Leveraging area bounds information for autonomous decentralized multi-robot exploration

作者：Tsung-Ming Liu, Damian M. Lyons · 发表于：Robotics and Autonomous Systems · 年份：2015 · 被引用次数：19 · 研究领域：Distributed Control Multi-Agent Systems、Robotic Path Planning Algorithms、Robotics and Sensor-Based Localization

This paper proposes a simple and uniform, decentralized approach to the problem of dispersing a team of robots to explore an area quickly. The Decentralized Space-Based Potential Field (D-SBPF) algorithm is a potential field approach that leverages knowledge of the overall bounds of the area to be explored. It includes a monotonic coverage factor in the potential field to avoid minima, realistic sensor bounds, and a distributed map exchange protocol. The D-SBPF approach yields a simple potential field control strategy for all robots but nonetheless has good dispersion and overlap performance in exploring areas with convex geometry while avoiding potential minima. Both simulation and robot experimental results are included as evidence, and performance, speedup and efficiency metrics for each are presented.