Tornado: A Robust Adaptive Foraging Algorithm for Swarm Robots

Abstract

Foraging is a benchmark problem for swarm robotics. It is inspired by swarms of insects cooperating to locate and/or transport food items that a single individual cannot move. The challenge is to program a swarm of simple robots, with minimal communication and individual capability, to search the environment for some search target and return it to their base collectively. In this paper we introduce a novel foraging algorithm: Tornado. The Tornado algorithm is inspired by the spiral tornado motion. The algorithm can scan an area with high speed given a large swarm. However, it can adapt in case of failure of some robots and successfully finish the job at a slower speed. Experimental results show that the algorithm provides better coverage and robustness compared to previous foraging algorithms.