Multirobot Target Searches in Unknown Environments Via Waypoint Planning System

Target searches by multiple robots in unknown environments have been widely applied in practical applications, such as rescues in hazardous areas, environmental monitoring, and locating leak sources. However, in existing methods, it is difficult to find all the information-lack targets in the unknown environment efficiently. To fill this gap, we propose a multirobot waypoint planning system consisting of an area decomposition-based local waypoint planner and a submap-based global waypoint planner. The local waypoint planner generates efficient coverage waypoints for every robot and accelerates the acquisition rate of global information. In contrast, the global planner optimizes the planning of waypoints using global information and prevents the multiple robots from duplicating searches. The proposed planning system benefits from the two planners by simultaneously guaranteeing a high coverage rate and searching efficiency in unknown environments. The effectiveness and advantages of the planning system are verified through both simulations and experimental results.