LEGS: Fine-Tuning Teleop-Free VLAs for Humanoid Loco-manipulation in an Embodied Gaussian Splatting World
Paper • 2606.01458 • Published
A training set of the paper's SAM3D (50) condition for Task 3 (long-horizon), from LEGS (code, paper). The mesh-only baseline: rendered with SAM 3D meshes instead of the splat, without color calibration. Its states and actions are those of episodes 0–49 of the same task's LEGS (200) set.
| Episodes | 50 |
| Frames | 60,355 at 30 fps |
| Prompt | "pick the orange, turn right, and place it on the plate" |
| Camera | observation.images.ego_view, 640×480 |
| State and action | observation.state_psi0_18 and action.psi0_18, the 18-D end-effector layout described under State and action |
| Format | LeRobot v2.1 |
From a clone of the code repository:
bash scripts/train/download.sh --dataset hojjunekim/sam_turn_50_uni
TASK=turn DATASET=hojjunekim/sam_turn_50_uni bash scripts/train/psi0.sh # or pi05.sh / groot.sh
The other sets of the paper are listed under Paper datasets.
This dataset is distributed under the SAM License, because its images show object and table meshes generated with SAM 3D Objects. If you redistribute it, you must do so under that license and include a copy of it. If you publish research that uses this dataset, the SAM License requires you to acknowledge the use of SAM Materials.
@inproceedings{kim2026legs,
title = {LEGS: Fine-Tuning Teleop-Free VLAs for Humanoid Loco-manipulation in an Embodied Gaussian Splatting World},
author = {Kim, Hojune and Chen, Timothy and Sun, Jiankai and Osterberg, Lars W. and Chen, Qianzhong and Wang, Ke and Schwager, Mac},
booktitle = {Conference on Robot Learning (CoRL)},
year = {2026}
}