Mobile Robot Path Planning based on Probabilistic Model Checking under Uncertainties

DOI

10.2991/icmmita-15.2015.265How to use a DOI?

Keywords

Mobile robot; Path planning; Probabilistic model checking; Markov decision process; Probabilistic computation tree logic.

Abstract

In this paper, a probabilistic model checking method for mobile robots path planning problem is proposed. Since surroundings always affect the behavior of mobile robots, four main environmental factors are analyzed as influencing parameters. With the map built by randomized sampling-based method, we model the uncertain motion behavior as a Markov Decision Process (MDP). Meanwhile, the properties are described in PCTL (Probabilistic Computation Tree Logic) which can be used to describe rich mission specifications. Then the path planning problem is mapped to the problem of generating an MDP control policy that maximizes the probability of accomplishing the mission objective satisfied a PCTL formula. We apply the PRISM platform to analyze model and verify properties. Our approach is demonstrated with illustrative case studies.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wei Lou
AU  - Chunrui Xia
PY  - 2015/11
DA  - 2015/11
TI  - Mobile Robot Path Planning based on Probabilistic Model Checking under Uncertainties
BT  - Proceedings of the 2015 3rd International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1437
EP  - 1445
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-15.2015.265
DO  - 10.2991/icmmita-15.2015.265
ID  - Lou2015/11
ER  -