README.md

metadata

library_name: lerobot
tags:
  - lerobot
  - robotics
  - imitation-learning
  - diffusion-policy
  - aloha
  - bimanual
datasets:
  - lerobot/aloha_sim_insertion_human

Decoupled Bimanual Diffusion — ALOHA Insertion — Shared State

EMA inference checkpoint for a decoupled bimanual diffusion policy trained on lerobot/aloha_sim_insertion_human.

Configuration

• Training steps: 20,000
• Batch size: 32
• Training seed: 1000
• Communication mode: none
• State routing: shared (both arm branches receive the full 14-dimensional state)
• Actions: two 7-dimensional arm actions
• Shared visual input: observation.images.top at 480 x 640
• Observation steps: 2
• Prediction horizon: 64
• Action steps: 32
• Checkpoint: EMA weights plus LeRobot preprocessor and postprocessor

Evaluation

Evaluated in AlohaInsertion-v0 with 400-step episodes and synchronous batches of 50 rollouts. Across seeds 1000 and 2000 (100 episodes total):

• Success: 16/100 (16%)
• Average reward sum: 218.80
• Average maximum reward: 2.36

Per-seed success was 7/50 (seed 1000) and 9/50 (seed 2000).

Notes

This is a research checkpoint from a custom LeRobot fork implementing decoupled bimanual diffusion. It is intended for the matching policy implementation and ALOHA simulation setup. Results may vary with environment and dependency versions.