Wilderness Search and Rescue with Heterogeneous Multi-Robot Systems

Recent developments in autonomous and communication technologies led the use of cooperative aerial and ground vehicles in Wilderness Search and Rescue missions (WiSAR). The use of a heterogeneous Multi-Robot System (MRS) improves the robustness and efficiency in achieving these tasks, comparing to the homogeneous systems with vehicles of the same characteristics. From this point, this paper proposed a Multi-Robot Task Allocation (MRTA) algorithm for heterogeneous vehicles (UAVs and UGVs) using the Market-based Approach to optimize the mission resources. The algorithm checks the availability of the vehicles, the characteristics of each task, and the payload required as inputs, then it provides each vehicle with a plan of tasks and charging commands. The proposed algorithm has been validated by performing several missions in simulations of mountains terrain with real dimensions, and the obtained results show the robustness and efficiency of the proposed system.