Resilient multi-objective mission planning for UAV formation:A unified framework integrating task pre-and re-assignment  

作　　者：Xinwei Wang Xiaohua Gao Lei Wang Xichao Su Junhong Jin Xuanbo Liu Zhilong Deng 

机构地区：[1]Department of Engineering Mechanics,State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment,Dalian University of Technology,Dalian,Liaoning 116024,China [2]School of Mathematics and Big Data,Anhui University of Science and Technology,Huainan,Anhui 232001,China [3]School of Mathematical Science,Dalian University of Technology,Dalian,Liaoning 116024,China [4]Department of Airborne Vehicle Engineering,Naval Aeronautical and Astronautical University,Yantai 264001,China

出　　处：《Defence Technology(防务技术)》2025年第3期203-226,共24页Defence Technology

基　　金：supported by the National Key Research and Development Plan(Grant No.2021YFB3302501);the National Natural Science Foundation of China(Grant Nos.12102077,12161076,U2241263).

摘　　要：Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution reliability.During the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be executed.To improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this paper.In the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization model.And an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient solution.As in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency scenario.And the dual objective used in the former phase is adapted into a single objective to keep a consistent combat intention.Three cases of different scales demonstrate that the two modules cooperate well with each other.On the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is introduced.On the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a millisecond.The corresponding animation is accessible at bilibili.com/video/BV12t421w7EE for better illustration.

关 键 词：Cooperative mission planning UAV formation Mission reliability Evolutionary algorithm Contract net protocol 

分 类 号：G63[文化科学—教育学]