Bio-Inspired Search Strategies for Robot Swarms

Abstract

We describe how the PSO algorithm can be embedded into a robot swarm by letting each bot's behavior be like a particle in the PSO. We call the algorithm the physically embedded PSO (pePSO). The bots swarm throughout the search space and take measurements. Over time, they cluster near the peak(s) or targets. We show through both 2D simulation results and robot hardware results that the pePSO effectively finds the targets with a minimum number of bot-bot communications. The second search strategy is based on the trophallactic behavior of social insects. Trophallaxis is the exchange of fluid by direct mouth-to-mouth contact. This phenomenon is observed in ants, bees, wasps and even dogs and birds. In our trophallaxis-based algorithm, the bots do not actually exchange information but instead make sensor measurements when two or more bots/particles are "in contact". The bots remain stationary for a certain time that is proportional to the measurement value. Bots thus cluster in areas of the search space that have high fitness/measurement values. This new trophallaxis-based search algorithm has several advantages over other swarmbased search techniques. First, no bot-bot communication is required. Thus, there is no concern with communication radius, protocol, or bandwidth. Second, the bots do not have to know their position. During the search, the bot/particle moves randomly except when it collides and stops, takes a measurement, and waits. At the end of the search, the cluster locations can be determined from a remote camera, special-purpose robot, or human canvassing. This paper is organized as follows: section 2 gives background on the Particle Swarm Optimization algorithm and its use in robot swarms and section 3 gives results from simulations and hardware results of embedding the PSO into a robot swarm. Section 4 discusses the trophallaxis-based search algorithm and section 5 gives simulation results using the trophallaxis algorithm. In section 6 we give our conclusions. * 1 1