Publications

MoE-DP: An MoE-Enhanced Diffusion Policy for Robust Long-Horizon Robotic Manipulation with Skill Decomposition and Failure Recovery

Baiye Cheng*, Tianhai Liang*, Suning Huang, Maanping Shao, Feihong Zhang, Botian Xu, Zhengrong Xue, Huazhe Xu

ICRA 2026 [Project]

A robust long-horizon robotic manipulation framework integrating Mixture-of-Experts into diffusion policies for skill decomposition, failure recovery and resilient visuomotor control across multi-stage tasks.

ParticleFormer: A 3D Point Cloud World Model for Multi-Object, Multi-Material Robotic Manipulation

Suning Huang, Qianzhong Chen, Xiaohan Zhang, Jiankai Sun, Mac Schwager

CoRL 2025 [Project]

A state-of-the-art 3D point cloud world model for complex scene dynamics modeling, enabling accurate dynamics prediction across multi-object and multi-material scenarios, and empowering model-based visuomotor control with novel configurations.

MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning

Suning Huang*, Zheyu Zhang*, Tianhai Liang, Yihan Xu, Zhehao Kou, Chenhao Lu, Guowei Xu, Zhengrong Xue, Huazhe Xu

ICML 2025 [Project]

A model-free visual RL algorithm achieving state-of-the-art performances in learning efficiency and performance on various tasks. The policy can even be directly trained on real robot to play tabletop golf!

DittoGym: Learning to Control Soft Shape-Shifting Robots

Suning Huang, Boyuan Chen, Huazhe Xu, Vincent Sitzmann

ICLR 2024 [Project]

A modeling of the highly-reconfigurable robot within a MPM-powered simulator, along with effective coarse-to-fine curriculum for high-dimensional RL policy training and a comprehensive reconfigurable robot testbed.