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Asymptotically Optimal Sampling-based Planners (1911.04044v3)
Published 11 Nov 2019 in cs.RO
Abstract: An asymptotically optimal sampling-based planner employs sampling to solve robot motion planning problems and returns paths with a cost that converges to the optimal solution cost, as the number of samples approaches infinity. This comprehensive article covers the theoretical characteristics of asymptotic optimality of motion planning algorithms, and traces its origins, analysis models, practical performance, extensions, and applications.