27 citations · 65 across the 6 of their papers we have counts for
12 papers
Coupled Distributional Random Expert Distillation for World Model Online Imitation Learning
Shangzhe Li, Zhiao Huang, Hao Su
Imitation Learning (IL) has achieved remarkable success across various domains, including robotics, autonomous driving, and healthcare, by enabling agents to learn complex behavior…
Diffusion Dynamics Models with Generative State Estimation for Cloth Manipulation
Tongxuan Tian, Haoyang Li, Bo Ai +3
Cloth manipulation is challenging due to its highly complex dynamics, near-infinite degrees of freedom, and frequent self-occlusions, which complicate both state estimation and dyn…
Reward-free World Models for Online Imitation Learning
Shangzhe Li, Zhiao Huang, Hao Su
Imitation learning (IL) enables agents to acquire skills directly from expert demonstrations, providing a compelling alternative to reinforcement learning. However, prior online IL…
ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
Stone Tao, Fanbo Xiang, Arth Shukla +20
Simulation has enabled unprecedented compute-scalable approaches to robot learning. However, many existing simulation frameworks typically support a narrow range of scenes/tasks an…
RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
Haochen Shi, Huazhe Xu, Zhiao Huang +2
Modeling and manipulating elasto-plastic objects are essential capabilities for robots to perform complex industrial and household interaction tasks (e.g., stuffing dumplings, roll…
Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics
Sizhe Li, Zhiao Huang, Tao Du +3
Differentiable physics has recently been shown as a powerful tool for solving soft-body manipulation tasks. However, the differentiable physics solver often gets stuck when the ini…