Computer Science – Artificial Intelligence
Scientific paper
2009-12-01
Computer Science
Artificial Intelligence
7 pages, 5 figures. Presented in Ingelectra 2009 conference
Scientific paper
Probabilistic sampling methods have become very popular to solve single-shot path planning problems. Rapidly-exploring Random Trees (RRTs) in particular have been shown to be efficient in solving high dimensional problems. Even though several RRT variants have been proposed for dynamic replanning, these methods only perform well in environments with infrequent changes. This paper addresses the dynamic path planning problem by combining simple techniques in a multi-stage probabilistic algorithm. This algorithm uses RRTs for initial planning and informed local search for navigation. We show that this combination of simple techniques provides better responses to highly dynamic environments than the RRT extensions.
Araya-López Mauricio
Barriga Nicolas A.
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