Maximizing Search Coverage Using Future Path Projection for Cooperative Multiple UAVs with Limited Communication Ranges

Abstract

In this chapter, we present Future Path Projection (FPP) as a novel method for multiple Unmanned Aerial Vehicles (UAVs) with limited communication ranges to cooperatively maximize the coverage of a large search area. For multiple cooperative UAVs to perform an effective search mission, the critical status and sensor information collected by each UAV must be shared with all other UAVs in the group. In an ideal environment where there is no communication limitation, all involved UAVs can share the necessary information without any constraints. In a more realistic environment, UAVs must deal with limited communication ranges. The communication range limitation, however, introduces a challenging problem for multiple UAVs to effectively cooperate. In the proposed method, each UAV constructs an individual probability distribution map of the search space which reflects predictions of the future paths of UAVs as they move beyond their communication ranges. The probability distribution map describes the likelihood of detecting targets within the search space. The overall, collective UAV search patterns are governed by decisions made by each UAV within the group, based on each individual probability distribution map. We show that the collective search patterns generated by cooperative UAVs using the proposed method significantly improve the search area coverage when compared to similar search patterns produced by other mitigation strategies designed to overcome the communication range limitation. We validate the effectiveness of the proposed path projection method using simulation results.