hhllzz/robocasa-qwen3vl4b-completion-judge-seen-nav-p30-1to2
Video-Text-to-Text • Updated • 4
Datasets:
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annotation.human.task_description int64 0 4.43k | annotation.human.task_name int64 2 4.43k | observation.state listlengths 16 16 | action listlengths 12 12 | next.reward float32 0 1 | next.done bool 2
classes | timestamp float32 0 258 | frame_index int64 0 5.16k | episode_index int64 0 24.7k | index int64 0 27.6M | task_index int64 0 4.43k |
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End of preview. Expand in Data Studio
Pretraining (Human) — composite
Human teleoperation data for 235 composite (multi-step) tasks (~100 demos/task). The long-horizon half of RoboCasa365's 482-hour pretraining-human dataset.
Part of the RoboCasa365 collection. Flat LeRobot v3.0 mirror of RoboCasa365 — standard layout, drop-in loadable.
Stats
- Episodes: 24,687
- Frames: 27,610,913 (20 fps → 383 h)
- Tasks: 4,428 (natural-language phrasings; underlying RoboCasa task classes: 235)
- Cameras: 3 × 256×256 h264 video (
robot0_agentview_left/_right/_eye_in_hand) - Robot: PandaOmron (Panda 7-DoF arm + Omron mobile base + torso lift)
Loading
from lerobot.datasets.lerobot_dataset import LeRobotDataset
ds = LeRobotDataset("ember-lab-berkeley/robocasa365-pretrain-composite")
Feature schema (shared across all 6 robocasa365 repos)
observation.state: float64[16] —base_pos(3) + base_quat(4) + eef_pos_rel(3) + eef_quat_rel(4) + gripper_qpos(2)action: float64[12] —base_motion(4) + control_mode(1) + eef_delta_pos(3) + eef_delta_aa(3) + gripper(1)control_modeconvention:-1= arm active (eef delta + gripper drive),+1= base active (base_motion drives). Source of truth:robosuite.controllers.composite.HybridMobileBase.
observation.images.robot0_agentview_left/_right/_eye_in_hand: video, 256×256×3
License
MIT, inherited from upstream RoboCasa365.
Citation
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Models trained or fine-tuned on ember-lab-berkeley/robocasa365-pretrain-composite