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

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.