具有持续侦察时间约束的协同航路规划

摘要: 为获得目标有效信息，无人机（UAVs）执行侦察任务时针对不同目标所需的持续侦察时间存在一定的差异。本文假设无人机在目标持续侦察过程中保持定直平飞以确保有效侦察，针对至多3个侦察任务重叠的情况，通过几何分析，提出了存在侦察任务重叠情况下的多侦察任务同时侦察方法。在考虑侦察任务重叠和多机协同侦察的同时，以最小化侦察路径长度为性能指标，相邻侦察点间采用Dubins曲线进行航路规划，利用引入精英机制的混合粒子群优化算法实现侦察任务序列优化，实现具有持续侦察时间约束的协同航路规划。仿真结果表明提出算法的有效性。
- 无人机 /
- 侦察任务重叠 /
- 协同航路规划 /
- 精英机制 /
- 混合粒子群优化算法
Abstract: When performing reconnaissance tasks, unmanned aerial vehicles (UAVs) keep reconnoitering the targets during different reconnaissance time for acquiring effective target information. It is assumed that UAVs fly in a straight line, which is suitable for better reconnaissance results during reconnaissance missions. A new simultaneous reconnaissance scheme was proposed by geometrical analysis for less than or equal to three reconnaissance mission overlapping. For the purpose of minimizing cooperative reconnaissance path length, modified hybrid particle swarm optimization algorithm with elitism mechanism was used to optimize the reconnaissance sequence, and the path planning was implemented between consecutive reconnaissance missions by Dubins path, with consideration of reconnaissance missions overlapping and reconnaissance duration time constraints. Simulation results demonstrate the effectiveness of the proposed method.
- unmanned aerial vehicle /
- reconnaissance missions overlapping /
- cooperative path planning /
- elitism mechanism /
- hybrid particle swarm optimization algorithm

HTML全文

参考文献(21)

[1]	YANG K,KANG Y,SUKKARIEH S.Adaptive nonlinear model predictive path-following control for a fixed-wing unmanned aerial vehicle[J].International Journal of Control Automation & Systems,2013,11(1):65-74.
[2]	CETIN O,ZAGLI I.Continuous airborne communication relay approach using unmanned aerial vehicles[J].Journal of Intelligent & Robotic Systems,2012,65(1-4):549-562.
[3]	GENG L,ZHANG Y F,WANG P F,et al.UAV surveillance mission planning with gimbaled sensors[C]// Control & Automation (ICCA).Piscataway,NJ:IEEE Press,2014:320-325.
[4]	OBERMEYER K J.Path planning for a UAV performing reconnaissance of static ground targets in terrain[C]//AIAA Guidance,Navigation,and Control Conference and Exhibit.Reston:AIAA,2009.
[5]	田菁,沈林成.多基地多无人机协同侦察问题研究[J].航空学报,2007,28(4):913-921.TIAN J,SHEN L C.Research on multi-base multi-UAV cooperative reconnaissance problem[J].Acta Aeronautica et Astronautica Sinica,2007,28(4):913-921(in Chinese).
[6]	李响,邢清华,董涛.无人机编队协同侦察效能研究[J].火力与指挥控制,2013,38(10):103-110.LI X,XING Q H,DONG T.Research on cooperative reconnaissance effectiveness of UAV formation[J].Fire Control & Command Control,2013,38(10):103-110(in Chinese).
[7]	OBERMEYER K J,OBERLIN P,DARBHA S.Sampling-based path planning for a visual reconnaissance unmanned air vehicle[J].Journal of Guidance,Control,and Dynamics,2012,35(2):619-631.
[8]	王剑文,戴光明,谢柏桥,等.求解TSP问题算法综述[J].计算机工程与科学,2008,30(2):72-74.WANG J W,DAI G M,XIE B Q,et al.A survey of solving the traveling salesman problem[J].Computer Engineering & Science,2008,30(2):72-74(in Chinese).
[9]	宗德才,王康康,丁勇.蚁群算法求解旅行商问题综述[J].计算机与数字工程,2014,42(11):2004-2013.ZONG D C,WANG K K,DING Y.Review of ant colony algorithm for solving traveling salesman problem[J].Computer & Digital Engineering,2014,42(11):2004-2013(in Chinese).
[10]	黄岚,王康平,周春光,等.粒子群优化算法求解旅行商问题[J].吉林大学学报(理学版),2003,41(4):477-480.HUANG L,WANG K P,ZHOU C G,et al.Particle swarm optimization for traveling salesman problems[J]. Journal of Jilin University(Science Edition),2003,41(4):477-480(in Chinese).
[11]	于莹莹,陈燕,李桃迎.改进的遗传算法求解旅行商问题[J].控制与决策,2014,29(8):1483-1488.YU Y Y,CHEN Y,LI T Y.Improved genetic algorithm for solving TSP[J].Control and Decision,2014,29(8):1483-1488(in Chinese).
[12]	杜占玮,杨永健,孙永雄,等.基于互信息的混合蚁群算法及其在旅行商问题上的应用[J].东南大学学报(自然科学版),2011,41(3):478-481.DU Z W,YANG Y J,SUN Y X,et al.Hybrid ant colony algorithm based on mutual information and its application to traveling salesman problem[J].Journal of Southeast University(Natural Science Edition),2011,41(3):478-481(in Chinese).
[13]	YU Q S,WANG D,LIN D M,et al.A novel two-level hybrid algorithm for multiple traveling salesman problems[C]// 3rd International Conference on Swarm Intelligence,ICSI 2012.Heidelberg: Springer Verlag,2012:497-503..
[14]	LEVIN A,YOVEl U.Local search algorithms for multiple-depot vehicle routing and for multiple traveling salesman problems with proved performance guarantees[J].Journal of Combinatorial Optimization,2014,28(4):726-747.
[15]	DUBINS L E.On curves of minimal length with a constraint on average curvature,and with prescribed initial and terminal positions and tangents[J].American Journal of Mathematics,1957,79(3):497-516.
[16]	MEYER Y,ISAIAH P,SHIMA T.On Dubins paths to intercept a moving target[J].Automatica,2015,53:256-263.
[17]	BHATIA A,FRAZZOLI E.Decentralized algorithm for minimum-time rendezvous of Dubins vehicles[C]//American Control Conference.Piscataway:IEEE Press,2008:1343-1349.
[18]	WANG Z,LI Y.A target visiting path planning algorithm for the fixed-wing UAV in obstacle environment[C]//6th IEEE Chinese Guidance,Navigation and Control Conference,CGNCC 2014.Piscataway:IEEE Press,2014:2774-2778.
[19]	史峰.MATLAB智能算法30个案例分析[M].北京:北京航空航天大学出版社,2011:144-149.SHI F.Analysis of intelligent algorithm in 30 MATLAB cases[M].Beijing:Beihang University Press,2011:144-149(in Chinese).
[20]	SEGUI-GASCO P,SHIN H S,TSOURDOS A,et al.A combinatorial auction framework for decentralised task allocation[C]// 2014 IEEE Globecom Workshops,GC Wkshps 2014.Piscataway,NJ:IEEE Press,2014:1445-1450.
[21]	CHEN P H.Two-level hierarchical approach to unit commitment using expert system and elite PSO[J].IEEE Transactions on Power Systems,2012,27(2):780-789.