Datasets:

tmeynier
/

hepha_act_100_domain_randomized

configs:
  - config_name: default
    data_files:
      - split: train
        path: hf_viewer/train.parquet
tags:
  - lerobot
  - robotics
  - imitation-learning
  - mujoco
  - act
task_categories:
  - robotics
pretty_name: Hepha ACT Dataset

tmeynier/hepha_act_100_domain_randomized

LeRobot-style behavior-cloning dataset generated from the Hepha MuJoCo simulation.

Summary

Robot type: hepha_mujoco
Codebase version: v3.0
Episodes: 100
Frames: 200341
FPS: 30
Joint normalization: min_max_0_1

Features

timestamp: float32 [1]
frame_index: int64 [1]
episode_index: int64 [1]
index: int64 [1]
task_index: int64 [1]
episode.drawer_index: int64 [1]
episode.cube_position: float32 [3]
episode.cube_quaternion: float32 [4]
observation.drawer_index: int64 [1]
observation.state: float32 [15]
action: float32 [15]
observation.state_raw: float32 [15]
action_raw: float32 [15]
observation.images.head_camera: video [3, 480, 640]

Policy-Facing Columns

observation.state: normalized robot joints in [0, 1]
observation.drawer_index: selected drawer target for each frame
action: normalized next-step robot joint targets in [0, 1]
observation.images.head_camera: RGB video frames from the robot camera

Extra Columns

observation.state_raw: raw joint-sensor readings (including configured sensor noise)
action_raw: raw next-step MuJoCo joint positions
episode.drawer_index: selected drawer index for each frame
episode.cube_position: initial cube position for each frame
episode.cube_quaternion: initial cube orientation for each frame

Notes

The dataset was produced by first computing the full IK episode, then resampling the robot joint trajectory at a constant normalized joint speed before saving frames/actions. Training code appends the normalized drawer target (drawer_index - 1) / 8 to the policy state when observation.drawer_index is present.

Joint limits and the normalization formula are stored in meta/info.json.