Adaptive potential fields model for solving distributed area coverage problem in swarm robotics

Abstract: Complete coverage of a given region has become a fundamental problem addressed in the field of swarm robots. Currently available approaches to the coverage problem are typically of computational complexity, and are manually specified with different map settings, which are not scalable and flexible. To address these shortcomings, this paper describes an efficient distributed approach based on potential fields method and self-adaptive control. It makes no assumptions about prior knowledge on global map, and need few manual intervention during execution. Although the motion policy of each robot is very simple, efficient coverage behavior is achieved at team level. We evaluate the approach against a traditional rule-based method and pheromone method under different target area scenarios. It shows state-of-the-art performance, both in the percentage of coverage and the degree of connectivity.

Download: [PDF]