64 citations · 96 across the 18 of their papers we have counts for
5 papers · 1 filter
Efficient Sim-to-real Transfer of Contact-Rich Manipulation Skills with Online Admittance Residual Learning
Xiang Zhang, Changhao Wang, Lingfeng Sun +3
Learning contact-rich manipulation skills is essential. Such skills require the robots to interact with the environment with feasible manipulation trajectories and suitable complia…
Distributed Multi-agent Interaction Generation with Imagined Potential Games
Lingfeng Sun, Pin-Yun Hung, Changhao Wang +2
Interactive behavior modeling of multiple agents is an essential challenge in simulation, especially in scenarios when agents need to avoid collisions and cooperate at the same tim…
Generalizable whole-body global manipulation of deformable linear objects by dual-arm robot in 3-D constrained environments
Mingrui Yu, Kangchen Lv, Changhao Wang +3
Constrained environments are common in practical applications of manipulating deformable linear objects (DLOs), where movements of both DLOs and robots should be constrained. This…
Contact-rich SE(3)-Equivariant Robot Manipulation Task Learning via Geometric Impedance Control
Joohwan Seo, Nikhil Potu Surya Prakash, Xiang Zhang +4
This paper presents a differential geometric control approach that leverages SE(3) group invariance and equivariance to increase transferability in learning robot manipulation task…
Learning from Local Experience: Informed Sampling Distributions for High Dimensional Motion Planning
Keita Kobashi, Changhao Wang, Yu Zhao +2
This paper presents a sampling-based motion planning framework that leverages the geometry of obstacles in a workspace as well as prior experiences from motion planning problems. P…