Mobile Robot Path Planning based on Probabilistic Model Checking under Uncertainties
Wei Lou, Chunrui Xia · Advances in computer science research · 2015
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.