Code for Scalable Offline Model-Based RL with Action chunking
multi-robot serving engine for cloud robot foundation models
Official simulation reproduction for SpeedTuning (ICRA 2025).
End-to-end implementation of Action Chunking Transformers (ACT) for imitation learning in robot manipulation tasks. Trained and evaluated in MuJoCo simulation on a pick-and-place task using the ROBOTIS FFW humanoid robot.
A list of Action chunking RL papers (continually updated)
World-model assisted VLA-lite prototype for offline robot control with action-chunk reranking.
MuJoCo grasping with behavior cloning, action chunking, and honestly scoped language-conditioning evidence.
Reproducing Action Chunking Transformer (ACT) on a low-cost SO-101 arm.
A CPU-first end-to-end imitation learning lab: collect demos, train BC/action chunks, evaluate closed loop, write reports.
Four VLA action representations compared on multimodal demonstrations: bins, regression, diffusion, flow. Regression drives into the obstacle it should route around; flow keeps multimodality at 90x diffusion's control rate.
A from-scratch PyTorch implementation of Diffusion Policy Policy Optimization (DPPO) for fine-tuning dexterous manipulation tasks in Gymnasium Robotics environments
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