3 papers
cs.RO2023
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…
cs.RO2018
Efficient Trajectory Optimization for Robot Motion Planning
Yu Zhao, Hsien-Chung Lin, Masayoshi Tomizuka
Motion planning for multi-jointed robots is challenging. Due to the inherent complexity of the problem, most existing works decompose motion planning as easier subproblems. However…
cs.RO2017
Real-Time Robust Finger Gaits Planning under Object Shape and Dynamics Uncertainties
Yongxiang Fan, Te Tang, Hsien-Chung Lin +2
Dexterous manipulation has broad applications in assembly lines, warehouses and agriculture. To perform large-scale manipulation tasks for various objects, a multi-fingered robotic…