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…