Path Planning for Messenger UAV in AGCS with Uncertainty Constraints

This paper mainly solves a path planning problem of messenger UAV in an air-ground collaborative system which is composed of a fixed-wing unmanned aerial vehicle (UAV) and multiple unmanned ground vehicles (UGVs). The UGVs play the role of mobile actuators, while the UAV serves as a messenger to achieve information sharing among the UGVs. The UAV needs to fly over each UGV periodically to collect the information and then transmit the information to the other UGVs. The path planning problem for the messenger UAV can be modeled as a Dynamic Dubins Traveling Salesman Problem with Neighborhood (DDTSPN). The goal of this problem is to find a shortest path which enables the UAV to access all the UGVs periodically. In the paper, we proposes a solution algorithm for the UAV’s path planning with uncertainty constraints which means the UAV doesn’t know the UGVs’ motion parameters. The algorithm is based on the idea of decoupling: firstly the sequence for the UAV to access the UGVs are determined by the genetic algorithm (GA), and then a reasonable prediction mechanism are proposed to determine the access locations of the UAV to the UGVs’ communication neighborhoods. Then the theoretical analysis of the effectiveness for the UAV’s path planning strategy is emphasized. At last, the effectiveness of the proposed approach is corroborated through computational experiments on several different scale instances.