Coordinated Informative Path Planning for Multi-Robot Search in Open Fields

Abstract

This study proposes an informative path planning algorithm for executing search missions cooperatively utilizing a multi-robot system, leading to a faster search over extensive areas such as oceans and large open fields. To facilitate efficient cooperative searching, we introduce a search area division algorithm based on the weighted Voronoi diagram and a coverage path planner inspired by the traveling salesman problem. Two key technical issues in cooperative search missions are efficient area coverage and accurate target localization, which involve a trade-off between exploration and exploitation. To address this trade-off issue, we present an algorithm that promotes active collaboration among the robots by leveraging the Fisher information matrix to optimize robot configurations and by employing a market-based strategy for effective compromise. The effectiveness of the proposed approach is demonstrated through simulation results.