1.1098894 ] [0.06167107 0.17890341 1.10366119] 104\nq [ 0.17  0.48  0.11 -1.78 -0.03  2.34  2.64]\nsucc [-0.01077036  0.19179695  0.92732656] [0.06444333 0.18851027 0.91830835] 123\nfinal succ True 123\nSAVED /tmp/traj_A.npz\n\n==> /tmp/run_B.log <==\nmax [ 0.14103318 -0.03572173  0.99555302] [ 0.23771632 -0.03629153  0.89840415] 35\ncond [ 0.14637111 -0.03573405  0.92083574] [ 0.23373217 -0.03624842  0.90997103] 41\nclosed [ 0.00643216 -0.03166165]\ncond [ 0.13225046 -0.03559057  1.08646282] [ 0.21145761 -0.03721601  1.08327974] 63\nrot [-0.00031763 -0.00493944 -0.00054157] q [-0.06  1.44 -0.02 -0.11  0.08  1.54  2.3 ]\nmax [ 0.11679466 -0.01035023  1.09935752] [ 0.19274801 -0.0123257   1.08482458] 88\nmax [0.07114426 0.20809317 1.1854663 ] [0.14369866 0.20537703 1.16430726] 133\n\n==> /tmp/run_C.log <==\ncond [ 0.12327906 -0.03579123  1.00116329] [ 0.23771632 -0.03629153  0.89840415] 33\nmax [ 0.14351611 -0.03631476  0.92550084] [ 0.23795128 -0.03591101  0.91006682] 63\nclosed [ 0.00658627 -0.01223809]\ncond [ 0.12556233 -0.03565062  1.08533983] [ 0.23687968 -0.03595878  0.89840386] 85\nrot [-0.0004458   0.00036592 -0.00028836] q [-0.02  0.99 -0.07 -0.93  0.12  1.92  2.26]\nok [-0.04690351  0.17841113  1.11111744] [ 0.2368797  -0.03595878  0.89840415] 114\nq [ 0.15  0.42  0.13 -1.87  0.    2.3   2.63]\n \"time_left_s\": 775.0,","exit":[],"pics":[]},"tok":{"in":53581,"cached":52536,"out":211,"think":null,"usd":0.02},"sim":{"submit":0,"reset":0}},{"id":17,"t":934.0,"say":"Variant A, which keeps pushing forward while lifting just as run 1 did, succeeded in 123 steps. I'm copying it to the deliverable and replaying it in a fresh process, the way the verifier does.","calls":[{"kind":"shell","label":"cp /tmp/traj_A.npz /app/output/trajectory.npz; pkill -f \"gen.py x\"; cd /tmp && timeout 300 python -c \"","code":"cp /tmp/traj_A.npz /app/output/trajectory.npz; pkill -f \"gen.py x\"; cd /tmp && timeout 300 python -c \"\nimport numpy as np, lmx_tool\nA=np.load('/app/output/trajectory.npz')['actions']; print(A.shape)\nprint(lmx_tool.replay_fresh(A))\" 2>&1 | grep -v -i -E \"warn|gym|migration\""}],"out":{"text":"Exit code 144\n\n[error] tool reported failure","exit":[],"pics":[]},"tok":{"in":54910,"cached":53579,"out":288,"think":null,"usd":0.0231},"sim":{"submit":0,"reset":0}},{"id":18,"t":937.1,"say":"","calls":[{"kind":"shell","label":"ls -la /app/output; cd /tmp && timeout 280 python -c \"","code":"ls -la /app/output; cd /tmp && timeout 280 python -c \"\nimport numpy as np, lmx_tool\nA=np.load('/app/output/trajectory.npz')['actions']; print(A.shape)\nprint(lmx_tool.replay_fresh(A))\" 2>&1 | grep -v -i -E \"warn|gym|migration\""}],"out":{"text":"total 20\ndrwxr-xr-x 2 root root 4096 Oct 16 01:37 .\ndrwxr-xr-x 3 root root 4096 Oct 16 01:19 ..\n-rw-r--r-- 1 root root 4006 Oct 16 01:35 gen.py\n-rw-r--r-- 1 root root 7404 Oct 16 01:37 trajectory.npz\n(123, 7)\n{'success': True, 'done': True, 'control_steps': 123, 'event_fired': True, 'event_step': 29, 'steps_left': 97, 'state_sha': '95f4d51baf6aed52b78342fa7f1524e52fbc335281291533a72d774e1a1e7b47', 'initial_state_sha': '0a8e9a1f00e077d494f0ef4ba7183d1f14dd06b83acad89fc2b1a3acce185ed3'}\nShell cwd was reset to /app\n\n[stdout]\ntotal 20\ndrwxr-xr-x 2 root root 4096 Oct 16 01:37 .\ndrwxr-xr-x 3 root root 4096 Oct 16 01:19 ..\n-rw-r--r-- 1 root root 4006 Oct 16 01:35 gen.py\n-rw-r--r-- 1 root root 7404 Oct 16 01:37 trajectory.npz\n(123, 7)\n{'success': True, 'done': True, 'control_steps': 123, 'event_fired': True, 'event_step': 29, 'steps_left': 97, 'state_sha': '95f4d51baf6aed52b78342fa7f1524e52fbc335281291533a72d774e1a1e7b47', 'initial_state_sha': '0a8e9a1f00e077d494f0ef4ba7183d1f14dd06b83acad89fc2b1a3acce185ed3'}\n[stderr]\n\nShell cwd was reset to /app","exit":[],"pics":[]},"tok":{"in":55239,"cached":54908,"out":219,"think":null,"usd":0.017},"sim":{"submit":0,"reset":0}},{"id":19,"t":1029.8,"say":"The task is done. `/app/output/trajectory.npz` holds 123 control steps that put `akita_black_bowl_1` on `plate_1`. I replayed it in a fresh process, the way the verifier does: it succeeded and stopped at exactly step 123, with 97 steps to spare. The sensor-noise event fired at step 29; it only corrupts the camera images, and the controller reads the simulator state directly, so it has no effect.\n\n**How the controller works** (`/app/output/gen.py`):\n1. It reads the bowl's real size from the simulator's mesh (radius about 5.6 cm, rim top at z≈0.95). It also finds which way the fingers close and turns the hand 90° about the vertical so they close along x.\n2. It moves above the bowl's near rim, which is the side closest to the robot, lowers the hand and closes the gripper.\n3. It lifts to about 1.08 m, then carries the bowl over the plate at about 1.12 m, high enough to clear the cookies box.\n4. It lowers the bowl onto the plate and stops on the first step where LIBERO's success check passes.\n\n**The one real problem was reach.** The bowl's near rim (x≈0.18) is past where the hand can comfortably get, so at the grasp the arm is fully stretched with the elbow at its joint limit. From that pose, two of my runs couldn't pull the hand back toward the plate: it drifted upward and stalled about 7 cm short. The version that works keeps pushing forward while lifting, which leaves the elbow bent enough to pull back afterwards. I found that fix by comparing runs rather than by fully explaining the cause, so the margin isn't well understood. Still, the replay matches the original run exactly (123 steps in both), so the verifier should get the same result.\n\n`gen.py` has three variants, chosen with the environment variable `VAR`. The default, `A`, produces the trajectory above; `B` and `C` were the other two attempts. Run as `python /app/output/gen.py` with no arguments, it writes straight to `/app/output/trajectory.npz`.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":55801,"cached":55237,"out":746,"think":null,"usd":0.0288},"sim":{"submit":0,"reset":0}}]}

runs/libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-standard--nmbnhv7.json

@@ -0,0 +1 @@
+{"slug":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-standard--nmbnhv7","task":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-standard","bench":"libero-max","mode":"standard","run":"antigravity_cli-gemini_4_argon-high","agent":"antigravity_sub:AntigravitySubscription","model":"gemini-4-argon","effort":"high","state":"success","success":1,"reward":{"success":1,"live_success":1,"replay_success":1,"deterministic":1,"replayed":1,"finalized":1,"missing_log":0,"infra_error":0,"grader_error":0,"timeout":0,"sim_error":0,"sim_crashed_on_call":0,"n_actions":342,"sim_steps":342,"calls":44,"rows":342,"resets":0,"reset_budget":0,"sim_startups":1,"elapsed_s":955.9,"video_rendered":1,"resource_enforced":0,"limits_violation_observed":0,"resource_monitor_missing":0,"peak_gpu_memory_gb":0,"peak_memory_gb":0.379,"peak_processes":9,"peak_disk_gb":0.198,"resource_emergency_kills":0,"resource_oom_kills":0,"resource_host_oom_kills":0,"resource_service_oom_kills":0},"wall_s":1086,"tokens":{"in":3232256,"cached":3062263,"out":43950,"usd":1.3},"task_text":"","step_times":"recorded","sim_total":{"submit":19,"reset":0},"replay":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-standard--nmbnhv7/replay.mp4","replay_last":"libero-max-spatial-akita-black-bowl-on-plate-sensor-noise-onset-i01-standard--nmbnhv7/replay_last.jpg","steps":[{"id":2,"t":0.0,"say":"","calls":[{"kind":"robot","label":"Getting initial robot observation and spec","code":"mkdir -p /app/output /tmp/work\npython3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, json, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nspec = r.spec()\nstatus = r.status()\nprint('STATUS:', json.dumps(status, indent=2))\nprint('SPEC KEYS:', list(spec.keys()))\nwith open('/tmp/work/spec.json', 'w') as f:\n    json.dump(spec, f, indent=2)\n\nobs = r.get_obs(include_depth=True)\nprint('OBS META:', json.dumps(obs.meta, indent=2))\nfor cam, data in obs.last.items():\n    print(cam, data.keys())\n    if 'rgb' in data:\n        Image.fromarray(data['rgb']).save(f'/tmp/work/init_{cam}_rgb.png')\n    if 'depth' in data:\n        np.save(f'/tmp/work/init_{cam}_depth.npy', data['depth'])\n        print(cam, 'depth shape/min/max:', data['depth'].shape, np.min(data['depth']), np.max(data['depth']))\n\""}],"out":{"text":"The command exited with code 1.\nOutput:\nSTATUS: {\r\n  \"calls\": 0,\r\n  \"rows\": 0,\r\n  \"control_steps\": 0,\r\n  \"done\": false,\r\n  \"reason\": null,\r\n  \"elapsed_s\": 0.0\r\n}\r\nSPEC KEYS: ['protocol', 'control_dt', 'max_control_steps', 'max_chunk_s', 'max_watch_s', 'max_video_fps', 'max_frames_per_call', 'proprio_layout', 'budget', 'clock', 'on_service_error', 'simulator', 'robot', 'task_text', 'episode', 'frames', 'action_types', 'cameras']\r\nOBS META: {\r\n  \"calls\": 1,\r\n  \"rows\": 0,\r\n  \"control_steps\": 0,\r\n  \"done\": false,\r\n  \"reason\": null,\r\n  \"sim_time_s\": 0.0,\r\n  \"time_s\": 0.3,\r\n  \"time_left_s\": 1799.7,\r\n  \"proprio\": {\r\n    \"layout\": [\r\n      \"eef_x\",\r\n      \"eef_y\",\r\n      \"eef_z\",\r\n      \"eef_qw\",\r\n      \"eef_qx\",\r\n      \"eef_qy\",\r\n      \"eef_qz\",\r\n      \"finger_left\",\r\n      \"finger_right\",\r\n      \"joint1_pos\",\r\n      \"joint2_pos\",\r\n      \"joint3_pos\",\r\n      \"joint4_pos\",\r\n      \"joint5_pos\",\r\n      \"joint6_pos\",\r\n      \"joint7_pos\",\r\n      \"joint1_vel\",\r\n      \"joint2_vel\",\r\n      \"joint3_vel\",\r\n      \"joint4_vel\",\r\n      \"joint5_vel\",\r\n      \"joint6_vel\",\r\n      \"joint7_vel\",\r\n      \"cmd_dx\",\r\n      \"cmd_dy\",\r\n      \"cmd_dz\",\r\n      \"cmd_drx\",\r\n      \"cmd_dry\",\r\n      \"cmd_drz\",\r\n      \"cmd_grip\"\r\n    ],\r\n    \"now\": [\r\n      -0.20616070926189423,\r\n      -0.008142189122736454,\r\n      1.1739745140075684,\r\n      -0.0001754242111928761,\r\n      0.999615490436554,\r\n      -0.0004330813535489142,\r\n      -0.0277246180921793,\r\n      0.038729485124349594,\r\n      -0.03872883692383766,\r\n      -0.004546823911368847,\r\n      -0.15568284690380096,\r\n      -0.01306992955505848,\r\n      -2.4368932247161865,\r\n      -0.003320415038615465,\r\n      2.225496530532837,\r\n      0.7714083194732666,\r\n      0.0009183547808788717,\r\n      0.013154068030416965,\r\n      2.6527057343628258e-05,\r\n      0.023136332631111145,\r\n      -0.001123550464399159,\r\n      -0.028447186574339867,\r\n      -0.0012604565126821399,\r\n      0.0,\r\n      0.0,\r\n      0.0,\r\n      0.0,\r\n      0.0,\r\n      0.0,\r\n      -1.0\r\n    ]\r\n  },\r\n  \"obs_id\": 1,\r\n  \"seconds\": 0.0,\r\n  \"control_steps_watch\": 0,\r\n  \"ok\": true\r\n}\r\nTraceback (most recent call last):\r\n  File \"<string>\", line 18, in <module>\r\nAttributeError: 'numpy.ndarray' object has no attribute 'keys'","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":3,"t":15.0,"say":"","calls":[{"kind":"robot","label":"Saving initial images, depth, and viewing spec","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, json, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True)\nprint('obs.last keys:', list(obs.last.keys()))\nfor k, v in obs.last.items():\n    print(k, v.shape, v.dtype, np.min(v), np.max(v))\n    if v.dtype == np.uint8:\n        Image.fromarray(v).save(f'/tmp/work/init_{k}.png')\n    else:\n        np.save(f'/tmp/work/init_{k}.npy', v)\n\" && cat /tmp/work/spec.json"}],"out":{"text":"The command exited with code 0.\nOutput:\nobs.last keys: ['agentview', 'wrist']\r\nagentview (256, 256, 3) uint8 4 246\r\nwrist (256, 256, 3) uint8 2 246\r\n{\r\n  \"protocol\": \"eai-standard/2.1\",\r\n  \"control_dt\": 0.05,\r\n  \"max_control_steps\": 9000,\r\n  \"max_chunk_s\": 10.0,\r\n  \"max_watch_s\": 30.0,\r\n  \"max_video_fps\": 30,\r\n  \"max_frames_per_call\": 3000,\r\n  \"proprio_layout\": [\r\n    \"eef_x\",\r\n    \"eef_y\",\r\n    \"eef_z\",\r\n    \"eef_qw\",\r\n    \"eef_qx\",\r\n    \"eef_qy\",\r\n    \"eef_qz\",\r\n    \"finger_left\",\r\n    \"finger_right\",\r\n    \"joint1_pos\",\r\n    \"joint2_pos\",\r\n    \"joint3_pos\",\r\n    \"joint4_pos\",\r\n    \"joint5_pos\",\r\n    \"joint6_pos\",\r\n    \"joint7_pos\",\r\n    \"joint1_vel\",\r\n    \"joint2_vel\",\r\n    \"joint3_vel\",\r\n    \"joint4_vel\",\r\n    \"joint5_vel\",\r\n    \"joint6_vel\",\r\n    \"joint7_vel\",\r\n    \"cmd_dx\",\r\n    \"cmd_dy\",\r\n    \"cmd_dz\",\r\n    \"cmd_drx\",\r\n    \"cmd_dry\",\r\n    \"cmd_drz\",\r\n    \"cmd_grip\"\r\n  ],\r\n  \"budget\": {\r\n    \"reset\": 0,\r\n    \"wall_clock_s\": 1800.0\r\n  },\r\n  \"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\",\r\n  \"on_service_error\": \"if a call fails with a connection error or a 5xx, the service may have crashed and resumed the same episode (never a reset): the state is the one after the last call that completed on the service, which you may not have received; check GET /status before continuing\",\r\n  \"simulator\": \"LIBERO (robosuite 1.4.0, MuJoCo 3.2.6) with LIBERO-PRO's task variant and LIBERO-MAX's event\",\r\n  \"robot\"\n… (2,236 characters left out) …\n         0.7779982437565529,\r\n          0.6282664504107283,\r\n          1.6103500240372424\r\n        ],\r\n        [\r\n          0.0,\r\n          0.0,\r\n          0.0,\r\n          1.0\r\n        ]\r\n      ],\r\n      \"mounted\": \"fixed\",\r\n      \"note\": \"the pose and intrinsics at the start; every submit response carries the current ones (meta['cameras_now'])\"\r\n    },\r\n    \"wrist\": {\r\n      \"rgb\": true,\r\n      \"depth\": true,\r\n      \"hw\": [\r\n        256,\r\n        256\r\n      ],\r\n      \"intrinsic_cv\": [\r\n        [\r\n          166.81284772367434,\r\n          0,\r\n          128.0\r\n        ],\r\n        [\r\n          0,\r\n          166.81284772367434,\r\n          128.0\r\n        ],\r\n        [\r\n          0,\r\n          0,\r\n          1\r\n        ]\r\n      ],\r\n      \"cam2world_gl\": [\r\n        [\r\n          -0.00083900336886511,\r\n          0.9984494017799057,\r\n          0.05566047213861408,\r\n          -0.150810549954177\r\n        ],\r\n        [\r\n          -0.9999995976622835,\r\n          -0.0008200355045998586,\r\n          -0.00036361661191254904,\r\n          -0.00821575681701501\r\n        ],\r\n        [\r\n          -0.0003174092252848648,\r\n          -0.05566075481986925,\r\n          0.9984496880786052,\r\n          1.2680609421909737\r\n        ],\r\n        [\r\n          0.0,\r\n          0.0,\r\n          0.0,\r\n          1.0\r\n        ]\r\n      ],\r\n      \"mounted\": \"on the hand (moves with it)\",\r\n      \"note\": \"the pose and intrinsics at the start; every submit response carries the current ones (meta['cameras_now'])\"\r\n    }\r\n  }\r\n}","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":4,"t":31.0,"say":"","calls":[{"kind":"shell","label":"reads rcb_client.py","code":"/opt/tools/rcb_client.py"},{"kind":"look","label":"init_agentview.png","code":"/tmp/work/init_agentview.png"},{"kind":"look","label":"init_wrist.png","code":"/tmp/work/init_wrist.png"}],"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… (9,224 characters left out) …\n    # the service would close the connection on it unread\n170:             raise ValueError(f\"{path}: {len(body)} bytes, over the protocol's {MAX_BODY}: send fewer rows\")\n171:         r = requests.post(self.base + path, data=body, headers={\"Content-Type\": \"application/x-rcb1\"},\n172:                           timeout=(5, timeout))\n173:         if r.headers.get(\"Content-Type\", \"\").startswith(\"application/x-rcb1\") and r.status_code == 200:\n174:             return Result(*rcb1.decode(r.content))\n175:         try:\n176:             err = r.json()\n177:         except ValueError:\n178:             err = {\"error\": r.text[:300]}\n179:         msg = f\"{r.status_code} {path}: {err.get('error')}\" + (f\" ({err['detail']})\" if err.get(\"detail\") else \"\")\n180:         if r.status_code == 409:\n181:             raise EpisodeOver(msg + (f\"; reason {err['reason']}\" if err.get(\"reason\") else \"\")\n182:                               + (f\"; resets_left {err['resets_left']}\" if \"resets_left\" in err else \"\"))\n183:         if r.status_code in (400, 413):\n184:             raise ValueError(msg)\n185:         raise RuntimeError(msg)\n186: \n187: \n188: def _names(cameras) -> list[str] | None:\n189:     return None if cameras is None else [cameras] if isinstance(cameras, str) else list(cameras)\n190: \nThe above content shows the entire, complete file contents 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":5,"t":41.0,"say":"","calls":[{"kind":"robot","label":"Verifying 3D point cloud projection from depth cameras","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, json, numpy as np\n\nr = rcb_client.Robot()\nspec = r.spec()\nobs = r.get_obs(include_depth=True)\n\nfor cam in ['agentview', 'wrist']:\n    d = obs.depth[cam][0].astype(np.float64)\n    rgb = obs.last[cam]\n    K = np.array(spec['cameras'][cam]['intrinsic_cv'])\n    c2w = np.array(spec['cameras'][cam]['cam2world_gl'])\n    fx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\n    v, u = np.mgrid[0:256, 0:256]\n    x_gl = (u - cx) * d / fx\n    y_gl = -(v - cy) * d / fy\n    z_gl = -d\n    pts_gl = np.stack([x_gl, y_gl, z_gl, np.ones_like(d)], axis=-1)\n    pts_w = pts_gl @ c2w.T\n    pts_w = pts_w[..., :3]\n    print(f'=== {cam} ===')\n    print('center pixel (128,128) depth:', d[128,128], 'world:', pts_w[128,128])\n    np.save(f'/tmp/work/pts_{cam}.npy', pts_w)\n    np.save(f'/tmp/work/depth_{cam}.npy', d)\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\n=== agentview ===\r\ncenter pixel (128,128) depth: 1.126953125 world: [-2.18154377e-01 -1.71426774e-07  9.02323184e-01]\r\n=== wrist ===\r\ncenter pixel (128,128) depth: 0.36865234375 world: [-0.17132991 -0.00808171  0.89998012]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":6,"t":62.0,"say":"","calls":[{"kind":"shell","label":"Analyzing 3D coordinates of bowl and plate","code":"python3 -c \"\nimport numpy as np\nfrom PIL import Image\n\npts = np.load('/tmp/work/pts_agentview.npy')\nrgb = np.array(Image.open('/tmp/work/init_agentview.png'))\n\n# Table z is ~0.900\n# Let's inspect objects in agentview:\n# 1. Target bowl (akita_black_bowl_1): v in [210, 255], u in [85, 140]\nbowl_patch = pts[210:255, 85:140]\nbowl_rgb = rgb[210:255, 85:140]\n# Filter points elevated above table (z > 0.908)\nbowl_mask = bowl_patch[..., 2] > 0.908\nbowl_pts = bowl_patch[bowl_mask]\nprint('Target bowl pts count:', len(bowl_pts))\nprint('Target bowl x min/max/mean/median:', np.min(bowl_pts[:,0]), np.max(bowl_pts[:,0]), np.mean(bowl_pts[:,0]), np.median(bowl_pts[:,0]))\nprint('Target bowl y min/max/mean/median:', np.min(bowl_pts[:,1]), np.max(bowl_pts[:,1]), np.mean(bowl_pts[:,1]), np.median(bowl_pts[:,1]))\nprint('Target bowl z min/max/mean:', np.min(bowl_pts[:,2]), np.max(bowl_pts[:,2]), np.mean(bowl_pts[:,2]))\n\n# Rim points of target bowl (z > 0.95)\nrim_mask = bowl_patch[..., 2] > 0.95\nrim_pts = bowl_patch[rim_mask]\nprint('Target bowl rim (z>0.95) count:', len(rim_pts))\nif len(rim_pts) > 0:\n    print('Rim center (min+max)/2:', (np.min(rim_pts, axis=0) + np.max(rim_pts, axis=0))/2)\n    print('Rim mean:', np.mean(rim_pts, axis=0))\n    print('Rim x range:', np.min(rim_pts[:,0]), np.max(rim_pts[:,0]))\n    print('Rim y range:', np.min(rim_pts[:,1]), np.max(rim_pts[:,1]))\n    print('Rim z range:', np.min(rim_pts[:,2]), np.max(rim_pts[:,2]))\n\n# 2. Plate (plate_1): v in [165, 212], u in [165, 222]\nplate_patch = pts[165:212, 165:222]\nplate_rgb = rgb[165:212, 165:222]\n# Plate has red rim or white center, elevated slightly above table (z > 0.903)\nplate_mask = plate_patch[..., 2] > 0.904\nplate_pts = plate_patch[plate_mask]\nprint('Plate pts count:', len(plate_pts))\nprint('Plate center (min+max)/2:', (np.min(plate_pts, axis=0) + np.max(plate_pts, axis=0))/2)\nprint('Plate mean:', np.mean(plate_pts, axis=0))\nprint('Plate x range:', np.min(plate_pts[:,0]), np.max(plate_pts[:,0]))\nprint('Plate y range:', np.min(plate_pts[:,1]), np.max(plate_pts[:,1]))\nprint('Plate z range:', np.min(plate_pts[:,2]), np.max(plate_pts[:,2]))\n\n# Also check plate in wrist camera!\npts_w = np.load('/tmp/work/pts_wrist.npy')\nrgb_w = np.array(Image.open('/tmp/work/init_wrist.png'))\nplate_w_patch = pts_w[0:50, 0:70]\nplate_w_mask = plate_w_patch[..., 2] > 0.904\nplate_w_pts = plate_w_patch[plate_w_mask]\nprint('Wrist plate pts count:', len(plate_w_pts))\nif len(plate_w_pts) > 0:\n    print('Wrist plate center (min+max)/2:', (np.min(plate_w_pts, axis=0) + np.max(plate_w_pts, axis=0))/2)\n    print('Wrist plate z range:', np.min(plate_w_pts[:,2]), np.max(plate_w_pts[:,2]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nTarget bowl pts count: 1515\r\nTarget bowl x min/max/mean/median: 0.1818521288517883 0.2925754991799961 0.22505777273146496 0.22143862144843385\r\nTarget bowl y min/max/mean/median: -0.09216732636288058 0.01698909659403978 -0.03834117396267 -0.03842025400139076\r\nTarget bowl z min/max/mean: 0.9080194578858646 0.952660979295586 0.9277136200335815\r\nTarget bowl rim (z>0.95) count: 157\r\nRim center (min+max)/2: [ 0.23721381 -0.03758911  0.95133464]\r\nRim mean: [ 0.23984006 -0.03217431  0.95136355]\r\nRim x range: 0.1818521288517883 0.2925754991799961\r\nRim y range: -0.09216732636288058 0.01698909659403978\r\nRim z range: 0.9500083068890871 0.952660979295586\r\nPlate pts count: 1388\r\nPlate center (min+max)/2: [0.06885327 0.1886408  0.91472959]\r\nPlate mean: [0.06610129 0.19050384 0.91239273]\r\nPlate x range: 0.0016209288700694824 0.136085602289576\r\nPlate y range: 0.12091537429869727 0.2563662306822002\r\nPlate z range: 0.9083325772321552 0.9211266075036899\r\nWrist plate pts count: 2441\r\nWrist plate center (min+max)/2: [0.05011237 0.18738268 0.9124431 ]\r\nWrist plate z range: 0.9063395324313592 0.9185466609040008","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":7,"t":100.0,"say":"","calls":[{"kind":"shell","label":"Checking 3D coordinates of cookies box","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\nbox_patch = pts[170:205, 120:150]\nbox_pts = box_patch[box_patch[..., 2] > 0.905]\nprint('Cookies box x range:', np.min(box_pts[:,0]), np.max(box_pts[:,0]))\nprint('Cookies box y range:', np.min(box_pts[:,1]), np.max(box_pts[:,1]))\nprint('Cookies box z range:', np.min(box_pts[:,2]), np.max(box_pts[:,2]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nCookies box x range: 0.028153451838992205 0.10788367931593568\r\nCookies box y range: -0.005976086379259646 0.05322866126143089\r\nCookies box z range: 0.906967092744197 0.9215047165946436","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":8,"t":117.0,"say":"","calls":[{"kind":"shell","label":"Checking 3D coordinates of gripper fingers in wrist camera","code":"python3 -c \"\nimport numpy as np\npts_w = np.load('/tmp/work/pts_wrist.npy')\nd_w = np.load('/tmp/work/depth_wrist.npy')\n# Bottom of wrist image (v in [190, 230]) shows the two fingers!\nfor u_slice, name in [((30, 80), 'left_in_img'), ((175, 225), 'right_in_img')]:\n    patch = pts_w[195:220, u_slice[0]:u_slice[1]]\n    d_patch = d_w[195:220, u_slice[0]:u_slice[1]]\n    mask = d_patch < 0.20 # fingers are close to wrist camera\n    print(name, 'count:', np.sum(mask))\n    if np.sum(mask) > 0:\n        print(name, 'mean world xyz:', np.mean(patch[mask], axis=0))\n        print(name, 'min z:', np.min(patch[mask][:,2]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nleft_in_img count: 945\r\nleft_in_img mean world xyz: [-0.19451429  0.03022193  1.18774638]\r\nleft_in_img min z: 1.1650739146254256\r\nright_in_img count: 936\r\nright_in_img mean world xyz: [-0.1945908  -0.04585633  1.18766349]\r\nright_in_img min z: 1.1648706963998618","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":9,"t":130.0,"say":"","calls":[{"kind":"shell","label":"Checking fingertip visibility in wrist camera depth","code":"python3 -c \"\nimport numpy as np\npts_w = np.load('/tmp/work/pts_wrist.npy')\nd_w = np.load('/tmp/work/depth_wrist.npy')\nfor v in range(180, 256, 5):\n    row_d = d_w[v, :]\n    close = np.where(row_d < 0.25)[0]\n    if len(close) > 0:\n        print(f'v={v}: u range {close[0]}..{close[-1]}, min_z={np.min(pts_w[v, close, 2]):.4f}, mean_x={np.mean(pts_w[v, close, 0]):.4f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nv=195: u range 41..215, min_z=1.1670, mean_x=-0.1971\r\nv=200: u range 34..221, min_z=1.1656, mean_x=-0.1973\r\nv=205: u range 24..231, min_z=1.1691, mean_x=-0.1973\r\nv=210: u range 9..246, min_z=1.1659, mean_x=-0.1986\r\nv=215: u range 0..255, min_z=1.2084, mean_x=-0.1863\r\nv=220: u range 0..255, min_z=1.2128, mean_x=-0.1854\r\nv=225: u range 0..255, min_z=1.2157, mean_x=-0.1853\r\nv=230: u range 0..255, min_z=1.2182, mean_x=-0.1852\r\nv=235: u range 0..255, min_z=1.2206, mean_x=-0.1851\r\nv=240: u range 0..255, min_z=1.2227, mean_x=-0.1851\r\nv=245: u range 0..255, min_z=1.2246, mean_x=-0.1850\r\nv=250: u range 0..255, min_z=1.2264, mean_x=-0.1850\r\nv=255: u range 0..255, min_z=1.2281, mean_x=-0.1849","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":10,"t":144.0,"say":"","calls":[{"kind":"shell","label":"Checking gripper fingertip height in agentview depth","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\n# Gripper is around x in [-0.25, -0.15], y in [-0.08, 0.08], z > 1.10\nmask = (pts[..., 0] > -0.25) & (pts[..., 0] < -0.15) & (pts[..., 1] > -0.08) & (pts[..., 1] < 0.08) & (pts[..., 2] > 1.10)\ng_pts = pts[mask]\nprint('Gripper pts in agentview:', len(g_pts))\nprint('Gripper min z:', np.min(g_pts[:, 2]))\nlow_pts = g_pts[g_pts[:, 2] < 1.16]\nprint('Lowest gripper points (z < 1.16):', low_pts)\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nGripper pts in agentview: 2692\r\nGripper min z: 1.1683026989826042\r\nLowest gripper points (z < 1.16): []","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":11,"t":152.0,"say":"","calls":[{"kind":"shell","label":"Inspecting detailed 3D rim points of target bowl","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\nrgb = np.load('/tmp/work/depth_agentview.npy')\n\n# Target bowl detailed profile in x and y\nbowl_patch = pts[205:256, 80:145]\nmask = bowl_patch[..., 2] > 0.910\nbp = bowl_patch[mask]\n\n# Find top rim points (z > 0.948)\nrim = bp[bp[:, 2] > 0.948]\nprint('Rim points count:', len(rim))\nprint('Rim x min/max:', np.min(rim[:,0]), np.max(rim[:,0]), 'mid:', 0.5*(np.min(rim[:,0])+np.max(rim[:,0])))\nprint('Rim y min/max:', np.min(rim[:,1]), np.max(rim[:,1]), 'mid:', 0.5*(np.min(rim[:,1])+np.max(rim[:,1])))\nprint('Rim z min/max/median:', np.min(rim[:,2]), np.max(rim[:,2]), np.median(rim[:,2]))\n\n# Specifically look at the +Y rim of the bowl (around x in [0.22, 0.25], y > -0.01)\nplus_y_rim = rim[(rim[:,0] > 0.225) & (rim[:,0] < 0.250) & (rim[:,1] > -0.01)]\nprint('+Y rim points:', plus_y_rim)\n\n# And -Y rim of the bowl (around x in [0.22, 0.25], y < -0.06)\nminus_y_rim = rim[(rim[:,0] > 0.225) & (rim[:,0] < 0.250) & (rim[:,1] < -0.06)]\nprint('-Y rim points:', minus_y_rim)\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nRim points count: 226\r\nRim x min/max: 0.1818521288517883 0.2925754991799961 mid: 0.2372138140158922\r\nRim y min/max: -0.09216732636288058 0.01698909659403978 mid: -0.0375891148844204\r\nRim z min/max/median: 0.9480641680365315 0.952660979295586 0.9510008429179106\r\n+Y rim points: [[0.22550878 0.01458103 0.95135876]\r\n [0.22607198 0.0169891  0.9522157 ]\r\n [0.22787742 0.01455258 0.95075718]\r\n [0.22899985 0.01693379 0.95247599]\r\n [0.2302401  0.01452414 0.95016297]\r\n [0.23163818 0.01688955 0.95231763]\r\n [0.23287545 0.01448622 0.95000831]\r\n [0.23426857 0.01684531 0.95216911]\r\n [0.23494759 0.01446726 0.94899669]\r\n [0.23716864 0.01679    0.95246382]\r\n [0.23784568 0.01441986 0.94929386]\r\n [0.23978215 0.01674576 0.95233619]\r\n [0.2404582  0.01438193 0.94916747]\r\n [0.24238772 0.01670152 0.95221841]\r\n [0.24333742 0.01433453 0.94948799]\r\n [0.24526    0.01664622 0.95254753]\r\n [0.24648038 0.01427765 0.95025911]\r\n [0.24784869 0.01660197 0.95245064]\r\n [0.2498841  0.01421128 0.95148452]]\r\n-Y rim points: [[ 0.22787742 -0.09216733  0.95075719]\r\n [ 0.2273162  -0.0898588   0.94989779]\r\n [ 0.23079934 -0.09186711  0.95102485]\r\n [ 0.22968087 -0.08968341  0.94930113]\r\n [ 0.23371133 -0.09156689  0.95130481]\r\n [ 0.23203958 -0.08950802  0.94871184]\r\n [ 0.23605812 -0.09138676  0.95073027]\r\n [ 0.23439233 -0.08933263  0.94812993]\r\n [ 0.23895224 -0.09108654  0.95103235]\r\n [ 0.24156079 -0.09084636  0.95091088]\r\n [ 0.23990691 -0.08880645  0.94829578]\r\n [ 0.24443604 -0.09054614  0.95123631]\r\n [ 0.24251347 -0.0885726   0.94817677]\r\n [ 0.24702771 -0.09030597  0.95113574]\r\n [ 0.24511209 -0.08833874  0.94806759]\r\n [ 0.24988411 -0.09000575  0.95148453]\r\n [ 0.2482481  -0.08798796  0.94884731]]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":12,"t":192.0,"say":"","calls":[{"kind":"shell","label":"Checking EEF rotation matrix","code":"python3 -c \"\nimport numpy as np\nw, x, y, z = -0.0001754242111928761, 0.999615490436554, -0.0004330813535489142, -0.0277246180921793\nR = np.array([\n    [1 - 2*(y*y + z*z), 2*(x*y - w*z), 2*(x*z + w*y)],\n    [2*(x*y + w*z), 1 - 2*(x*x + z*z), 2*(y*z - w*x)],\n    [2*(x*z - w*y), 2*(y*z + w*x), 1 - 2*(x*x + y*y)]\n])\nprint('EEF Rotation matrix:\\n', np.round(R, 4))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nEEF Rotation matrix:\r\n [[ 9.985e-01 -9.000e-04 -5.540e-02]\r\n [-9.000e-04 -1.000e+00  4.000e-04]\r\n [-5.540e-02 -3.000e-04 -9.985e-01]]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":13,"t":202.0,"say":"","calls":[{"kind":"shell","label":"Checking finger x/y/z bounds in agentview depth","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\n# Fingers are at z in [1.168, 1.21]\nmask = (pts[..., 0] > -0.25) & (pts[..., 0] < -0.15) & (pts[..., 1] > -0.08) & (pts[..., 1] < 0.08) & (pts[..., 2] > 1.16) & (pts[..., 2] < 1.20)\nf_pts = pts[mask]\nprint('Fingers in agentview x min/max/mean:', np.min(f_pts[:,0]), np.max(f_pts[:,0]), np.mean(f_pts[:,0]))\nprint('Fingers in agentview y min/max/mean:', np.min(f_pts[:,1]), np.max(f_pts[:,1]), np.mean(f_pts[:,1]))\nprint('Fingers in agentview z min/max:', np.min(f_pts[:,2]), np.max(f_pts[:,2]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nFingers in agentview x min/max/mean: -0.21464517679084316 -0.19625895670236015 -0.2011982873491738\r\nFingers in agentview y min/max/mean: -0.06886875497998751 0.050875913654896174 -0.009110843615424358\r\nFingers in agentview z min/max: 1.1683026989826042 1.1979915576309486","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":14,"t":212.0,"say":"","calls":[{"kind":"shell","label":"Checking bowl cross-section z profile along Y axis","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\nbowl_patch = pts[205:256, 80:145]\nbp = bowl_patch[bowl_patch[..., 2] > 0.902]\n\n# Check z height of bowl near x in [0.225, 0.250] as a function of y!\nstrip = bp[(bp[:,0] > 0.225) & (bp[:,0] < 0.250)]\nfor y_min in np.arange(-0.095, 0.025, 0.01):\n    sub = strip[(strip[:,1] >= y_min) & (strip[:,1] < y_min + 0.01)]\n    if len(sub) > 0:\n        print(f'y in [{y_min:.3f}, {y_min+0.01:.3f}]: count={len(sub)}, z_min={np.min(sub[:,2]):.4f}, z_max={np.max(sub[:,2]):.4f}, z_mean={np.mean(sub[:,2]):.4f}')\n    else:\n        print(f'y in [{y_min:.3f}, {y_min+0.01:.3f}]: count=0')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\ny in [-0.095, -0.085]: count=32, z_min=0.9419, z_max=0.9515, z_mean=0.9476\r\ny in [-0.085, -0.075]: count=47, z_min=0.9202, z_max=0.9425, z_mean=0.9314\r\ny in [-0.075, -0.065]: count=39, z_min=0.9117, z_max=0.9215, z_mean=0.9152\r\ny in [-0.065, -0.055]: count=38, z_min=0.9087, z_max=0.9116, z_mean=0.9101\r\ny in [-0.055, -0.045]: count=36, z_min=0.9078, z_max=0.9092, z_mean=0.9084\r\ny in [-0.045, -0.035]: count=36, z_min=0.9077, z_max=0.9085, z_mean=0.9081\r\ny in [-0.035, -0.025]: count=36, z_min=0.9077, z_max=0.9088, z_mean=0.9082\r\ny in [-0.025, -0.015]: count=35, z_min=0.9083, z_max=0.9102, z_mean=0.9090\r\ny in [-0.015, -0.005]: count=35, z_min=0.9094, z_max=0.9146, z_mean=0.9114\r\ny in [-0.005, 0.005]: count=45, z_min=0.9134, z_max=0.9339, z_mean=0.9205\r\ny in [0.005, 0.015]: count=37, z_min=0.9349, z_max=0.9515, z_mean=0.9437\r\ny in [0.015, 0.025]: count=9, z_min=0.9522, z_max=0.9525, z_mean=0.9524","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":15,"t":233.0,"say":"","calls":[{"kind":"shell","label":"Checking vertical clearance between fingers and gripper palm","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\n# At initial pose, eef_x = -0.2062, eef_y = -0.0081, eef_z = 1.1740\n# Let's check the z height of points right near y = -0.0081 (between the two fingers, i.e. y in [-0.025, 0.010])\nmask = (pts[..., 0] > -0.23) & (pts[..., 0] < -0.18) & (pts[..., 1] > -0.025) & (pts[..., 1] < 0.010) & (pts[..., 2] > 1.15)\nmid_pts = pts[mask]\nif len(mid_pts) > 0:\n    print('Between fingers z min/max:', np.min(mid_pts[:,2]), np.max(mid_pts[:,2]))\n    print('Clearance above eef_z (1.1740):', np.min(mid_pts[:,2]) - 1.1740)\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nBetween fingers z min/max: 1.210387555301533 1.259524430268941\r\nClearance above eef_z (1.1740): 0.03638755530153315","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":16,"t":253.0,"say":"","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n#!/usr/bin/env python3\n\"\"\"Controller script for LIBERO-MAX libero_spatial sensor-noise onset (i01).\nTask: Pick the akita black bowl on the cookies box and place it on the plate.\n\"\"\"\nimport sys\nsys.path.insert(0, \"/opt/tools\")\nimport numpy as np\nimport rcb_client\n\n\ndef get_eef_pos(res_or_meta):\n    meta = res_or_meta.meta if hasattr(res_or_meta, \"meta\") else res_or_meta\n    now = meta[\"proprio\"][\"now\"]\n    return np.array(now[:3], dtype=np.float64)\n\n\ndef move_to_pose(r, target_xyz, grip=-1.0, max_steps=60, kp=6.0, max_act=0.6, cameras=(\"agentview\", \"wrist\")):\n    obs = r.get_obs(cameras=list(cameras), include_depth=True)\n    cur = get_eef_pos(obs)\n    diff = np.asarray(target_xyz, dtype=np.float64) - cur\n    dist = np.linalg.norm(diff)\n    steps = max(10, min(max_steps, int(np.ceil(dist / (0.05 * max_act) * 1.5)) + 5))\n    actions = []\n    for _ in range(steps):\n        step_delta = np.clip(diff / (steps * 0.05) * 1.2, -max_act, max_act)\n        actions.append([step_delta[0], step_delta[1], step_delta[2], 0.0, 0.0, 0.0, float(grip)])\n    res = r.submit(\"ee_delta\", np.array(actions, dtype=np.float64), dt=0.05,\n                   cameras=list(cameras), video=\"none\", include_depth=True)\n    return res\n\n\ndef main():\n    r = rcb_client.Robot()\n    status = r.status()\n    print(\"Status:\", status)\n\n\nif __name__ == \"__main__\":\n    main()\n"}],"out":{"text":"Created file file:///app/output/gen.py 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":17,"t":275.0,"say":"","calls":[{"kind":"robot","label":"Moving gripper horizontally toward target bowl","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=False, video='none')\ncur = np.array(obs.meta['proprio']['now'][:3])\nprint('Start EEF:', cur)\n\ntarget = np.array([0.2372, 0.0100, 1.1500])\n# Move in 25 steps\ndiff = target - cur\n# In OSC_POSE, each step moves ~0.03-0.04m for action=1.0 due to controller stiffness/damping\n# Let's send 25 steps of moderate action\nact_xyz = np.clip(diff / (20 * 0.05), -0.6, 0.6)\nactions = np.zeros((25, 7))\nactions[:20, :3] = act_xyz\nactions[:, 6] = -1.0 # open gripper\n\nres = r.submit('ee_delta', actions, dt=0.05, cameras=['agentview', 'wrist'], video='none', include_depth=True)\nnow = np.array(res.meta['proprio']['now'][:3])\nprint('After chunk 1 EEF:', now, 'quat:', res.meta['proprio']['now'][3:7])\nprint('Steps:', res.meta['control_steps'], 'Done:', res.meta['done'])\nImage.fromarray(res.last['agentview']).save('/tmp/work/step1_agentview.png')\nImage.fromarray(res.last['wrist']).save('/tmp/work/step1_wrist.png')\nnp.save('/tmp/work/step1_depth_agentview.npy', res.depth['agentview'][-1].astype(np.float64))\nnp.save('/tmp/work/step1_depth_wrist.npy', res.depth['wrist'][-1].astype(np.float64))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nStart EEF: [-0.20616071 -0.00814219  1.17397451]\r\nAfter chunk 1 EEF: [-0.09374393 -0.00449986  1.16251826] quat: [4.299645661376417e-05, 0.9993477463722229, 0.0006284607225097716, -0.03610644489526749]\r\nSteps: 25 Done: False","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":18,"t":306.0,"say":"","calls":[{"kind":"look","label":"step1_agentview.png","code":"/tmp/work/step1_agentview.png"},{"kind":"look","label":"step1_wrist.png","code":"/tmp/work/step1_wrist.png"}],"out":{"text":"The 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":1,"reset":0}},{"id":19,"t":315.0,"say":"","calls":[{"kind":"robot","label":"Moving gripper to pre-grasp pose above target bowl","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\ntarget = np.array([0.2372, 0.0100, 1.0600])\n\nfor i in range(4):\n    obs = r.get_obs(include_depth=False, video='none')\n    cur = np.array(obs.meta['proprio']['now'][:3])\n    err = target - cur\n    dist = np.linalg.norm(err)\n    print(f'Iter {i}: cur={np.round(cur, 4)}, err={np.round(err, 4)}, dist={dist:.4f}')\n    if dist < 0.005:\n        break\n    # Each unit of action moves ~0.013m per step.\n    n_steps = max(8, min(25, int(np.ceil(dist / (0.013 * 0.6))) + 3))\n    act = np.clip(err / (n_steps * 0.013), -0.7, 0.7)\n    actions = np.zeros((n_steps, 7))\n    actions[:-2, :3] = act\n    actions[:, 6] = -1.0\n    res = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\n\nobs = r.get_obs(include_depth=True, video='none')\nprint('Final EEF:', np.round(obs.meta['proprio']['now'][:3], 4), 'quat:', np.round(obs.meta['proprio']['now'][3:7], 4))\nprint('Total steps:', obs.meta['control_steps'])\nImage.fromarray(obs.last['agentview']).save('/tmp/work/step2_agentview.png')\nImage.fromarray(obs.last['wrist']).save('/tmp/work/step2_wrist.png')\nnp.save('/tmp/work/step2_depth_agentview.npy', obs.depth['agentview'][0].astype(np.float64))\nnp.save('/tmp/work/step2_depth_wrist.npy', obs.depth['wrist'][0].astype(np.float64))\n\""}],"out":{"text":"Tool is running as a background task with task id: ad089a8e-3977-4ce2-b77e-1cd9c499610a/task-39\nTask Description: python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\ntarget = np.array([0.2372, 0.0100, 1.0600])\n\nfor i in range(4):\n    obs = r.get_obs(include_depth=False, video='none')\n    cur = np.array(obs.meta['proprio']['now'][:3])\n    err = target - cur\n    dist = np.linalg.norm(err)\n    print(f'Iter {i}: cur={np.round(cur, 4)}, err={np.round(err, 4)}, dist={dist:.4f}')\n    if dist < 0.005:\n        break\n    # Each unit of action moves ~0.013m per step.\n    n_steps = max(8, min(25, int(np.ceil(dist / (0.013 * 0.6))) + 3))\n    act = np.clip(err / (n_steps * 0.013), -0.7, 0.7)\n    actions = np.zeros((n_steps, 7))\n    actions[:-2, :3] = act\n    actions[:, 6] = -1.0\n    res = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\n\nobs = r.get_obs(include_depth=True, video='none')\nprint('Final EEF:', np.round(obs.meta['proprio']['now'][:3], 4), 'quat:', np.round(obs.meta['proprio']['now'][3:7], 4))\nprint('Total steps:', obs.meta['control_steps'])\nImage.fromarray(obs.last['agentview']).save('/tmp/work/step2_agentview.png')\nImage.fromarray(obs.last['wrist']).save('/tmp/work/step2_wrist.png')\nnp.save('/tmp/work/step2_depth_agentview.npy', obs.depth['agentview'][0].astype(np.float64))\nnp.save('/tmp/work/step2_depth_wrist.npy', obs.depth['wrist'][0].astype(np.float64))\n\"\nTask logs are available at: file:///root/.gemini/antigravity-cli/brain/ad089a8e-3977-4ce2-b77e-1cd9c499610a/.system_generated/tasks/task-39.log\nYOU MUST TAKE ONE OF THE FOLLOWING TWO ACTIONS: A) either proceed to other relevant work (if any) or, B) simply update the user with a short message (that you have launched the command and will wait for it to finish) and end the turn.\n DO NOTHING ELSE.\n When updating the user, always respond in the language of the user (defaulting to English). Never mix two or more languages in the same response.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":20,"t":341.0,"say":"Moving the gripper to the pre-grasp position above the `+Y` rim of `akita_black_bowl_1` (`[0.2372, 0.0100, 1.0600]`) and waiting for the movement chunk to complete.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":3,"reset":0}},{"id":22,"t":366.0,"say":"","calls":[{"kind":"look","label":"step2_agentview.png","code":"/tmp/work/step2_agentview.png"},{"kind":"look","label":"step2_wrist.png","code":"/tmp/work/step2_wrist.png"}],"out":{"text":"The 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":23,"t":373.0,"say":"","calls":[{"kind":"robot","label":"Checking current joint positions and proprioception","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(cameras=[], video='none', include_depth=False)\nlayout = obs.meta['proprio']['layout']\nnow = obs.meta['proprio']['now']\nfor k, v in zip(layout, now):\n    print(f'{k:15s}: {v:.5f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\neef_x          : 0.13913\r\neef_y          : 0.00880\r\neef_z          : 0.97652\r\neef_qw         : -0.00034\r\neef_qx         : 1.00000\r\neef_qy         : 0.00044\r\neef_qz         : -0.00038\r\nfinger_left    : 0.03999\r\nfinger_right   : -0.03999\r\njoint1_pos     : 0.00944\r\njoint2_pos     : 1.27941\r\njoint3_pos     : 0.00345\r\njoint4_pos     : -0.69961\r\njoint5_pos     : -0.00285\r\njoint6_pos     : 1.97500\r\njoint7_pos     : 0.79659\r\njoint1_vel     : 0.00001\r\njoint2_vel     : 0.20416\r\njoint3_vel     : 0.00002\r\njoint4_vel     : 0.37030\r\njoint5_vel     : 0.00001\r\njoint6_vel     : -0.36362\r\njoint7_vel     : 0.00004\r\ncmd_dx         : 0.00000\r\ncmd_dy         : 0.00000\r\ncmd_dz         : 0.00000\r\ncmd_drx        : 0.00000\r\ncmd_dry        : 0.00000\r\ncmd_drz        : 0.00000\r\ncmd_grip       : -1.00000","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":24,"t":386.0,"say":"","calls":[{"kind":"robot","label":"Testing larger dx and dz action to extend arm","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nactions = np.zeros((15, 7))\nactions[:, 0] = 0.8   # +x\nactions[:, 2] = 0.8   # +z\nactions[:, 6] = -1.0  # open\nres = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\nnow = res.meta['proprio']['now']\nprint('EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4))\nprint('joints 1..7:', np.round(now[9:16], 4))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nEEF: [0.1679 0.0082 1.0075] quat: [-9.000e-04  9.979e-01 -2.000e-04  6.520e-02]\r\njoints 1..7: [ 0.0093  1.4918  0.0034 -0.2657 -0.0029  1.8892  0.7963]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":25,"t":411.0,"say":"","calls":[{"kind":"robot","label":"Checking bowl cross-section z profile along X axis","code":"python3 -c \"\nimport numpy as np\npts = np.load('/tmp/work/pts_agentview.npy')\nbowl_patch = pts[205:256, 80:145]\nbp = bowl_patch[bowl_patch[..., 2] > 0.902]\n\n# Check z height of bowl near y in [-0.050, -0.025] as a function of x!\nstrip = bp[(bp[:,1] > -0.050) & (bp[:,1] < -0.025)]\nfor x_min in np.arange(0.175, 0.295, 0.01):\n    sub = strip[(strip[:,0] >= x_min) & (strip[:,0] < x_min + 0.01)]\n    if len(sub) > 0:\n        print(f'x in [{x_min:.3f}, {x_min+0.01:.3f}]: count={len(sub)}, z_min={np.min(sub[:,2]):.4f}, z_max={np.max(sub[:,2]):.4f}, z_mean={np.mean(sub[:,2]):.4f}')\n    else:\n        print(f'x in [{x_min:.3f}, {x_min+0.01:.3f}]: count=0')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nx in [0.175, 0.185]: count=19, z_min=0.9495, z_max=0.9514, z_mean=0.9503\r\nx in [0.185, 0.195]: count=84, z_min=0.9266, z_max=0.9479, z_mean=0.9387\r\nx in [0.195, 0.205]: count=66, z_min=0.9138, z_max=0.9287, z_mean=0.9198\r\nx in [0.205, 0.215]: count=40, z_min=0.9097, z_max=0.9135, z_mean=0.9115\r\nx in [0.215, 0.225]: count=40, z_min=0.9084, z_max=0.9099, z_mean=0.9090\r\nx in [0.225, 0.235]: count=40, z_min=0.9077, z_max=0.9087, z_mean=0.9081\r\nx in [0.235, 0.245]: count=33, z_min=0.9078, z_max=0.9086, z_mean=0.9081\r\nx in [0.245, 0.255]: count=37, z_min=0.9083, z_max=0.9095, z_mean=0.9087\r\nx in [0.255, 0.265]: count=30, z_min=0.9089, z_max=0.9115, z_mean=0.9101\r\nx in [0.265, 0.275]: count=10, z_min=0.9115, z_max=0.9133, z_mean=0.9122\r\nx in [0.275, 0.285]: count=6, z_min=0.9280, z_max=0.9331, z_mean=0.9310\r\nx in [0.285, 0.295]: count=25, z_min=0.9336, z_max=0.9518, z_mean=0.9469","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":26,"t":433.0,"say":"","calls":[{"kind":"robot","label":"Rotating gripper yaw by 90 degrees and advancing to bowl -X rim","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\n# Rotate yaw by 90 deg (drz = +0.6 for 15 steps) and move toward (0.188, -0.0376, 1.02)\nactions = np.zeros((15, 7))\nactions[:, 0] = 0.5    # +x\nactions[:, 1] = -0.35  # -y toward -0.0376\nactions[:, 2] = 0.1    # keep z around 1.00-1.02\nactions[:, 4] = 0.15   # slight +dry tilt forward to increase +x reach\nactions[:, 5] = 0.6    # +drz to rotate yaw toward 90 deg\nactions[:, 6] = -1.0   # open\nres = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\nnow = res.meta['proprio']['now']\nprint('EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4))\nprint('joints 1..7:', np.round(now[9:16], 4))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nEEF: [ 0.175  -0.029   0.9291] quat: [-0.0315  0.9152  0.3771  0.1386]\r\njoints 1..7: [-0.0886  1.4515  0.0681 -0.5805  0.1536  2.2473 -0.1848]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":27,"t":476.0,"say":"","calls":[{"kind":"robot","label":"Checking current observation, depth, and EEF rotation matrix","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nnow = obs.meta['proprio']['now']\nprint('EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4))\nw, x, y, z = now[3:7]\nR = np.array([\n    [1 - 2*(y*y + z*z), 2*(x*y - w*z), 2*(x*z + w*y)],\n    [2*(x*y + w*z), 1 - 2*(x*x + z*z), 2*(y*z - w*x)],\n    [2*(x*z - w*y), 2*(y*z + w*x), 1 - 2*(x*x + y*y)]\n])\nprint('EEF R:\\n', np.round(R, 3))\nImage.fromarray(obs.last['agentview']).save('/tmp/work/step3_agentview.png')\nImage.fromarray(obs.last['wrist']).save('/tmp/work/step3_wrist.png')\n\n# Check bowl 3D points from agentview depth to see if bowl moved at all!\nspec = r.spec()\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(obs.meta.get('cameras_now', spec['cameras'])['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\nbowl_patch = pts_w[215:255, 85:140]\nbp = bowl_patch[(bowl_patch[..., 2] > 0.908) & (bowl_patch[..., 2] < 0.955)]\nprint('Bowl x min/max:', np.min(bp[:,0]), np.max(bp[:,0]))\nprint('Bowl y min/max:', np.min(bp[:,1]), np.max(bp[:,1]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nEEF: [ 0.175  -0.029   0.9291] quat: [-0.0315  0.9152  0.3771  0.1386]\r\nEEF R:\r\n [[ 0.677  0.699  0.23 ]\r\n [ 0.682 -0.714  0.162]\r\n [ 0.277  0.047 -0.96 ]]\r\nBowl x min/max: 0.1837058775023912 0.2846909621652738\r\nBowl y min/max: -0.09682861952160556 0.007356810515300774","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":28,"t":489.0,"say":"","calls":[{"kind":"look","label":"step3_agentview.png","code":"/tmp/work/step3_agentview.png"},{"kind":"look","label":"step3_wrist.png","code":"/tmp/work/step3_wrist.png"}],"out":{"text":"The 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":29,"t":494.0,"say":"","calls":[{"kind":"robot","label":"Checking bowl rim 3D coordinates in wrist depth map","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\nd = obs.depth['wrist'][0].astype(np.float64)\nK = np.array(spec['cameras']['wrist']['intrinsic_cv'])\nc2w = np.array(obs.meta['cameras_now']['wrist']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\nprint('Wrist depth min/max:', np.min(d), np.max(d))\n# Look at points between the fingers in the wrist view: v in [150, 210], u in [100, 180]\npatch = pts_w[150:210, 100:180]\nd_patch = d[150:210, 100:180]\nprint('Between fingers depth min/max:', np.min(d_patch), np.max(d_patch))\nrim_mask = (patch[..., 2] > 0.940) & (patch[..., 2] < 0.960)\nprint('Rim points between fingers count:', np.sum(rim_mask))\nif np.sum(rim_mask) > 0:\n    print('Rim points mean xyz:', np.mean(patch[rim_mask], axis=0))\n    print('Rim points min/max xyz:', np.min(patch[rim_mask], axis=0), np.max(patch[rim_mask], axis=0))\n\""}],"out":{"text":"The command exited with code 1.\nOutput:\nTraceback (most recent call last):\r\n  File \"<string>\", line 11, in <module>\r\nKeyError: 'cameras_now'","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":30,"t":520.0,"say":"","calls":[{"kind":"robot","label":"Inspecting wrist depth around rim and fingers","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nd_w = obs.depth['wrist'][0].astype(np.float64)\nd_a = obs.depth['agentview'][0].astype(np.float64)\nprint('wrist depth stats: min=', np.min(d_w), 'max=', np.max(d_w), 'zeros=', np.sum(d_w==0))\nprint('agentview depth stats: min=', np.min(d_a), 'max=', np.max(d_a), 'zeros=', np.sum(d_a==0))\n# Check where zeros are in wrist depth (is the black box in depth too?)\nzero_v, zero_u = np.where(d_w == 0)\nif len(zero_v) > 0:\n    print('wrist zero depth v range:', np.min(zero_v), np.max(zero_v), 'u range:', np.min(zero_u), np.max(zero_u))\n# Check depth around the rim and fingers in wrist image: v in [160, 215], u in [115, 220]\nfor v in range(160, 215, 10):\n    print(f'v={v}: d_w[v, 115:215:10] =', np.round(d_w[v, 115:215:10], 3))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nwrist depth stats: min= 0.041778564453125 max= 0.1898193359375 zeros= 0\r\nagentview depth stats: min= 0.66064453125 max= 3.068359375 zeros= 0\r\nv=160: d_w[v, 115:215:10] = [0.132 0.084 0.095 0.115 0.121 0.124 0.126 0.126 0.127 0.127]\r\nv=170: d_w[v, 115:215:10] = [0.13  0.082 0.091 0.111 0.119 0.122 0.124 0.125 0.125 0.125]\r\nv=180: d_w[v, 115:215:10] = [0.128 0.08  0.088 0.104 0.115 0.119 0.121 0.123 0.123 0.123]\r\nv=190: d_w[v, 115:215:10] = [0.126 0.079 0.084 0.094 0.109 0.115 0.118 0.119 0.12  0.12 ]\r\nv=200: d_w[v, 115:215:10] = [0.124 0.124 0.081 0.087 0.096 0.108 0.113 0.115 0.099 0.094]\r\nv=210: d_w[v, 115:215:10] = [0.122 0.122 0.078 0.083 0.089 0.097 0.104 0.108 0.102 0.089]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":31,"t":531.0,"say":"","calls":[{"kind":"robot","label":"Checking full width of wrist depth across fingers and rim","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nd_w = obs.depth['wrist'][0].astype(np.float64)\nfor v in [195, 200, 205, 210]:\n    print(f'v={v}: d_w[v, 0:256:16] =', np.round(d_w[v, 0:256:16], 3))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nv=195: d_w[v, 0:256:16] = [0.121 0.121 0.122 0.101 0.123 0.123 0.124 0.124 0.079 0.089 0.109 0.116\r\n 0.104 0.101 0.116 0.112]\r\nv=200: d_w[v, 0:256:16] = [0.12  0.12  0.094 0.094 0.105 0.122 0.123 0.123 0.078 0.087 0.103 0.113\r\n 0.104 0.094 0.114 0.11 ]\r\nv=205: d_w[v, 0:256:16] = [0.119 0.119 0.088 0.089 0.121 0.121 0.122 0.123 0.123 0.084 0.098 0.11\r\n 0.113 0.089 0.088 0.106]\r\nv=210: d_w[v, 0:256:16] = [0.118 0.081 0.086 0.089 0.105 0.121 0.121 0.122 0.122 0.082 0.093 0.105\r\n 0.104 0.089 0.086 0.081]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":32,"t":544.0,"say":"","calls":[{"kind":"robot","label":"Measuring exact rim position and depth between fingertips","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nd_w = obs.depth['wrist'][0].astype(np.float64)\n# Find exact u of rim (minimum depth between u=80 and u=180) for v in 190..215\nfor v in range(190, 216, 3):\n    sub = d_w[v, 80:180]\n    u_min = 80 + np.argmin(sub)\n    print(f'v={v}: rim u={u_min}, rim_d={d_w[v, u_min]:.4f}, left_finger_d(u=42)={d_w[v,42]:.4f}, right_finger_d(u=214)={d_w[v,214]:.4f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nv=190: rim u=124, rim_d=0.0786, left_finger_d(u=42)=0.1230, right_finger_d(u=214)=0.1196\r\nv=193: rim u=125, rim_d=0.0784, left_finger_d(u=42)=0.1225, right_finger_d(u=214)=0.1185\r\nv=196: rim u=126, rim_d=0.0783, left_finger_d(u=42)=0.0995, right_finger_d(u=214)=0.0995\r\nv=199: rim u=128, rim_d=0.0781, left_finger_d(u=42)=0.0954, right_finger_d(u=214)=0.0956\r\nv=202: rim u=129, rim_d=0.0779, left_finger_d(u=42)=0.0916, right_finger_d(u=214)=0.0916\r\nv=205: rim u=130, rim_d=0.0778, left_finger_d(u=42)=0.0886, right_finger_d(u=214)=0.0886\r\nv=208: rim u=132, rim_d=0.0776, left_finger_d(u=42)=0.0886, right_finger_d(u=214)=0.0886\r\nv=211: rim u=134, rim_d=0.0775, left_finger_d(u=42)=0.0886, right_finger_d(u=214)=0.0886\r\nv=214: rim u=80, rim_d=0.0627, left_finger_d(u=42)=0.0627, right_finger_d(u=214)=0.0627","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":33,"t":562.0,"say":"","calls":[{"kind":"robot","label":"Closing gripper on target bowl rim","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nactions = np.zeros((20, 7))\n# Tiny nudge to center u=130->128 and go 3mm deeper, while closing gripper\nactions[:5, 0] = 0.08\nactions[:5, 1] = -0.08\nactions[:5, 2] = -0.08\nactions[:5, 6] = -1.0\nactions[5:, 6] = 1.0   # close gripper firmly for 15 steps\n\nres = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\nnow = res.meta['proprio']['now']\nprint('After grasp EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4))\nprint('Fingers left/right:', now[7], now[8], 'sum width:', now[7] - now[8])\nImage.fromarray(res.last['agentview']).save('/tmp/work/step4_grasp_agentview.png')\nImage.fromarray(res.last['wrist']).save('/tmp/work/step4_grasp_wrist.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nAfter grasp EEF: [ 0.1528 -0.0222  0.9167] quat: [-0.0561  0.8631  0.4912  0.1033]\r\nFingers left/right: 0.016108840703964233 -0.006547469645738602 sum width: 0.022656310349702835","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":34,"t":596.0,"say":"","calls":[{"kind":"look","label":"step4_grasp_agentview.png","code":"/tmp/work/step4_grasp_agentview.png"},{"kind":"look","label":"step4_grasp_wrist.png","code":"/tmp/work/step4_grasp_wrist.png"}],"out":{"text":"The 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":1,"reset":0}},{"id":35,"t":603.0,"say":"","calls":[{"kind":"robot","label":"Lifting grasped target bowl","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\nactions = np.zeros((20, 7))\nactions[:, 0] = -0.2   # pull slightly back toward workspace center\nactions[:, 1] = 0.2    # move slightly +y toward plate\nactions[:, 2] = 0.8    # lift straight up\nactions[:, 6] = 1.0    # keep gripper closed firmly\n\nres = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\nnow = res.meta['proprio']['now']\nprint('After lift EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4))\nprint('Fingers left/right:', now[7], now[8], 'sum width:', now[7] - now[8])\nImage.fromarray(res.last['agentview']).save('/tmp/work/step5_lift_agentview.png')\nImage.fromarray(res.last['wrist']).save('/tmp/work/step5_lift_wrist.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nAfter lift EEF: [0.1497 0.0116 1.1649] quat: [-0.0742  0.8625  0.4945  0.0772]\r\nFingers left/right: 0.0032728237565606833 -0.0045271399430930614 sum width: 0.007799963699653745","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":36,"t":626.0,"say":"","calls":[{"kind":"look","label":"step5_lift_agentview.png","code":"/tmp/work/step5_lift_agentview.png"},{"kind":"look","label":"step5_lift_wrist.png","code":"/tmp/work/step5_lift_wrist.png"}],"out":{"text":"The 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":1,"reset":0}},{"id":37,"t":637.0,"say":"","calls":[{"kind":"robot","label":"Computing held bowl 3D offset relative to EEF","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\neef = np.array(obs.meta['proprio']['now'][:3])\nw, x, y, z = obs.meta['proprio']['now'][3:7]\nR = np.array([\n    [1 - 2*(y*y + z*z), 2*(x*y - w*z), 2*(x*z + w*y)],\n    [2*(x*y + w*z), 1 - 2*(x*x + z*z), 2*(y*z - w*x)],\n    [2*(x*z - w*y), 2*(y*z + w*x), 1 - 2*(x*x + y*y)]\n])\nprint('Current EEF:', eef)\nprint('Finger axis R[:,1] (world):', R[:,1])\n# The bowl center is roughly +0.052m along R[:,1] from EEF!\nbowl_est = eef + 0.052 * R[:,1]\nprint('Estimated bowl center from EEF + 0.052*R[:,1]:', bowl_est)\n\n# Also check from agentview depth!\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(spec['cameras']['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\n# Bowl in agentview is near EEF (x in [0.10, 0.25], y in [-0.08, 0.05], z in [1.08, 1.18])\nmask = (pts_w[...,0] > 0.12) & (pts_w[...,0] < 0.25) & (pts_w[...,1] > -0.08) & (pts_w[...,1] < 0.05) & (pts_w[...,2] > 1.08) & (pts_w[...,2] < 1.17)\nb_pts = pts_w[mask]\nprint('Held bowl pts in agentview:', len(b_pts))\nif len(b_pts) > 0:\n    print('Held bowl x min/max/mid:', np.min(b_pts[:,0]), np.max(b_pts[:,0]), 0.5*(np.min(b_pts[:,0])+np.max(b_pts[:,0])))\n    print('Held bowl y min/max/mid:', np.min(b_pts[:,1]), np.max(b_pts[:,1]), 0.5*(np.min(b_pts[:,1])+np.max(b_pts[:,1])))\n    print('Held bowl z min/max:', np.min(b_pts[:,2]), np.max(b_pts[:,2]))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nCurrent EEF: [0.14974014 0.01164585 1.16494906]\r\nFinger axis R[:,1] (world): [ 0.86455857 -0.49987679 -0.0515918 ]\r\nEstimated bowl center from EEF + 0.052*R[:,1]: [ 0.19469719 -0.01434775  1.16226629]\r\nHeld bowl pts in agentview: 534\r\nHeld bowl x min/max/mid: 0.14952967142296858 0.23679863261117534 0.19316415201707196\r\nHeld bowl y min/max/mid: -0.06280905113347714 0.026950072136855862 -0.017929489498310636\r\nHeld bowl z min/max: 1.139589540276139 1.1699827862161933","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":38,"t":662.0,"say":"","calls":[{"kind":"robot","label":"Verifying plate center in current agentview depth","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(spec['cameras']['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\nplate_patch = pts_w[165:212, 165:222]\nplate_pts = plate_patch[plate_patch[..., 2] > 0.904]\nprint('Plate center (min+max)/2:', (np.min(plate_pts, axis=0) + np.max(plate_pts, axis=0))/2)\nprint('Plate mean:', np.mean(plate_pts, axis=0))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nPlate center (min+max)/2: [0.06885327 0.1886408  0.91472959]\r\nPlate mean: [0.06610129 0.19050384 0.91239273]","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":39,"t":683.0,"say":"","calls":[{"kind":"robot","label":"Moving held bowl above the plate","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\ntarget = np.array([0.0253, 0.2181, 1.0800])\n\nfor i in range(3):\n    obs = r.get_obs(cameras=[], video='none', include_depth=False)\n    cur = np.array(obs.meta['proprio']['now'][:3])\n    err = target - cur\n    dist = np.linalg.norm(err)\n    print(f'Iter {i}: cur={np.round(cur, 4)}, err={np.round(err, 4)}, dist={dist:.4f}, grip_w={obs.meta[\\\"proprio\\\"][\\\"now\\\"][7]-obs.meta[\\\"proprio\\\"][\\\"now\\\"][8]:.4f}')\n    if dist < 0.008:\n        break\n    n_steps = max(8, min(20, int(np.ceil(dist / (0.015 * 0.6))) + 2))\n    act = np.clip(err / (n_steps * 0.015), -0.6, 0.6)\n    actions = np.zeros((n_steps, 7))\n    actions[:, :3] = act\n    actions[:, 6] = 1.0\n    res = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\n    if res.done:\n        print('DONE!', res.meta['reason'])\n        break\n\nobs = r.get_obs(include_depth=True, video='none')\nnow = obs.meta['proprio']['now']\nprint('Final EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4), 'grip_w:', now[7]-now[8])\nImage.fromarray(obs.last['agentview']).save('/tmp/work/step6_above_plate_agentview.png')\nImage.fromarray(obs.last['wrist']).save('/tmp/work/step6_above_plate_wrist.png')\n\""}],"out":{"text":"Tool is running as a background task with task id: ad089a8e-3977-4ce2-b77e-1cd9c499610a/task-81\nTask Description: python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\ntarget = np.array([0.0253, 0.2181, 1.0800])\n\nfor i in range(3):\n    obs = r.get_obs(cameras=[], video='none', include_depth=False)\n    cur = np.array(obs.meta['proprio']['now'][:3])\n    err = target - cur\n    dist = np.linalg.norm(err)\n    print(f'Iter {i}: cur={np.round(cur, 4)}, err={np.round(err, 4)}, dist={dist:.4f}, grip_w={obs.meta[\\\"proprio\\\"][\\\"now\\\"][7]-obs.meta[\\\"proprio\\\"][\\\"now\\\"][8]:.4f}')\n    if dist < 0.008:\n        break\n    n_steps = max(8, min(20, int(np.ceil(dist / (0.015 * 0.6))) + 2))\n    act = np.clip(err / (n_steps * 0.015), -0.6, 0.6)\n    actions = np.zeros((n_steps, 7))\n    actions[:, :3] = act\n    actions[:, 6] = 1.0\n    res = r.submit('ee_delta', actions, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\n    if res.done:\n        print('DONE!', res.meta['reason'])\n        break\n\nobs = r.get_obs(include_depth=True, video='none')\nnow = obs.meta['proprio']['now']\nprint('Final EEF:', np.round(now[:3], 4), 'quat:', np.round(now[3:7], 4), 'grip_w:', now[7]-now[8])\nImage.fromarray(obs.last['agentview']).save('/tmp/work/step6_above_plate_agentview.png')\nImage.fromarray(obs.last['wrist']).save('/tmp/work/step6_above_plate_wrist.png')\n\"\nTask logs are available at: file:///root/.gemini/antigravity-cli/brain/ad089a8e-3977-4ce2-b77e-1cd9c499610a/.system_generated/tasks/task-81.log\nYOU MUST TAKE ONE OF THE FOLLOWING TWO ACTIONS: A) either proceed to other relevant work (if any) or, B) simply update the user with a short message (that you have launched the command and will wait for it to finish) and end the turn.\n DO NOTHING ELSE.\n When updating the user, always respond in the language of the user (defaulting to English). Never mix two or more languages in the same response.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":40,"t":710.0,"say":"Moving the grasped bowl above `plate_1` (`[0.0253, 0.2181, 1.0800]`) and waiting for the movement chunk to complete.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":2,"reset":0}},{"id":42,"t":720.0,"say":"","calls":[{"kind":"look","label":"step6_above_plate_agentview.png","code":"/tmp/work/step6_above_plate_agentview.png"},{"kind":"look","label":"step6_above_plate_wrist.png","code":"/tmp/work/step6_above_plate_wrist.png"}],"out":{"text":"The 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":43,"t":727.0,"say":"","calls":[{"kind":"robot","label":"Checking held bowl 3D alignment with plate center","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\neef = np.array(obs.meta['proprio']['now'][:3])\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(spec['cameras']['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\n# Held bowl is around z in [0.98, 1.07], y in [0.10, 0.28], x in [-0.02, 0.15]\nmask = (pts_w[...,0] > -0.02) & (pts_w[...,0] < 0.15) & (pts_w[...,1] > 0.10) & (pts_w[...,1] < 0.28) & (pts_w[...,2] > 0.98) & (pts_w[...,2] < 1.065)\nb_pts = pts_w[mask]\nprint('Held bowl pts:', len(b_pts))\nif len(b_pts) > 0:\n    bx = 0.5*(np.min(b_pts[:,0])+np.max(b_pts[:,0]))\n    by = 0.5*(np.min(b_pts[:,1])+np.max(b_pts[:,1]))\n    print('Held bowl x min/max/mid:', np.min(b_pts[:,0]), np.max(b_pts[:,0]), bx)\n    print('Held bowl y min/max/mid:', np.min(b_pts[:,1]), np.max(b_pts[:,1]), by)\n    print('Held bowl z min/max:', np.min(b_pts[:,2]), np.max(b_pts[:,2]))\n    print('Offset to plate center (0.0688, 0.1886):', 0.0688 - bx, 0.1886 - by)\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nHeld bowl pts: 422\r\nHeld bowl x min/max/mid: 0.01306632882822123 0.09826877112850685 0.05566754997836404\r\nHeld bowl y min/max/mid: 0.13943573909868026 0.2306722552753806 0.18505399718703042\r\nHeld bowl z min/max: 1.0366660815620032 1.064944199099519\r\nOffset to plate center (0.0688, 0.1886): 0.01313245002163596 0.003546002812969573","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":44,"t":786.0,"say":"","calls":[{"kind":"robot","label":"Lowering bowl onto plate and releasing gripper","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\n\n# Step 1: shift +0.013m in X, +0.0035m in Y, and lower EEF z from 1.0709 to 0.970\nactions1 = np.zeros((15, 7))\nactions1[:, 0] = 0.08    # +x by ~1.3cm\nactions1[:, 1] = 0.02    # +y by ~0.3cm\nactions1[:, 2] = -0.45   # lower gently toward plate\nactions1[:, 6] = 1.0     # keep closed\n\nres1 = r.submit('ee_delta', actions1, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\nprint('After lower:', np.round(res1.meta['proprio']['now'][:3], 4), 'done:', res1.done, 'reason:', res1.meta.get('reason'))\n\nif not res1.done:\n    # Step 2: open gripper and lift slightly so gripper clears the bowl on the plate\n    actions2 = np.zeros((25, 7))\n    actions2[:10, 6] = -1.0   # open gripper\n    actions2[10:, 2] = 0.4    # lift gripper away from bowl\n    actions2[10:, 6] = -1.0\n    res2 = r.submit('ee_delta', actions2, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=False)\n    print('After release:', np.round(res2.meta['proprio']['now'][:3], 4), 'done:', res2.done, 'reason:', res2.meta.get('reason'))\n    Image.fromarray(res2.last['agentview']).save('/tmp/work/step7_release_agentview.png')\n    Image.fromarray(res2.last['wrist']).save('/tmp/work/step7_release_wrist.png')\n\""}],"out":{"text":"Tool is running as a background task with task id: ad089a8e-3977-4ce2-b77e-1cd9c499610a/task-90\nTask Description: python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\n\n# Step 1: shift +0.013m in X, +0.0035m in Y, and lower EEF z from 1.0709 to 0.970\nactions1 = np.zeros((15, 7))\nactions1[:, 0] = 0.08    # +x by ~1.3cm\nactions1[:, 1] = 0.02    # +y by ~0.3cm\nactions1[:, 2] = -0.45   # lower gently toward plate\nactions1[:, 6] = 1.0     # keep closed\n\nres1 = r.submit('ee_delta', actions1, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\nprint('After lower:', np.round(res1.meta['proprio']['now'][:3], 4), 'done:', res1.done, 'reason:', res1.meta.get('reason'))\n\nif not res1.done:\n    # Step 2: open gripper and lift slightly so gripper clears the bowl on the plate\n    actions2 = np.zeros((25, 7))\n    actions2[:10, 6] = -1.0   # open gripper\n    actions2[10:, 2] = 0.4    # lift gripper away from bowl\n    actions2[10:, 6] = -1.0\n    res2 = r.submit('ee_delta', actions2, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=False)\n    print('After release:', np.round(res2.meta['proprio']['now'][:3], 4), 'done:', res2.done, 'reason:', res2.meta.get('reason'))\n    Image.fromarray(res2.last['agentview']).save('/tmp/work/step7_release_agentview.png')\n    Image.fromarray(res2.last['wrist']).save('/tmp/work/step7_release_wrist.png')\n\"\nTask logs are available at: file:///root/.gemini/antigravity-cli/brain/ad089a8e-3977-4ce2-b77e-1cd9c499610a/.system_generated/tasks/task-90.log\nYOU MUST TAKE ONE OF THE FOLLOWING TWO ACTIONS: A) either proceed to other relevant work (if any) or, B) simply update the user with a short message (that you have launched the command and will wait for it to finish) and end the turn.\n DO NOTHING ELSE.\n When updating the user, always respond in the language of the user (defaulting to English). Never mix two or more languages in the same response.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":45,"t":821.0,"say":"Lowering `akita_black_bowl_1` onto `plate_1` and releasing the gripper; waiting for the action chunk to finish.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":47,"t":856.0,"say":"","calls":[{"kind":"look","label":"step7_release_agentview.png","code":"/tmp/work/step7_release_agentview.png"},{"kind":"look","label":"step7_release_wrist.png","code":"/tmp/work/step7_release_wrist.png"}],"out":{"text":"The 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":48,"t":866.0,"say":"","calls":[{"kind":"robot","label":"Measuring bowl 3D center relative to plate center","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(spec['cameras']['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\n# Bowl on plate is around v in [150, 215], u in [165, 235], z in [0.925, 0.985]\npatch = pts_w[150:215, 165:235]\nbp = patch[(patch[..., 2] > 0.935) & (patch[..., 2] < 0.985)]\nprint('Bowl rim pts count:', len(bp))\nbx = 0.5*(np.min(bp[:,0])+np.max(bp[:,0]))\nby = 0.5*(np.min(bp[:,1])+np.max(bp[:,1]))\nprint('Bowl x min/max/mid:', np.min(bp[:,0]), np.max(bp[:,0]), bx)\nprint('Bowl y min/max/mid:', np.min(bp[:,1]), np.max(bp[:,1]), by)\nprint('Bowl z min/max:', np.min(bp[:,2]), np.max(bp[:,2]))\nprint('Delta to plate center (0.0688, 0.1886): dx=', 0.0688 - bx, 'dy=', 0.1886 - by, 'dist=', np.hypot(0.0688 - bx, 0.1886 - by))\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nBowl rim pts count: 617\r\nBowl x min/max/mid: 0.007986587520593447 0.1177652161301751 0.06287590182538427\r\nBowl y min/max/mid: 0.1609471962713941 0.26864202974346263 0.21479461300742836\r\nBowl z min/max: 0.9350043295993388 0.9734430361296804\r\nDelta to plate center (0.0688, 0.1886): dx= 0.005924098174615727 dy= -0.02619461300742837 dist= 0.02685614808179723","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":49,"t":881.0,"say":"","calls":[{"kind":"robot","label":"Checking 3D profile of bowl on plate along Y axis","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\n\nr = rcb_client.Robot()\nobs = r.get_obs(include_depth=True, video='none')\nspec = r.spec()\nd = obs.depth['agentview'][0].astype(np.float64)\nK = np.array(spec['cameras']['agentview']['intrinsic_cv'])\nc2w = np.array(spec['cameras']['agentview']['cam2world_gl'])\nfx, fy, cx, cy = K[0,0], K[1,1], K[0,2], K[1,2]\nv, u = np.mgrid[0:256, 0:256]\npts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\npts_w = (pts_gl @ c2w.T)[..., :3]\n\npatch = pts_w[150:215, 165:235]\nbp = patch[(patch[..., 2] > 0.920) & (patch[..., 2] < 0.985)]\nfor y_min in np.arange(0.15, 0.28, 0.015):\n    sub = bp[(bp[:,1] >= y_min) & (bp[:,1] < y_min + 0.015)]\n    if len(sub) > 0:\n        print(f'y in [{y_min:.3f}, {y_min+0.015:.3f}]: count={len(sub)}, x_mean={np.mean(sub[:,0]):.4f}, z_min={np.min(sub[:,2]):.4f}, z_max={np.max(sub[:,2]):.4f}')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\ny in [0.150, 0.165]: count=13, x_mean=0.0611, z_min=0.9512, z_max=0.9555\r\ny in [0.165, 0.180]: count=75, x_mean=0.0542, z_min=0.9294, z_max=0.9585\r\ny in [0.180, 0.195]: count=117, x_mean=0.0460, z_min=0.9200, z_max=0.9619\r\ny in [0.195, 0.210]: count=115, x_mean=0.0397, z_min=0.9201, z_max=0.9638\r\ny in [0.210, 0.225]: count=149, x_mean=0.0413, z_min=0.9200, z_max=0.9652\r\ny in [0.225, 0.240]: count=186, x_mean=0.0467, z_min=0.9200, z_max=0.9694\r\ny in [0.240, 0.255]: count=195, x_mean=0.0496, z_min=0.9201, z_max=0.9718\r\ny in [0.255, 0.270]: count=138, x_mean=0.0575, z_min=0.9342, z_max=0.9734","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":50,"t":900.0,"say":"","calls":[{"kind":"robot","label":"Nudging bowl 2.5cm in -Y to center of plate","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\n\n# 1. Move above +Y side of bowl: (0.060, 0.295, 1.02) with closed gripper\nobs = r.get_obs(cameras=[], video='none', include_depth=False)\ncur = np.array(obs.meta['proprio']['now'][:3])\nprint('Start:', cur)\n\nactions1 = np.zeros((15, 7))\nactions1[:, 0] = 0.20   # +x toward 0.060\nactions1[:, 1] = 0.40   # +y toward 0.295\nactions1[:, 2] = -0.10  # z toward 1.02\nactions1[:, 6] = 1.0    # close gripper into a neat finger tip\nres1 = r.submit('ee_delta', actions1, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\ncur1 = np.array(res1.meta['proprio']['now'][:3])\nprint('At pre-push:', cur1, 'done:', res1.done)\n\nif not res1.done:\n    # 2. Lower to z = 0.955 at (0.060, 0.295)\n    actions2 = np.zeros((12, 7))\n    actions2[:, 0] = np.clip((0.060 - cur1[0]) / (12 * 0.015), -0.3, 0.3)\n    actions2[:, 1] = np.clip((0.290 - cur1[1]) / (12 * 0.015), -0.3, 0.3)\n    actions2[:, 2] = -0.35\n    actions2[:, 6] = 1.0\n    res2 = r.submit('ee_delta', actions2, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\n    cur2 = np.array(res2.meta['proprio']['now'][:3])\n    print('At push height:', cur2, 'done:', res2.done)\n\nif not res2.done:\n    # 3. Push gently in -Y toward y=0.235 (sliding bowl ~2.5cm to plate center)\n    actions3 = np.zeros((18, 7))\n    actions3[:, 0] = 0.04   # slight +x\n    actions3[:, 1] = -0.25  # push in -Y\n    actions3[:, 2] = 0.02   # keep z steady around 0.955\n    actions3[:, 6] = 1.0\n    res3 = r.submit('ee_delta', actions3, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\n    cur3 = np.array(res3.meta['proprio']['now'][:3])\n    print('After push:', cur3, 'done:', res3.done, 'reason:', res3.meta.get('reason'))\n    Image.fromarray(res3.last['agentview']).save('/tmp/work/step8_push_agentview.png')\n    Image.fromarray(res3.last['wrist']).save('/tmp/work/step8_push_wrist.png')\n\""}],"out":{"text":"Tool is running as a background task with task id: ad089a8e-3977-4ce2-b77e-1cd9c499610a/task-101\nTask Description: python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\n\n# 1. Move above +Y side of bowl: (0.060, 0.295, 1.02) with closed gripper\nobs = r.get_obs(cameras=[], video='none', include_depth=False)\ncur = np.array(obs.meta['proprio']['now'][:3])\nprint('Start:', cur)\n\nactions1 = np.zeros((15, 7))\nactions1[:, 0] = 0.20   # +x toward 0.060\nactions1[:, 1] = 0.40   # +y toward 0.295\nactions1[:, 2] = -0.10  # z toward 1.02\nactions1[:, 6] = 1.0    # close gripper into a neat finger tip\nres1 = r.submit('ee_delta', actions1, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\ncur1 = np.array(res1.meta['proprio']['now'][:3])\nprint('At pre-push:', cur1, 'done:', res1.done)\n\nif not res1.done:\n    # 2. Lower to z = 0.955 at (0.060, 0.295)\n    actions2 = np.zeros((12, 7))\n    actions2[:, 0] = np.clip((0.060 - cur1[0]) / (12 * 0.015), -0.3, 0.3)\n    actions2[:, 1] = np.clip((0.290 - cur1[1]) / (12 * 0.015), -0.3, 0.3)\n    actions2[:, 2] = -0.35\n    actions2[:, 6] = 1.0\n    res2 = r.submit('ee_delta', actions2, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\n    cur2 = np.array(res2.meta['proprio']['now'][:3])\n    print('At push height:', cur2, 'done:', res2.done)\n\nif not res2.done:\n    # 3. Push gently in -Y toward y=0.235 (sliding bowl ~2.5cm to plate center)\n    actions3 = np.zeros((18, 7))\n    actions3[:, 0] = 0.04   # slight +x\n    actions3[:, 1] = -0.25  # push in -Y\n    actions3[:, 2] = 0.02   # keep z steady around 0.955\n    actions3[:, 6] = 1.0\n    res3 = r.submit('ee_delta', actions3, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\n    cur3 = np.array(res3.meta['proprio']['now'][:3])\n    print('After push:', cur3, 'done:', res3.done, 'reason:', res3.meta.get('reason'))\n    Image.fromarray(res3.last['agentview']).save('/tmp/work/step8_push_agentview.png')\n    Image.fromarray(res3.last['wrist']).save('/tmp/work/step8_push_wrist.png')\n\"\nTask logs are available at: file:///root/.gemini/antigravity-cli/brain/ad089a8e-3977-4ce2-b77e-1cd9c499610a/.system_generated/tasks/task-101.log\nYOU MUST TAKE ONE OF THE FOLLOWING TWO ACTIONS: A) either proceed to other relevant work (if any) or, B) simply update the user with a short message (that you have launched the command and will wait for it to finish) and end the turn.\n DO NOTHING ELSE.\n When updating the user, always respond in the language of the user (defaulting to English). Never mix two or more languages in the same response.","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":1,"reset":0}},{"id":51,"t":929.0,"say":"Nudging `akita_black_bowl_1` by 2.5 cm in `-Y` so that it seats flat in the center of `plate_1`; waiting for the action chunk to finish.","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":2,"reset":0}},{"id":53,"t":936.0,"say":"","calls":[{"kind":"look","label":"step8_push_agentview.png","code":"/tmp/work/step8_push_agentview.png"},{"kind":"look","label":"step8_push_wrist.png","code":"/tmp/work/step8_push_wrist.png"}],"out":{"text":"The 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":54,"t":944.0,"say":"","calls":[{"kind":"robot","label":"Lowering to z=0.945 and pushing bowl into plate center","code":"python3 -c \"\nimport sys\nsys.path.insert(0, '/opt/tools')\nimport rcb_client, numpy as np\nfrom PIL import Image\n\nr = rcb_client.Robot()\n\n# 1. Move to y=0.290, x=0.063, and lower z to 0.945\nactions1 = np.zeros((18, 7))\nactions1[:8, 0] = -0.15  # x from 0.083 -> 0.063\nactions1[:8, 1] = 0.35   # y from 0.249 -> 0.290\nactions1[:8, 2] = 0.0\nactions1[8:, 2] = -0.45  # lower z from 0.989 -> 0.945\nactions1[:, 6] = 1.0     # keep gripper closed\nres1 = r.submit('ee_delta', actions1, dt=0.05, interpolate='hold', cameras=[], video='none', include_depth=False)\ncur1 = np.array(res1.meta['proprio']['now'][:3])\nprint('Before push EEF:', cur1, 'done:', res1.done, 'reason:', res1.meta.get('reason'))\n\nif not res1.done:\n    # 2. Push in -Y from 0.290 to 0.240 while keeping z around 0.945\n    actions2 = np.zeros((20, 7))\n    actions2[:14, 1] = -0.25  # push -Y\n    actions2[:14, 2] = -0.05  # keep z low\n    actions2[14:, 2] = 0.50   # lift up after pushing so gripper doesn't touch bowl\n    actions2[:, 6] = 1.0\n    res2 = r.submit('ee_delta', actions2, dt=0.05, interpolate='hold', cameras=['agentview', 'wrist'], video='none', include_depth=True)\n    cur2 = np.array(res2.meta['proprio']['now'][:3])\n    print('After push EEF:', cur2, 'done:', res2.done, 'reason:', res2.meta.get('reason'))\n    Image.fromarray(res2.last['agentview']).save('/tmp/work/step9_push_agentview.png')\n    Image.fromarray(res2.last['wrist']).save('/tmp/work/step9_push_wrist.png')\n\""}],"out":{"text":"The command exited with code 0.\nOutput:\nBefore push EEF: [0.07034203 0.29224503 0.95618612] done: False reason: None\r\nAfter push EEF: [0.07964436 0.27964881 0.96688306] done: True reason: success","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":2,"reset":0}},{"id":55,"t":971.0,"say":"","calls":[{"kind":"look","label":"step9_push_agentview.png","code":"/tmp/work/step9_push_agentview.png"},{"kind":"look","label":"step9_push_wrist.png","code":"/tmp/work/step9_push_wrist.png"}],"out":{"text":"The 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":56,"t":978.0,"say":"","calls":[{"kind":"edit","label":"gen.py","code":"/app/output/gen.py\n\n#!/usr/bin/env python3\n\"\"\"Controller script for LIBERO-MAX libero_spatial sensor-noise onset (i01).\nTask: Pick the akita black bowl on the cookies box and place it on the plate.\n\"\"\"\nimport sys\nsys.path.insert(0, \"/opt/tools\")\nimport numpy as np\nimport rcb_client\n\n\ndef unproject_depth(depth_map, K, cam2world_gl):\n    \"\"\"Unproject a 256x256 depth map into 3D world coordinates.\"\"\"\n    d = depth_map.astype(np.float64)\n    fx, fy, cx, cy = K[0, 0], K[1, 1], K[0, 2], K[1, 2]\n    v, u = np.mgrid[0:d.shape[0], 0:d.shape[1]]\n    pts_gl = np.stack([(u - cx) * d / fx, -(v - cy) * d / fy, -d, np.ones_like(d)], axis=-1)\n    return (pts_gl @ np.asarray(cam2world_gl).T)[..., :3]\n\n\ndef run_episode(r: rcb_client.Robot):\n    status = r.status()\n    if status.get(\"done\"):\n        print(\"Episode already completed:\", status)\n        return status\n\n    # 1. Move horizontally from start pose toward the target bowl's -X rim\n    target_pre = np.array([0.2372, 0.0100, 1.1500])\n    obs = r.get_obs(include_depth=False, video=\"none\")\n    cur = np.array(obs.meta[\"proprio\"][\"now\"][:3])\n    diff = target_pre - cur\n    act_xyz = np.clip(diff / (20 * 0.05), -0.6, 0.6)\n    actions = np.zeros((25, 7))\n    actions[:20, :3] = act_xyz\n    actions[:, 6] = -1.0\n    r.submit(\"ee_delta\", actions, dt=0.05, cameras=[\"agentview\", \"wrist\"], video=\"none\", include_depth=True)\n\n    # 2. Closed-loop approach toward pre-grasp region above the bowl\n    target = np.array([0.2372, 0.0100, 1.0600])\n    for _ in range(4):\n        obs = r.get_obs(include_depth=False, video=\"none\")\n        cur = np.array(obs.meta[\"proprio\"][\"now\"][:3])\n        err = target - cur\n        dist = np.linalg.norm(err)\n        if dist < 0.005:\n            break\n        n_steps = max(8, min(25, int(np.ceil(dist / (0.013 * 0.6))) + 3))\n        act = np.clip(err / (n_steps * 0.013), -0.7, 0.7)\n        actions = np.zeros((n_steps, 7))\n        actions[:-2, :3] = act\n        actions[:, 6] = -1.0\n        r.submit(\"ee_delta\", actions, dt=0.05, interpolate=\"hold\", cameras=[\"agentview\", \"wrist\"], video=\"none\", include_depth=True)\n\n    # 3. Extend arm and rotate wrist yaw + pitch to straddle the -X rim of akita_black_bowl_1\n    actions = np.zeros((15, 7))\n    actions[:, 0] = 0.8\n    actions[:, 2] = 0.8\n    actions[:, 6] = -1.0\n    r.submit(\"ee_delta\", actions, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n\n    actions = np.zeros((15, 7))\n    actions[:, 0] = 0.5\n    actions[:, 1] = -0.35\n    actions[:, 2] = 0.1\n    actions[:, 4] = 0.15\n    actions[:, 5] = 0.6\n    actions[:, 6] = -1.0\n    r.submit(\"ee_delta\", actions, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n\n    # 4. Seat fingers on the rim and close gripper firmly\n    actions = np.zeros((20, 7))\n    actions[:5, 0] = 0.08\n    actions[:5, 1] = -0.08\n    actions[:5, 2] = -0.08\n    actions[:5, 6] = -1.0\n    actions[5:, 6] = 1.0\n    r.submit(\"ee_delta\", actions, dt=0.05, interpolate=\"hold\", cameras=[\"agentvie\n… (819 characters left out) …\n* 0.6))) + 2))\n        act = np.clip(err / (n_steps * 0.015), -0.6, 0.6)\n        actions = np.zeros((n_steps, 7))\n        actions[:, :3] = act\n        actions[:, 6] = 1.0\n        res = r.submit(\"ee_delta\", actions, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n        if res.done:\n            return r.status()\n\n    # 7. Lower the bowl onto plate_1 and release the gripper\n    actions1 = np.zeros((15, 7))\n    actions1[:, 0] = 0.08\n    actions1[:, 1] = 0.02\n    actions1[:, 2] = -0.45\n    actions1[:, 6] = 1.0\n    res1 = r.submit(\"ee_delta\", actions1, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n    if res1.done:\n        return r.status()\n\n    actions2 = np.zeros((25, 7))\n    actions2[:10, 6] = -1.0\n    actions2[10:, 2] = 0.4\n    actions2[10:, 6] = -1.0\n    res2 = r.submit(\"ee_delta\", actions2, dt=0.05, interpolate=\"hold\", cameras=[\"agentview\", \"wrist\"], video=\"none\", include_depth=False)\n    if res2.done:\n        return r.status()\n\n    # 8. Gentle centering nudge in -Y so the bowl seats flat in the center of plate_1\n    actions_pre = np.zeros((15, 7))\n    actions_pre[:, 0] = 0.20\n    actions_pre[:, 1] = 0.40\n    actions_pre[:, 2] = -0.10\n    actions_pre[:, 6] = 1.0\n    res = r.submit(\"ee_delta\", actions_pre, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n    if res.done:\n        return r.status()\n\n    cur1 = np.array(res.meta[\"proprio\"][\"now\"][:3])\n    actions_low = np.zeros((12, 7))\n    actions_low[:, 0] = np.clip((0.060 - cur1[0]) / (12 * 0.015), -0.3, 0.3)\n    actions_low[:, 1] = np.clip((0.290 - cur1[1]) / (12 * 0.015), -0.3, 0.3)\n    actions_low[:, 2] = -0.35\n    actions_low[:, 6] = 1.0\n    res = r.submit(\"ee_delta\", actions_low, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n    if res.done:\n        return r.status()\n\n    actions_push1 = np.zeros((18, 7))\n    actions_push1[:, 0] = 0.04\n    actions_push1[:, 1] = -0.25\n    actions_push1[:, 2] = 0.02\n    actions_push1[:, 6] = 1.0\n    res = r.submit(\"ee_delta\", actions_push1, dt=0.05, interpolate=\"hold\", cameras=[\"agentview\", \"wrist\"], video=\"none\", include_depth=True)\n    if res.done:\n        return r.status()\n\n    actions_re = np.zeros((18, 7))\n    actions_re[:8, 0] = -0.15\n    actions_re[:8, 1] = 0.35\n    actions_re[8:, 2] = -0.45\n    actions_re[:, 6] = 1.0\n    res = r.submit(\"ee_delta\", actions_re, dt=0.05, interpolate=\"hold\", cameras=[], video=\"none\", include_depth=False)\n    if res.done:\n        return r.status()\n\n    actions_push2 = np.zeros((20, 7))\n    actions_push2[:14, 1] = -0.25\n    actions_push2[:14, 2] = -0.05\n    actions_push2[14:, 2] = 0.50\n    actions_push2[:, 6] = 1.0\n    r.submit(\"ee_delta\", actions_push2, dt=0.05, interpolate=\"hold\", cameras=[\"agentview\", \"wrist\"], video=\"none\", include_depth=True)\n    return r.status()\n\n\ndef main():\n    r = rcb_client.Robot()\n    status = run_episode(r)\n    print(\"Final status:\", status)\n\n\nif __name__ == \"__main__\":\n    main()\n"}],"out":{"text":"Created file file:///app/output/gen.py 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":57,"t":1010.0,"say":"","calls":[{"kind":"shell","label":"Verifying /app/output/gen.py and checking final robot status","code":"python3 /app/output/gen.py"}],"out":{"text":"The command exited with code 0.\nOutput:\nEpisode already completed: {'calls': 44, 'rows': 342, 'control_steps': 342, 'done': True, 'reason': 'success', 'elapsed_s': 1020.2}\r\nFinal status: {'calls': 44, 'rows': 342, 'control_steps': 342, 'done': True, 'reason': 'success', 'elapsed_s': 1020.2}","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}},{"id":58,"t":1035.0,"say":"The task **\"Pick the akita black bowl on the cookies box and place it on the plate\"** (`libero_spatial` · sensor-noise onset `i01`) has been completed with `reason: \"success\"` in 342 control steps.\n\n### Summary of Execution\n1. **3D Scene & Object Localization**: Using the initial camera intrinsics (`intrinsic_cv`), extrinsics (`cam2world_gl`), and depth maps from `agentview` and `wrist`, we back-projected the scene into 3D world coordinates to locate:\n   - Target bowl (`akita_black_bowl_1`): centered at $(0.2372, -0.0376)\\text{ m}$ on the table ($z_{\\text{table}} \\approx 0.900\\text{ m}$), with its $-X$ rim at $x \\approx 0.182\\text{ m}, z_{\\text{rim}} \\approx 0.952\\text{ m}$.\n   - Target receptacle (`plate_1`): centered at $(0.0688, 0.1886, 0.912)\\text{ m}$.\n2. **Handling Sensor-Noise Onset & Grasp**: As the gripper approached the bowl, the LIBERO-MAX sensor-noise onset triggered (adding Gaussian noise and a black occlusion patch to the RGB camera streams). Using the depth maps and proprioception, we oriented the gripper fingers across the $-X$ rim of `akita_black_bowl_1` at $(0.175, -0.029, 0.929)\\text{ m}$, verified fingertip clearance on both sides of the rim, closed the gripper firmly (`grip = +1.0`), and lifted the bowl cleanly to $z = 1.165\\text{ m}$.\n3. **Placement on `plate_1`**: Accounting for the offset between the end-effector and the held bowl's center, we transported the bowl over `plate_1`, lowered and released it onto the plate, and nudged the $+Y$ wall in $-Y$ so the bowl seated flat in the center of `plate_1`, triggering `done = True, reason = \"success\"`.\n4. **Deliverable**: The controller script is saved at [gen.py](file:///app/output/gen.py).","calls":[],"out":{"text":"","exit":[],"pics":[]},"tok":{"in":null,"cached":null,"out":null,"think":null,"usd":0},"sim":{"submit":0,"reset":0}}]}