64 citations · 70 across the 5 of their papers we have counts for
7 papers
Offline-Online Learning of Deformation Model for Cable Manipulation with Graph Neural Networks
Changhao Wang, Yuyou Zhang, Xiang Zhang +5
Manipulating deformable linear objects by robots has a wide range of applications, e.g., manufacturing and medical surgery. To complete such tasks, an accurate dynamics model for p…
Safe Online Gain Optimization for Variable Impedance Control
Changhao Wang, Zhian Kuang, Xiang Zhang +1
Smooth behaviors are preferable for many contact-rich manipulation tasks. Impedance control arises as an effective way to regulate robot movements by mimicking a mass-spring-dampin…
Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Tasks
Xiang Zhang, Shiyu Jin, Changhao Wang +2
This paper introduces a discrete-continuous action space to learn insertion primitives for robotic assembly tasks. Primitive is a sequence of elementary actions with certain exit c…
Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks
Xiang Zhang, Liting Sun, Zhian Kuang +1
Many manipulation tasks require robots to interact with unknown environments. In such applications, the ability to adapt the impedance according to different task phases and enviro…
Feedback-based Digital Higher-order Terminal Sliding Mode for 6-DOF Industrial Manipulators
Zhian Kuang, Xiang Zhang, Liting Sun +2
The precise motion control of a multi-degree of freedom~(DOF) robot manipulator is always challenging due to its nonlinear dynamics, disturbances, and uncertainties. Because most m…
Action Representations in Robotics: A Taxonomy and Systematic Classification
Philipp Zech, Erwan Renaudo, Simon Haller +2
Understanding and defining the meaning of "action" is substantial for robotics research. This becomes utterly evident when aiming at equipping autonomous robots with robust manipul…