Evolutionary optimization of fuzzy map formation using sonar data from robot swarms

Abstract

An essential component of an autonomous robotic swarm system is the ability to form an accurate map of its environment. In this paper, we consider the fuzzy approach to map generation using a swarm of robots fitted with multi-sonar sensors. While adopting an approach to map making similar to that in [1] we have reduced and simplified the number of parameters employed without significant loss of accuracy. These parameters are first optimized using a synthetic image of the target environment using differential evolution. A parallel implementation of the differential evolution optimizer is developed in MPI on a 200 core cluster. The algorithm has been tested on real-time data through experiments with three Parallax Stingray robots, each equipped with three sonars, with good results.