A distributed and integrated method for cooperative mission planning of multiple heterogeneous UAVs

Abstract

Purpose The purpose of this paper is to develop a distributed and integrated method to get a fast and feasible solution for cooperative mission planning of multiple heterogeneous unmanned aerial vehicles (UAVs). Design/methodology/approach In this study, the planning process is conducted in a distributed framework; the cooperative mission planning problem is reformulated with some specific constraints in the real mission; a distributed genetic algorithm is the algorithm proposed for searching for the optimal solution; genes of the chromosome are modified to adapt to the heterogeneous characteristic of UAVs; a fixed-wing UAV’s six degrees-of-freedom (DOF) model with a path following method is used to test the proposed mission planning method. Findings This method not only has the ability to obtain good feasible solutions but also improves the operating rate vastly. Research limitations/implications This study is only applied to the case where the communication among UAVs is linked during the mission. Practical implications This study is expected to be practical for a real mission because of its fast operating rate and good feasible solution. Originality/value This solution is tested on a fixed-wing UAV’s 6-DOF model by a path following method, so it is believable from the perspective of an autonomous UAV guidance and control system.