2019/06/17 by Simon O. Obute, Obute, Simon O., Mehmet R. Doğar +3
Computer Science · Engineering · #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #Metaheuristic Optimization Algorithms Research #Modular Robots and Swarm Intelligence #Multiagent Systems (cs.MA) #Robotics (cs.RO)
paper · pdf · doi:10.48550/arxiv.1906.07030
openalex publication_date 2019/06/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Swarm foraging is a common test case application for multi-robot systems. In this paper we present a novel algorithm for controlling swarm robots with limited communication range and storage capacity to efficiently search for and retrieve targets within an unknown environment. In our approach, robots search using random walk and adjust their turn probability based on attraction and repulsion signals they sense from other robots. We compared our algorithm with five different variations reflecting absence or presence of attractive and/or repulsive communication signals. Our results show that best performance is achieved when both signals are used by robots for communication. Furthermore, we show through hardware experiments how the communication model we used in the simulation could be realized on real robots.