Motion Planning for Car-Like Robots Using Lazy Probabilistics Roadmap Method

Abstract : In this paper we describe an approach to probabilistic roadmap method. Our algorithm builds initially a roadmap in the configuration space considering that all nodes and edges are collision-free, and searches the roadmap for the shortest path between start and goal nodes. If a collision with the obstacles occurs, the corresponding nodes and edges are removed from the roadmap or the planner updates the roadmap with new nodes and edges, and then searches for a shortest path. The procedure is repeated until a collision-free path is found. The goal of our approach is to minimize the number of collision checks and calls to the local method. Experimental results presented in this paper show that our approach is very efficient in practice.
Type de document :
Communication dans un congrès
MICAI: Mexican International Conference on Artificial Intelligence, Apr 2002, Yucatan, Mexico. 2nd Mexican International Conference on Artificial Intelligence, LNCS (2313), pp.1-10, 2002, MICAI 2002: Advances in Artificial Intelligence. 〈10.1007/3-540-46016-0_1〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00268530
Contributeur : Christine Carvalho de Matos <>
Soumis le : mardi 1 avril 2008 - 09:27:40
Dernière modification le : jeudi 24 mai 2018 - 15:59:23

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Abraham Sánchez Lopez, René Zapata, J. Abraham Arenas B.. Motion Planning for Car-Like Robots Using Lazy Probabilistics Roadmap Method. MICAI: Mexican International Conference on Artificial Intelligence, Apr 2002, Yucatan, Mexico. 2nd Mexican International Conference on Artificial Intelligence, LNCS (2313), pp.1-10, 2002, MICAI 2002: Advances in Artificial Intelligence. 〈10.1007/3-540-46016-0_1〉. 〈lirmm-00268530〉

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