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

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Vydáno v:Defence Technology vol. 45 (2025), p. 203
Hlavní autor: Wang, Xinwei
Další autoři: Gao, Xiaohua, Wang, Lei, Su, Xichao, Jin, Junhong, Liu, Xuanbo, Deng, Zhilong
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KeAi Publishing Communications Ltd
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024 7 |a 10.1016/j.dt.2024.08.002  |2 doi 
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045 2 |b d20250101  |b d20251231 
100 1 |a Wang, Xinwei  |u 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 
245 1 |a Resilient multi-objective mission planning for UAV formation: A unified framework integrating task pre- and re-assignment 
260 |b KeAi Publishing Communications Ltd  |c 2025 
513 |a Journal Article 
520 3 |a 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. 
653 |a Genetic algorithms 
653 |a Operators (mathematics) 
653 |a Unmanned aerial vehicles 
653 |a Assignment problem 
653 |a Planning 
653 |a Reliability 
653 |a Mission planning 
653 |a Optimization 
653 |a Linear programming 
653 |a Modules 
653 |a Multiple objective analysis 
653 |a Animation 
653 |a Real time 
653 |a Traveling salesman problem 
653 |a Optimization models 
653 |a Schedules 
700 1 |a Gao, Xiaohua  |u School of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, Anhui 232001, China 
700 1 |a Wang, Lei  |u School of Mathematical Science, Dalian University of Technology, Dalian, Liaoning 116024, China 
700 1 |a Su, Xichao  |u Department of Airborne Vehicle Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China 
700 1 |a Jin, Junhong  |u School of Mathematical Science, Dalian University of Technology, Dalian, Liaoning 116024, China 
700 1 |a Liu, Xuanbo 
700 1 |a Deng, Zhilong 
773 0 |t Defence Technology  |g vol. 45 (2025), p. 203 
786 0 |d ProQuest  |t Military Database 
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