An adaptive approach to swarm surveillance using particle swarm optimization

Abstract

Swarm robotics is a field of robotics in which coordination between relatively simple multi-robot system leads to complex desired behavior. This field of robotics is inspired from behavior of insects like ants, bees and cockroaches where simple actions performed by them achieves complex swarm behavior. Scalability, miniaturization and lower complexity of individual robots are three main motivations of swarm robotics. This paper discusses an important application of swarm robotics to surveillance task and provides an effective algorithm for protection against enemy intrusion. Results are verified by simulating intrusion in case of `Castle', `Guards', `Enemy' system wherein guards protect the castle from enemy intrusion. A comparison is presented from the case where `Social potential field' is used as a controller for obtaining desired swarm behavior.