Swarms of mobile robots for area exploration

Abstract

This study investigates the use of a random-walk search algorithm for a swarm of mobile robots for area exploration. A stochastic process was employed to define the robots’ route, and a cluster-based distribution factor and nature-inspired algorithms were used to explore undiscovered areas. A distributed search technique was also evaluated for area exploration using a multi-robot team, with cost and performance of the swarm analyzed for determining the optimal size of the swarm. The results suggested that the random-walk search algorithm is a viable and cost-effective solution for area exploration by a swarm of robots, with the added benefit of improving performance. In addition, the optimal size of the swarm analysis revealed the optimum number of robots for a particular task.