A Novel Communication Technique for Nanorobots Swarms Based on Evolutionary Strategies

This paper is concerned with the issue of modeling the behaviors of a swarm of nanorobots. The proposed algorithm identifies communication based coordination between nanorobots in the swarm in order to survey the predetermined target area. Also, controls the movements of the nanorobots with a self trajectory plan to enable them to make decision. The algorithm uses the (1+1) Evolution Strategy (ES) with One-Fifth success rule which is one of the first adaptive search algorithms proposed for optimization. A simulation platform is implemented and generates nanorobots swarm behaviors through evolutionary programming. When a nanorobot runs the optimization algorithm to mutate its movement plan, the simulator creates three mutation strategies that are randomly applied (Straight strategy, Swap Strategy and High Strategy). The paper includes also a comparative study among these strategies in order to investigate the most efficient one which will take a less average time to reach the predetermined target area. As a consequence, the simulation results show that the high mutation strategy makes the swarm of nanorobots communication to each other more efficient than the other mutation strategies.