Comparison of the PMHT path planning algorithm with the Genetic Algorithm for multiple platforms

This paper considers the problem of automatically coordinating multiple platforms to explore an unknown environment. The goal is a planning algorithm that provides a path for each platform in such a way that the collection of platforms cooperatively sense the environment in a globally efficient manner. A collection of discrete locales of interest is assumed to be known and the platforms use these as waypoints. The key feature of the method is to treat the assignment of locales to platforms as a target tracking problem. This paper compares the use of the Probabilistic Multi Hypothesis Tracker (PMHT) as a method of performing multiple platform batch data association with the Genetic Algorithm to solve the modified Multi Travelling Salesman Problem.