Efficient Strategy for Multi-UAV Path Planning in Target Coverage Problems

In recent years, multi unmanned aerial vehicles (UAVs) are used in the same system to accomplish more complex missions. In many multi-UAV system applications, the main objective is to visit some predetermined checkpoints in operational area. If the number of check points and constraints increases, finding a feasible solution takes up too much time. In this paper, a checkpoint based multi-UAV path planning problem is solved by using improved genetic algorithm. The main contributions of this paper are: (1) the introducing revisit time interval concept, (2) the investigating of the effect of objective function description, and (3) looking into an outcome of using multiple runways on optimal multi-UAV path planning. The proposed strategy-based optimization methodology is performed for checkpoint based multi-UAV path planning problems in two-dimensional (2D) environment. Performance results show that the proposed strategy provides effective and feasible paths for each UAV.