Improved 3-D real-time trajectory planning algorithm for UAV
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摘要: 航迹规划对于战场环境中无人机完成其作战任务具有非常重要的意义.针对真实战场环境中低空无人机的三维航迹实时规划问题,构建了一个更加真实的战场威胁精简模型;提出遗传个体的基因优劣对比度,改进一种共享小生境遗传算法中编码基因的遗传特性.经过改进,增大优化基因的遗传概率,实现提高小生境遗传算法的全局优化能力和收敛速度,增强航迹规划的实时性.对三维数字地形空间进行定长网格编码,将改进的小生境遗传算法应用于三维虚拟战场环境中的无人机航迹规划,实验验证了改进算法的有效性,并能满足在线航迹规划的实时性要求.Abstract: It is of vital importance to plan trajectory for unmanned aircraft vehicle (UAV) completing missions in battlefield. A method to address the real-time problem of low-altitude UAV 3-D trajectory planning in realistic battlefield was proposed. Simplified threat models of battlefield were constructed, and an algorithm based on sharing niched genetic algorithm (NGA) was developed by defining the contrast of gene to change gene-s inheritance characteristic. The improvement made superior genes easy to transmit to the next generation, targeted to accelerate the NGA converging to the global optimum and improve real-time performance of NGA. The algorithm was used to 3-D trajectory planning for UAV in virtual battlefield environments while the 3-D digital terrain space was coded by gridding with constant interval. Experimental results show the effectiveness of the proposed algorithm, and prove it meets the real-time requirement of UAV trajectory planning on-line.
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Key words:
- unmanned aircraft vehicle /
- trajectories /
- planning /
- genetic algorithms
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[1] De la Cruz J M,Besada-Portas E,Torre-Cubillo L.Evolutionary path planner for UAVs in realistic environments //2008 Proceedings of the 10th annual conference on Genetic and evolutionary computation.Atlanta: ACM,2008:1477-1484 [2] Hennebry Michael,Jian Kuodi,Nygard Kendall E.Dynamic network refinement in automated aircraft route planning //IEEE EIT2007 Proceedings.Chicago: IEEE,2007:373-377 [3] Arunadevi J,Johnsanjeevkumar A,Sujatha N.Intelligent transport route planning using parallel genetic algorithms and MPI in high performance computing cluster //15th International Conference on Adanced Computing and Communications.Guwahati: IEEE,2007:578-583 [4] Nakamiya Masaki,Kishino yasue,Terada Tsutomu, et al.A route planning method using cost map for mobile sensor nodes //2nd International Symposium on Wireless Pervasive Computing.Sanjuan: IEEE,2007:169-174 [5] Sun Tsungying,Huo Chihli,Tsai Shangjeng, et al.Optimal UAV flight path planning using skeletonization and particle swarm optimizer //2008 IEEE Congress on Evolutionary Computation.Hongkong: IEEE,2008: 1183-1188 [6] 赵文婷.基于作战想定的无人机航迹规划与数据库设计 .北京:北京航空航天大学自动化科学与电气工程学院,2007 Zhao Wenting.Unmanned aerial vehicle flight path planning and database design based on war scenario .Beijing: School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,2007(in Chinese) [7] Admin.遗传算法小生境技术简介 .南昌:Admin,2006 .http://qbwh.com/viewthread_123913.html Admin.Brief introduction of niched genetic algorithm technology .Nanchang:Admin,2006 .http://qbwh.com/viewthread_123913.html(in Chinese) [8] Lup Laiwei,Srinivasan Dipti.A hybird evolutionary algorithm for dynamic route planning //2007 IEEE Congress on Evolutionary Computation.Singapore: IEEE,2007:4743-4749
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