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        "variant": {}
      },
      "language": "The two robot arms must coordinate to insert the peg into the hole.",
      "preview_id": "robosuite-two-arm-peg-in-hole",
      "qpos0_robots": [
        "panda",
        "panda"
      ],
      "robot_id": "robosuite.robot.panda",
      "scene_id": "robosuite.scene.env.two-arm-peg-in-hole",
      "source_index": 15,
      "success": {
        "bar": null,
        "kind": "source-parsed",
        "notes": "TwoArmPegInHole._check_success returns True when d < 0.06 and -0.12 <= t <= 0.14 and cos > 0.95. robosuite environments do not terminate on success; they run to the horizon. Parsed from the pinned source. A reset scene is not a scored run."
      },
      "suite_key": "TwoArmPegInHole",
      "task_key": "TwoArmPegInHole",
      "version_id": "robosuite.fbee5844ff5632f5b5698e204ec5357ca50be0df"
    },
    {
      "assembly": {
        "entrypoint": "worlds/robosuite/scenes/wipe.xml",
        "reasons": [
          "the browser viewer does not open this scene: assets/worlds-adapter.js declares no resolver remotes for this suite (the site path worlds/robosuite/ and the pinned robosuite: asset remote), so it rejects the complete world",
          "native composed model of robosuite.make('Wipe') after reset() under seed 0 at robosuite fbee584",
          "WipeArena, Panda on RethinkMount, WipingGripper; a table with dirt markers; the arm carries the wiping tool",
          "poses and colours that reset() wrote into the compiled model are written back; the keyframe is the native reset qpos",
          "a compile of the published file reproduces every native body pose and geom frame; a second independent construction matches",
          "visual geoms are group 1 (visual-group-1-noncolliding); group 0 collision geoms stay in the XML and are not drawn",
          "64 mesh and texture files load from the pinned robosuite: remote; none is rehosted"
        ],
        "status": "blocked",
        "visibility_policy": "visual-group-1-noncolliding"
      },
      "capabilities": {
        "catalogue": {
          "evidence_ids": [
            "benchmarks-r38"
          ],
          "reasons": [],
          "supported": true
        },
        "preview": {
          "evidence_ids": [
            "benchmarks-r38"
          ],
          "reasons": [
            "fragment preview only: the official table_arena.xml the arena class loads",
            "the browser viewer does not open this scene: assets/worlds-adapter.js declares no resolver remotes for this suite (the site path worlds/robosuite/ and the pinned robosuite: asset remote), so it rejects the complete world"
          ],
          "supported": true
        },
        "replay": {
          "evidence_ids": [],
          "reasons": [
            "the shipped wipe demonstration (repository_version 1.0.0) stores its model as models/model_1.xml; MuJoCo 3.1.6 rejects that file (XML Error: problem reading attribute 'pos', element 'site', line 86), and _check_success needs the wiped-marker set that only stepping the environment builds",
            "the robomimic dataset repository (MIT dataset card) distributes v1.5 files recorded with robosuite 1.5.1; they do not restore at the 1.4.0 pin"
          ],
          "supported": false
        },
        "reproduced": {
          "evidence_ids": [],
          "reasons": [
            "no site-reproduced benchmark evaluation is recorded"
          ],
          "supported": false
        },
        "run": {
          "evidence_ids": [],
          "reasons": [
            "native robosuite 1.4.0 / MuJoCo 3.1.6 execution is not implemented in the browser"
          ],
          "supported": false
        }
      },
      "control": "osc-pose",
      "default_model_path": "worlds/robosuite/scenes/wipe.xml",
      "gym_id": "Wipe",
      "id": "robosuite.task.wipe",
      "kwargs": {
        "action": "float Box[-1,1]^6; per arm 3 position deltas (x0.05 m) and 3 axis-angle deltas (x0.5 rad) through OSC_POSE; the wiping tool has no actuator",
        "asset_bytes": 42953840,
        "asset_files": 64,
        "check_success_sha256": "dace31ee44531693126fc352487e30301ab24b133b936c2a702750d902f652a7",
        "control_freq": 20,
        "controller": "OSC_POSE",
        "env_configuration": "default",
        "family_class": "Wipe",
        "family_goal": "The robot arm must learn to wipe the whiteboard surface and clean all of the markings.",
        "grippers": [
          "WipingGripper"
        ],
        "horizon": 1000,
        "make": "robosuite.make('Wipe')",
        "mounts": [
          "RethinkMount"
        ],
        "native": {
          "nbody": 119,
          "ngeom": 211,
          "njnt": 7,
          "nmesh": 59,
          "nq": 7,
          "nu": 7,
          "nv": 7
        },
        "reset_seed": 0,
        "robots": [
          "Panda"
        ],
        "scene_description": "A table with a whiteboard surface and some markings is placed in front of a single robot arm, which has a whiteboard eraser mounted on its hand.",
        "scene_family": "34da968e6bdcd78496ea152f5597d37783016fce59c2c53d7e487e0bdb3e2f53",
        "scene_family_shared_with": [],
        "start_state_distribution": "The whiteboard markings are randomized at the beginning of each episode.",
        "variant": {}
      },
      "language": "The robot arm must learn to wipe the whiteboard surface and clean all of the markings.",
      "preview_id": "robosuite-wipe",
      "qpos0_robots": [
        "panda"
      ],
      "robot_id": "robosuite.robot.panda",
      "scene_id": "robosuite.scene.env.wipe",
      "source_index": 13,
      "success": {
        "bar": null,
        "kind": "source-parsed",
        "notes": "Wipe._check_success returns True when len(wiped_markers) == num_markers. The marker set is updated by reward() during env.step, so it cannot be read from a restored state. robosuite environments do not terminate on success; they run to the horizon. Parsed from the pinned source. A reset scene is not a scored run."
      },
      "suite_key": "Wipe",
      "task_key": "Wipe",
      "version_id": "robosuite.fbee5844ff5632f5b5698e204ec5357ca50be0df"
    }
  ],
  "versions": [
    {
      "coordinates": {
        "angle_unit": "radian",
        "frame": "mujoco-worldbody",
        "length_unit": "m",
        "up_axis": "z"
      },
      "evidence_ids": [
        "benchmarks-r38"
      ],
      "id": "robosuite.fbee5844ff5632f5b5698e204ec5357ca50be0df",
      "reset": {
        "kind": "robosuite-make-seeded-reset",
        "notes": "Tag v1.4.0 is this commit; setup.py and robosuite.__version__ declare 1.4.0. Each scene is robosuite.make(<name>, robots=Panda (two for the two-arm environments), controller_configs=load_controller_config(default_controller='OSC_POSE'), has_renderer=False, has_offscreen_renderer=False, use_camera_obs=False), then random.seed(0), numpy.random.seed(0) and the environment's own reset(), in an interpreter started with PYTHONHASHSEED=0. The hash seed matters for NutAssemblySingle and PickPlaceSingle only: they pick the kept object with random.choice over a set of names, whose order follows Python's string hash seed. Every other argument is the class default: 20 Hz control, horizon 1000, default grippers and mounts. Panda with OSC_POSE is the configuration the pinned docs/algorithms/benchmarking.md recommends and the shipped demonstration files record. Native runtime is MuJoCo 3.1.6 with NumPy 1.26.4 on CPython 3.12; setup.py asks for mujoco>=2.3.0. reset() samples object placements, cube sizes, the door position and the wipe markers from that seed; a different seed is the same scene family, not another world.",
        "randomness": null,
        "seed": "0"
      },
      "simulator": {
        "name": "robosuite",
        "version": "1.4.0"
      },
      "source": {
        "access": "public",
        "licence": "MIT",
        "url": "https://github.com/ARISE-Initiative/robosuite/tree/fbee5844ff5632f5b5698e204ec5357ca50be0df"
      },
      "spaces": {
        "action": "Box[-1,1]. Per arm, OSC_POSE takes 3 position deltas scaled to 0.05 m and 3 axis-angle deltas scaled to 0.5 rad, plus one gripper command where the arm carries an actuated gripper: 7 values for the single-arm environments, 6 for Wipe, 14 for TwoArmLift and TwoArmHandover, 12 for TwoArmPegInHole. Not joint positions.",
        "observation": "Dictionary observations: robot proprioception per arm and an object-state vector. Camera observations are switched off for the export."
      },
      "suite_id": "robosuite",
      "upstream": {
        "digest": "sha1:fbee5844ff5632f5b5698e204ec5357ca50be0df",
        "host": "github",
        "owner": "ARISE-Initiative",
        "ref": "fbee5844ff5632f5b5698e204ec5357ca50be0df",
        "repo": "robosuite",
        "url": "https://github.com/ARISE-Initiative/robosuite/tree/fbee5844ff5632f5b5698e204ec5357ca50be0df"
      }
    }
  ]
}
