README.md

metadata

license: other
tags:
  - robotics
  - imitation-learning
  - decentralized-control
  - multi-robot
  - rgb-d

RoboFactory Five-Task Decentralized Wrist RGB-D

Public research corpus for reproducible Stereo-CoRE shared-policy experiments.

Contract

• 500 successful synchronized demonstrations: 100 each of LiftBarrier (2 robots), CameraAlignment (3), ThreeRobotsStackCube (3), LongPipelineDelivery (4), and TakePhoto (4).
• A policy stream contains only one panda_hand wrist RGB-D observation and that robot's qpos.
• RGB is 640x480; depth is native metric depth stored in millimetres.
• No task ID, agent ID, peer/global/right-camera image, language, or communication is a policy input.
• HDF5 convention: action has T records, while RGB/depth/qpos have T+1 records. The final observation is the post-action state.

Reproducible training protocol

All methods use the same corpus, held-out episode split, action chunk 100, ACT posterior encoder with 4 layers, and policy decoder with 7 layers. The main Stereo-CoRE run uses hierarchical weighted item sampling: equal probability for task, then demonstration, local arm, and time index. The sampling label is never supplied to the policy.

Companion releases

• Code and protocols: https://github.com/YananZHOU5555/Stereo-CoRE
• Weights, configurations and raw results: https://huggingface.co/B111ue/Stereo-CoRE

The repository-level corpus_manifest.json and per-task audit/manifest files describe the public payload. Users remain responsible for complying with RoboFactory and simulator asset licenses.