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action_delta_abs_mean
dict
action_ranges
dict
coverage_by_active_joint_count
dict
coverage_by_stage
dict
discarded_short_episodes
int64
episodes_with_nan
int64
near_joint_limit_fraction
float64
num_episodes
int64
rejected_initial_poses
int64
retained_steps
dict
state_ranges
dict
stuck_episode_fraction
float64
total_frames
int64
truncated_episode_fraction
float64
{ "joint_0": 0.002442586701363325, "joint_1": 0.0011787454131990671, "joint_2": 0.0007981357630342245, "joint_3": 0.0010654120706021786, "joint_4": 0.001408482319675386, "joint_5": 0.0023195811081677675, "joint_6": 0.00001655028245295398 }
{ "joint_0": { "max": 3.1354711055755615, "min": -3.139349937438965 }, "joint_1": { "max": 3.1379435062408447, "min": 0.0038626091554760933 }, "joint_2": { "max": 3.138418197631836, "min": 0.006693489383906126 }, "joint_3": { "max": 1.6975175142288208, "min": -1.68819558620...
{ "1": 256, "2": 191, "3": 193, "4": 115, "5": 98, "6": 96, "7": 75 }
{ "k1": 256, "k23": 384, "k47": 384 }
340
0
0.000011
1,024
67
{ "max": 4096, "mean": 3463.884765625, "min": 1027 }
{ "qpos": { "joint_0": { "max": 3.1356043815612793, "min": -3.139787435531616 }, "joint_1": { "max": 3.1526918411254883, "min": -0.013530549593269825 }, "joint_2": { "max": 3.149794101715088, "min": -0.0047327568754553795 }, "joint_3": { "max": 1.7...
0
3,547,018
0.258789

ARX5 MuJoCo Trajectories

Offline trajectory dataset for training world models on the ARX5 7-DOF robot arm in MuJoCo.

Contents

File Description
train.pt PyTorch tensor file containing 1024 episodes of robot arm trajectories (~3.5M total frames)
train_verification.json Dataset statistics: joint ranges, action deltas, coverage by stage and active joint count

Dataset Stats

  • Episodes: 1,024
  • Total frames: 3,547,018
  • Steps per episode: min 1,027 / mean 3,464 / max 4,096
  • State space: 14-dim (7 joint positions + 7 joint velocities)
  • Action space: 7-dim (joint position targets)
  • Discarded short episodes: 340
  • Episodes with NaN: 0
  • Stuck episodes: 0%
  • Near joint-limit fraction: ~0.001%

Usage

import torch
data = torch.load("train.pt", weights_only=False)

Source

Generated from randomised MuJoCo rollouts of the ARX5 arm with multi-stage coverage (single joint, 2-3 joints, 4-7 joints active).

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