Datasets:
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observation.state
sequence | action
sequence | timestamp
float32 0
89.8
| episode_index
int64 0
109
| frame_index
int64 0
449
| next.reward
float32 1
1
| next.done
bool 2
classes | index
int64 0
26.1k
| task_index
int64 0
215
|
|---|---|---|---|---|---|---|---|---|
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End of preview. Expand
in Dataset Viewer.
This dataset was created using LeRobot.
Dataset Structure
{
"codebase_version": "v2.0",
"robot_type": "unknown",
"total_episodes": 110,
"total_frames": 26113,
"total_tasks": 216,
"total_videos": 110,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 5,
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},
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"video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
"features": {
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}
Citation
BibTeX:
@inproceedings{zhou2023modularity,
title={Modularity through Attention: Efficient Training and Transfer of Language-Conditioned Policies for Robot Manipulation},
author={Zhou, Yifan and Sonawani, Shubham and Phielipp, Mariano and Stepputtis, Simon and Amor, Heni},
booktitle={Conference on Robot Learning},
pages={1684--1695},
year={2023},
organization={PMLR}
}
@article{zhou2023learning,
title={Learning modular language-conditioned robot policies through attention},
author={Zhou, Yifan and Sonawani, Shubham and Phielipp, Mariano and Ben Amor, Heni and Stepputtis, Simon},
journal={Autonomous Robots},
pages={1--21},
year={2023},
publisher={Springer}
}
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