Robotics
LeRobot
Safetensors
act
imitation-learning
reinforcement-learning
grpo
mujoco
bimanual
roboeval
hybird-control

LocalModels / ACT-bimanual

Entry ACT-bimanual by team LocalModels (Saleh Alsharideh, Independent) to the CoRL 2026 RoboEval Diagnostic Bimanual Challenge. Official score 0.9861, 399 of 400 episodes successful.

Seven tasks run hand-designed RGB-D controllers (no learned weights); LiftPot runs an Action Chunking Transformer (ACT) trained on the demonstrations and fine-tuned in simulation with GRPO. Code, report and explainer videos: github.com/Sa74ll/RoboevalChallenge.

Path Content
submission/ the submitted bundle: metadata.yaml, policy/, checkpoint/ (seven hybrid.json controller selectors and the LiftPot ACT weights)
official_run/ the official run (seeds 1000-1049): results.json and the 400 episode logs
SHA1SUMS.txt SHA-1 of every file in submission/

The submission archive was packaged without checkpoint/; its checkpoint_url points to submission/checkpoint here.

Run

Needs RoboEval at tag corl2026-challenge.

hf download Sa74ll/LocalModels-ACT-bimanual --include "submission/*" --include SHA1SUMS.txt --local-dir ACT-bimanual
cd ACT-bimanual && sha1sum -c SHA1SUMS.txt
pip install -r submission/policy/requirements.txt
python -m roboeval.challenge.evaluate --submission submission --workers W --gpus 0

Results (official run)

Task Policy Successes Score
CubeHandover controller 50 1.000
LiftPot ACT 50 0.999
LiftTray controller 50 1.000
PackBox controller 49 0.954
PickSingleBookFromTable controller 50 0.987
RotateValve controller 50 1.000
StackSingleBookShelf controller 50 1.000
StackTwoBlocks controller 50 0.948
Suite 399 / 400 0.9861

Training data and every use of simulator state: the report, Sec. 3. The files here equal the submitted ones except three edits that do not change behaviour (no contact e-mail in metadata.yaml, local paths shortened in the LiftPot configs, a license notice in modeling_act.py); see GitHub.

License

Apache-2.0. modeling_act.py is modified from LeRobot (Apache-2.0).

Downloads last month

-

Downloads are not tracked for this model. How to track
Video Preview
loading

Datasets used to train Sa74ll/LocalModels-ACT-bimanual