Learning from Local Experience: Informed Sampling Distributions for High Dimensional Motion Planning

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. Previous studies have demonstrated the benefits of utilizing prior solutions to motion planning problems for improving pl...

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Hauptverfasser:	Kobashi, Keita, Wang, Changhao, Zhao, Yu, Lin, Hsien-Chung, Tomizuka, Masayoshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Robotics
Online-Zugang:	Volltext bestellen
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