Distributed Multirobot Path Planning in Unknown Maps Using Petri Net Models

Abstract

This paper considers the path planning problem in multirobot systems with an unknown environment. The robots’ mission is given as a Boolean formula on the final states. We assume that the robots have partial knowledge of the environment and they are able to estimate the environment using a recursive Bayes estimator. Furthermore, they communicate between them if they are at a distance smaller than a given threshold in order to improve their own estimation. Each robot will solve an optimization problem based on the Petri net model of the environment and it will move accordingly. We provide an algorithm to be iterated by each robot and we evaluate the results by simulation.