{
  "id": "signiq-egocentric-foldlaundry",
  "captured_at": "2025-08-21T11:42:55+09:00",
  "facility": "SignIQ Lab \u2014 Tokyo facility (egocentric capture suite)",
  "robot": {
    "name": "Egocentric human capture rig",
    "embodiment": "human-egocentric",
    "control_mode": "n/a (human capture)",
    "control_hz": 30.0,
    "action_dim": 190,
    "state_dim": 190,
    "cameras": [
      "egocentric"
    ]
  },
  "task": {
    "instruction": "Human fold laundry (egocentric capture, hands visible).",
    "subtasks": [
      {
        "index": 0,
        "name": "01 \u00b7 pose hold",
        "description": "Low-energy pose hold (hand stable)",
        "start": 0,
        "end": 90
      },
      {
        "index": 1,
        "name": "02 \u00b7 pose hold",
        "description": "Low-energy pose hold (hand stable)",
        "start": 90,
        "end": 168
      },
      {
        "index": 2,
        "name": "03 \u00b7 fast retract",
        "description": "Fast retract / repositioning",
        "start": 168,
        "end": 248
      },
      {
        "index": 3,
        "name": "04 \u00b7 fast retract",
        "description": "Fast retract / repositioning",
        "start": 248,
        "end": 326
      },
      {
        "index": 4,
        "name": "05 \u00b7 pose hold",
        "description": "Low-energy pose hold (hand stable)",
        "start": 326,
        "end": 450
      }
    ],
    "outcome": "success"
  },
  "schema": {
    "observation.state": {
      "shape": [
        190
      ],
      "names": [
        "hand_joint_000",
        "hand_joint_001",
        "hand_joint_002",
        "hand_joint_003",
        "hand_joint_004",
        "hand_joint_005",
        "hand_joint_006",
        "hand_joint_007",
        "hand_joint_008",
        "hand_joint_009",
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        "hand_joint_056",
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        "hand_joint_062",
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        "hand_joint_090",
        "hand_joint_091",
        "hand_joint_092",
        "hand_joint_093",
        "hand_joint_094",
        "hand_joint_095",
        "hand_joint_096",
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        "hand_joint_098",
        "hand_joint_099",
        "hand_joint_100",
        "hand_joint_101",
        "hand_joint_102",
        "hand_joint_103",
        "hand_joint_104",
        "hand_joint_105",
        "hand_joint_106",
        "hand_joint_107",
        "hand_joint_108",
        "hand_joint_109",
        "hand_joint_110",
        "hand_joint_111",
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        "hand_joint_113",
        "hand_joint_114",
        "hand_joint_115",
        "hand_joint_116",
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        "hand_joint_118",
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        "hand_joint_120",
        "hand_joint_121",
        "hand_joint_122",
        "hand_joint_123",
        "hand_joint_124",
        "hand_joint_125",
        "hand_joint_126",
        "hand_joint_127",
        "hand_joint_128",
        "hand_joint_129",
        "hand_joint_130",
        "hand_joint_131",
        "hand_joint_132",
        "hand_joint_133",
        "hand_joint_134",
        "hand_joint_135",
        "hand_joint_136",
        "hand_joint_137",
        "hand_joint_138",
        "hand_joint_139",
        "hand_joint_140",
        "hand_joint_141",
        "hand_joint_142",
        "hand_joint_143",
        "hand_joint_144",
        "hand_joint_145",
        "hand_joint_146",
        "hand_joint_147",
        "hand_joint_148",
        "hand_joint_149",
        "finger_angle_00",
        "finger_angle_01",
        "finger_angle_02",
        "finger_angle_03",
        "finger_angle_04",
        "finger_angle_05",
        "finger_angle_06",
        "finger_angle_07",
        "finger_angle_08",
        "finger_angle_09",
        "finger_angle_10",
        "finger_angle_11",
        "finger_angle_12",
        "finger_angle_13",
        "finger_angle_14",
        "finger_angle_15",
        "finger_angle_16",
        "finger_angle_17",
        "finger_angle_18",
        "finger_angle_19",
        "finger_angle_20",
        "finger_angle_21",
        "finger_angle_22",
        "finger_angle_23",
        "finger_angle_24",
        "finger_angle_25",
        "finger_angle_26",
        "finger_angle_27",
        "finger_angle_28",
        "finger_angle_29",
        "finger_angle_30",
        "finger_angle_31",
        "finger_angle_32",
        "finger_angle_33",
        "finger_angle_34",
        "finger_angle_35",
        "finger_angle_36",
        "finger_angle_37",
        "finger_angle_38",
        "finger_angle_39"
      ]
    },
    "action": {
      "shape": [
        190
      ],
      "kind": "human pose (mirrors state for export consistency)"
    },
    "observation.imu": {
      "shape": [
        6
      ]
    },
    "trajectory_projection": {
      "kind": "hand-pose path",
      "left": {
        "label": "wrist root (x,y,z)",
        "indices": [
          0,
          3
        ]
      },
      "right": {
        "label": "mid-finger root (x,y,z)",
        "indices": [
          75,
          78
        ]
      }
    }
  },
  "privacy": {
    "consent_for_model_training": true,
    "faces_blurred": true,
    "pii_reviewed": true,
    "consent_basis": "Recorded with explicit operator consent in our facility; faces blurred before delivery."
  },
  "attribution": {
    "demo_data_origin": "OpenGraphLabs-Research/manus-egocentric-sample",
    "license": "Apache-2.0",
    "note": "Demo data illustrating egocentric human capture quality. SignIQ commercial collections are recorded in-house with explicit consent and embodiment-specific retargeting pipelines."
  }
}