Sampling-based algorithms for optimal motion planning
نویسندگان
چکیده
منابع مشابه
Sampling-based algorithms for optimal motion planning
During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a functio...
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During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), have been shown to work well in practice and to possess theoretical guarantees such as probabilistic completeness. However, no theoretical bounds on the quality of the solution obtained by these algorithms, e.g., in terms of a given cost function, have been establish...
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Topological motion planning is a planning problem embedding topological concept of trajectories. In this work, we propose two asymptotically optimal sampling-based algorithms for topological motion planning: (a) a batch processingbased planner, termed Fast Marching Homology-embedded Tree star (FMHT*); and (b) an incremental anytime algorithm, termed Rapidly-exploring Random Homology-embedded Tr...
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Dynamical systems bring further challenges to the problem of motion planning, by additionally complicating the computation of collision-free paths with collision-free dynamic motions. This dissertation proposes efficient approaches for the optimal sampling-based motion planning algorithms, with a strong emphasis on the accommodation of realistic dynamical systems as the subject of motion planni...
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ژورنال
عنوان ژورنال: The International Journal of Robotics Research
سال: 2011
ISSN: 0278-3649,1741-3176
DOI: 10.1177/0278364911406761