A method for multi-agent exploration planning

Abstract

This project is concerned with the problem of exploration planning, which arises in systems of one or several mobile robots set with a task of exploring the map of their environment. Today the most popular algorithm that deals with this problem is the naive (greedy) approach, which is very simple and usually shows reasonably good results. This algorithm performs poorly in the worst case with several robots however. To cope with this problem, a new approach is developed and analyzed. This approach, called coordinated breadth-first search, is shown to guarantee linear scaling and to be asymptotically more efficient than the naive method in the worst case. To test these findings a computer simulation was developed which admits both algorithms and arbitrary maps. Finally, a comparison between the algorithms is made and further improvements are suggested.