Extended Reliable Robust Motion Planners

Abstract : A new method to plan guaranteed to be safe paths in an uncertain environment , with an uncertain initial and final configuration space, while avoiding static obstacles is presented. First, two improved versions of the previously proposed BoxRRT algorithm are presented: both with a better integration scheme and one of them with the control input selected according to a desired objective, and not randomly, as in the original formulation. Second, a new motion planner, called towards BoxRRT*, based on optimal Rapidly-exploring Random Trees algorithm and using interval analysis is introduced. Finally, each of the described algorithms are evaluated on a numerical example. Results show that our algorithms make it possible to find shorter reliable paths with less iterations.
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Adina Panchea, Alexandre Chapoutot, David Filliat. Extended Reliable Robust Motion Planners. 56th IEEE Conference on Decision and Control, Dec 2017, Melbourne, Australia. IEEE, 2017, 〈http://cdc2017.ieeecss.org〉. 〈10.1109/CDC.2017.8263805〉. 〈hal-01493576〉

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