旋翼无人机智能航迹规划研究综述
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摘要
无人机在军事和民用领域的广泛应用,使其成为全球范围的研究热点。智能航迹规划是旋翼无人机自主导航飞行的关键技术保障,有着重大的应用前景和研究意义。本文对旋翼无人机智能航迹规划进行了研究综述,在旋翼无人机航迹规划模型的基础上,分析了传统经典算法、现代智能算法等规划算法,指出了其优点与不足并讨论了智能算法的改进算法,最后展望了无人机智能航迹规划的发展趋势。
The wide application of UAV in military and civilian is a global research hotspot. Intelligent track planning is a key technology guarantee of the autonomous navigation of rotor unmanned aerial vehicle, which has significant application prospects and research significance. In this paper, the research on the intelligent track planning of rotorcraft UAV is reviewed.Based on the rotorcraft drone track planning model, the traditional classical algorithm, modern intelligent algorithm and other planning algorithms are analyzed, and the advantages and disadvantages are pointed out and the improved intelligence algorithms are discussed. Finally, the development trend of intelligent track planning for unmanned aerial vehicles is prospected.
The wide application of UAV in military and civilian is a global research hotspot. Intelligent track planning is a key technology guarantee of the autonomous navigation of rotor unmanned aerial vehicle, which has significant application prospects and research significance. In this paper, the research on the intelligent track planning of rotorcraft UAV is reviewed.Based on the rotorcraft drone track planning model, the traditional classical algorithm, modern intelligent algorithm and other planning algorithms are analyzed, and the advantages and disadvantages are pointed out and the improved intelligence algorithms are discussed. Finally, the development trend of intelligent track planning for unmanned aerial vehicles is prospected.
引文
[1]何小九,李彦彬,朱枫,等.国外垂直起降无人机发展现状及设计制造关键技术[J].飞航导弹,2016(6):22-27.
[2]贾阳阳.飞行器避障与航迹规划研究[D].北京:北京理工大学,2015.
[3]K.Y.CHEE,Z.W.ZHONG.Control,navigation and collision avoidance for an unmanned aerial vehicle[J].Sensors and Actuators A,2013(190):66-76.
[4]张煜,张万鹏,陈璟,等.基于Gauss伪谱法的UCAV对地攻击武器投放轨迹规划[J].航空学报,2011,32(7):1240-1251.
[5]白瑞光,孙鑫,陈秋双,等.基于Gauss伪谱法的多UAV协同航迹规划[J].宇航学报,2014,35(9):1022-1029.
[6]任耀庭.基于超声波测距与图像信息融合的旋翼无人机避障算法研究[D].成都:电子科技大学,2016.
[7]刘志宏,施工,胡永明.一种新的全局优化算法--统计归纳算法[J].清华大学学报(自然科学版),2002,42(5):580-583.
[8]LEWIS L P R.Rapid motion planning and autonomous obstacle avoidance for unmanned vehicles[D].Monterey:Naval Postgraduate School,2006.
[9]WILLIAMS P.Three-dimensional aircraft terrain-following via real-time optimal control[J].Journal of Guidance,Control,and Dynamics,2007,30(4):1201-1205.
[10]王维平,刘娟.无人飞行器航迹规划方法综述[J].飞行力学,2010,28(2):6-15.
[11]张瑜.电力巡检多旋翼无人机避障技术研究[D].成都:电子科技大学,2016.
[12]冯楠.自主移动机器人路径规划的RRT算法研究[D].大连:大连理工大学,2014.
[13]L KAVRAKI,J LATOMBE.Randomized Preprocessing of Configuration Space for Fast Path Planning[C].
[14]WILMARTH S,AMATO N,STILLER P.MAPRM:A probabilistic roadmap planner with sampling on the medial axis of the free space[C].IEEE International Conference on Robotics and Automation,1999:1024-1031.
[15]N AMATO,O BAYAZIT,L DALE,C Jones,D Vallejo.OBPRM:An obstacle-based PRM for 3D workspaces[C].Robotics:The algorithmic perspective,1998:155-168.
[16]陈家照,张中位,徐福后.改进的概率路径图法[J].计算机工程与应用,2009(10):54-55.
[17]张莹.动态规划算法综述[J].科技视界,2014(28):157-158.
[18]许云红,周锐,夏洁,等.无人机自动防撞冲突检测与优化控制方法[J].学术研究,2014(1):2-5.
[19]薛若宸.无人机飞行控制与航迹规划研究[D].北京:北京理工大学,2016.
[20]任波,周焘,于雷.基于改进A*算法的飞行器三维航迹规划算法[J].系统工程与电子技术,2008,30(2):324-326.
[21]刘莉,于成龙,王祝,等.小型无人机快速三维航迹规划算法[J].系统工程与电子技术,2013,35(12):2521-2526.
[22]周佳,蒋玉明.遗传算法和动态规划综述[J].技术研发,2009,16(12):18.
[23]辛贵州.无人飞行器航迹规划算法研究[D].哈尔滨:哈尔滨工程大学,2010.
[24]KENNEDY,J.,EBERHART,R.C.Particle swarm optimization[C].in Proceedings of IEEE International Conference on Neural Networks,1995:1942-1948.
[25]KENNEDY,J.F.,EBERHART,R.C.,SHI,Y.Swarm Intelligence[M].San Francisco:Morgan Kaufmann,2001.
[26]陈攀峰,刘文军,王为.基于粒子群算法的无人机航迹规划[J].电子设计工程,2013,21(22):36-39.
[27]傅阳光.粒子群优化算法的改进及其在航迹规划中的应用研究[D].武汉:华中科技大学,2011.
[28]李栋,曹义华,苏媛,等.基于改进蚁群算法的低空突防航迹规划[J].北京航空航天大学学报,2006,32(3),258-261.
[29]杨丹.蚁群算法的改进及其在航迹规划中的应用研究[D].哈尔滨:哈尔滨工业大学,2007.
[30]韩攀,陈谋,陈哨东,等.基于改进蚁群算法的无人机航迹规划[J].吉林大学学报,2013,31(1):66-72.
[31]任子玉.智能车自主避障路径规划研究综述[J].软件导刊,2017,16(10):209-212.
[32]何娟,涂中英,牛玉刚.一种遗传蚁群算法的机器人路径规划方法[J].计算机仿真,2010,27(3):170-174.
[33]李晋.基于蚁群算法和遗传算法的机器人路径规划研究[D].哈尔滨:哈尔滨工业大学,2012.
[34]张超,李擎,董冀媛,等.基于混沌粒子群-专用遗传算法切换策略的移动机器人路径规划[J].北京科技大学学报,2013(6):826-830.
[2]贾阳阳.飞行器避障与航迹规划研究[D].北京:北京理工大学,2015.
[3]K.Y.CHEE,Z.W.ZHONG.Control,navigation and collision avoidance for an unmanned aerial vehicle[J].Sensors and Actuators A,2013(190):66-76.
[4]张煜,张万鹏,陈璟,等.基于Gauss伪谱法的UCAV对地攻击武器投放轨迹规划[J].航空学报,2011,32(7):1240-1251.
[5]白瑞光,孙鑫,陈秋双,等.基于Gauss伪谱法的多UAV协同航迹规划[J].宇航学报,2014,35(9):1022-1029.
[6]任耀庭.基于超声波测距与图像信息融合的旋翼无人机避障算法研究[D].成都:电子科技大学,2016.
[7]刘志宏,施工,胡永明.一种新的全局优化算法--统计归纳算法[J].清华大学学报(自然科学版),2002,42(5):580-583.
[8]LEWIS L P R.Rapid motion planning and autonomous obstacle avoidance for unmanned vehicles[D].Monterey:Naval Postgraduate School,2006.
[9]WILLIAMS P.Three-dimensional aircraft terrain-following via real-time optimal control[J].Journal of Guidance,Control,and Dynamics,2007,30(4):1201-1205.
[10]王维平,刘娟.无人飞行器航迹规划方法综述[J].飞行力学,2010,28(2):6-15.
[11]张瑜.电力巡检多旋翼无人机避障技术研究[D].成都:电子科技大学,2016.
[12]冯楠.自主移动机器人路径规划的RRT算法研究[D].大连:大连理工大学,2014.
[13]L KAVRAKI,J LATOMBE.Randomized Preprocessing of Configuration Space for Fast Path Planning[C].
[14]WILMARTH S,AMATO N,STILLER P.MAPRM:A probabilistic roadmap planner with sampling on the medial axis of the free space[C].IEEE International Conference on Robotics and Automation,1999:1024-1031.
[15]N AMATO,O BAYAZIT,L DALE,C Jones,D Vallejo.OBPRM:An obstacle-based PRM for 3D workspaces[C].Robotics:The algorithmic perspective,1998:155-168.
[16]陈家照,张中位,徐福后.改进的概率路径图法[J].计算机工程与应用,2009(10):54-55.
[17]张莹.动态规划算法综述[J].科技视界,2014(28):157-158.
[18]许云红,周锐,夏洁,等.无人机自动防撞冲突检测与优化控制方法[J].学术研究,2014(1):2-5.
[19]薛若宸.无人机飞行控制与航迹规划研究[D].北京:北京理工大学,2016.
[20]任波,周焘,于雷.基于改进A*算法的飞行器三维航迹规划算法[J].系统工程与电子技术,2008,30(2):324-326.
[21]刘莉,于成龙,王祝,等.小型无人机快速三维航迹规划算法[J].系统工程与电子技术,2013,35(12):2521-2526.
[22]周佳,蒋玉明.遗传算法和动态规划综述[J].技术研发,2009,16(12):18.
[23]辛贵州.无人飞行器航迹规划算法研究[D].哈尔滨:哈尔滨工程大学,2010.
[24]KENNEDY,J.,EBERHART,R.C.Particle swarm optimization[C].in Proceedings of IEEE International Conference on Neural Networks,1995:1942-1948.
[25]KENNEDY,J.F.,EBERHART,R.C.,SHI,Y.Swarm Intelligence[M].San Francisco:Morgan Kaufmann,2001.
[26]陈攀峰,刘文军,王为.基于粒子群算法的无人机航迹规划[J].电子设计工程,2013,21(22):36-39.
[27]傅阳光.粒子群优化算法的改进及其在航迹规划中的应用研究[D].武汉:华中科技大学,2011.
[28]李栋,曹义华,苏媛,等.基于改进蚁群算法的低空突防航迹规划[J].北京航空航天大学学报,2006,32(3),258-261.
[29]杨丹.蚁群算法的改进及其在航迹规划中的应用研究[D].哈尔滨:哈尔滨工业大学,2007.
[30]韩攀,陈谋,陈哨东,等.基于改进蚁群算法的无人机航迹规划[J].吉林大学学报,2013,31(1):66-72.
[31]任子玉.智能车自主避障路径规划研究综述[J].软件导刊,2017,16(10):209-212.
[32]何娟,涂中英,牛玉刚.一种遗传蚁群算法的机器人路径规划方法[J].计算机仿真,2010,27(3):170-174.
[33]李晋.基于蚁群算法和遗传算法的机器人路径规划研究[D].哈尔滨:哈尔滨工业大学,2012.
[34]张超,李擎,董冀媛,等.基于混沌粒子群-专用遗传算法切换策略的移动机器人路径规划[J].北京科技大学学报,2013(6):826-830.