基于快速扩展随机树算法的多无人机编队重构方法研究
|
摘要
为适应瞬息万变的战场环境,发挥多无人机不同队形下的作战优势,以快速扩展随机树(RRT)算法为基础,提出一种多无人机编队重构的方法。首先建立多无人机编队的运动模型,分析传统RRT算法与编队重构方法结合的可行性,并采用多余节点去除和构造过渡航迹等策略对航迹进行修正。之后,重点分析重构过程中的动力学及防碰撞等约束,为随机树的扩展和无人机的航迹变换提供依据。最后通过对比仿真和飞行试验,验证所提重构方法的安全性和可行性。结果表明,该重构方法能在复杂环境下快速实现编队重构,同时所规划的航迹利于无人机进行跟踪,可满足实际战场的飞行需求。
To adapt the complexity and flexibility of battlefield environment, a method of formation reconfiguration based on Rapidly-exploring Random Tree(RRT) algorithm is proposed, which shows the advantage of formation of Unmanned Aerial Vehicles(UAVs). Firstly, the kinematic model for UAVs is built, and the feasibility of combination of traditional RRT algorithm and formation reconfiguration of UAVs is analyzed. Secondly, the strategies of trajectory correction comprising node removal and transition trajectory are adopted. Then the dynamic and collision avoidance constraints are discussed respectively, which are essential for exploring the process of RRT algorithm as well as adjusting the trajectory of UAVs. Finally, the simulation and flight experiment are carried out to verify the effectiveness of the proposed method. The results show that the reconfiguration method is able to achieve the formation reconfiguration rapidly and safely. Moreove, the planed trajectory can satisfy the tracing requirement, which is of significance for flight of UAVs in the battlefield environment.
To adapt the complexity and flexibility of battlefield environment, a method of formation reconfiguration based on Rapidly-exploring Random Tree(RRT) algorithm is proposed, which shows the advantage of formation of Unmanned Aerial Vehicles(UAVs). Firstly, the kinematic model for UAVs is built, and the feasibility of combination of traditional RRT algorithm and formation reconfiguration of UAVs is analyzed. Secondly, the strategies of trajectory correction comprising node removal and transition trajectory are adopted. Then the dynamic and collision avoidance constraints are discussed respectively, which are essential for exploring the process of RRT algorithm as well as adjusting the trajectory of UAVs. Finally, the simulation and flight experiment are carried out to verify the effectiveness of the proposed method. The results show that the reconfiguration method is able to achieve the formation reconfiguration rapidly and safely. Moreove, the planed trajectory can satisfy the tracing requirement, which is of significance for flight of UAVs in the battlefield environment.
引文
[1] 李文皓,张珩.无人机编队飞行技术的研究现状与展望[J].飞行力学,2007,25(1):9-11LI Wenhao,ZHANG Heng.Reviews on Unmanned Aerial Vehicle from ation-Flight[J].Flight Dynamics,2007,25(1):9-11 (in Chinese)
[2] 潘华,毛海涛.无人机编队飞行面临问题及关键技术研究[J].现代电子技术,2014,37(16):77-79PAN Hua,MAO Haitao.Study on Problems Facing with UAV Formation Flight and Its Key Technology[J].Modern Electronics Technique,2014,37(16):77-79 (in Chinese)
[3] 宗群,王丹丹,邵士凯,等.多无人机协同编队飞行控制研究现状及发展[J].哈尔滨工业大学学报,2017,49(3):1-14ZONG Qun,WAN Dandan,SHAO Shikai,et al.Research Status and Development of Multi UAV Coordinated Formation Flight Control[J].Journal of Harbin Institute of Technology,2017,49(3):1-14 (in Chinese)
[4] MASOUD A A.Kinodynamic Motion Planning[J].Robotics and Automation,2010,17(1):85-99
[5] KIM S H,BHATTACHARYA R.Motion Planning in Obstacle Rich Environments[J].Journal of Aerospace Computing,Information,and Communication,2009(6):433-450
[6] LI Yue,CHEN Qingyang,HOU Zhongxi.Research on UAVs Formation Reconfiguration Based on Dubins Path[C]//Proceedings of 2016 IEEE Chinese Guidance,Navigation and Control Conference,2016:2745-2750
[7] HUMI M A,SEKHAVA P,ROSS I M.Autonomous Path Planning Using Real-time Inforrnation Updates[C]//AIAA Guidance,Navigation and Control Conference and Exhibit,2007
[8] LAVALLE S M.Rapidly-Exploring Random Trees:a New Tool for Path Planning[D].Ames,Iowa State University,1998
[9] 尹高扬,周绍磊,吴青坡.无人机快速三维航迹规划算法[J].西北工业大学学报,2016,34(4):563-569YIN Gaoyang,ZHOU Shaolei,WU Qingpo.Efficient Path Planning Algorithm in Three Dimensions for UAV[J].Journal of Northwestern Polytechnical University,2016,34(4):563-569 (in Chinese)
[10] 林娜,张亚伦.自适应RRT无人机航路规划算法研究与仿真[J].计算机仿真,2015,32(1):73-77LIN Na,ZHANG Yalun.Research and Simulation on Adaptive RRT Algorithm for UAVs Path Planning[J].Computer Simulation,2015,32(1):73-77 (in Chinese)
[11] BARES P,LAZARUSY S,TSOURDOSZ A,et al.Adaptive Guidance for UAV Based on Dubins Path[C]//AIAA Guidance,Navigation,and Control Conference,2013
[12] LEE H,LEE D,SHIM D H.Receding Horizon-Based RRT Algorithm for a UAV Realtime[C]//AIAA Sci Tech Forum Grapevine,2017
[13] SUN C C,LIU Y C,DAI R.Two Approaches for Path Planning of Unmanned Aerial Vehicles with Avoidance Zones[J].Journal of Guidance,Control,and Dynamics,2017,40(8):2076-2083
[14] FARINELL J,LAY C,BHANDARI S.UAV Collision Avoidance Using a Predictive Rapidly-Exploring Random Tree[C]//AIAA Sci Tech Forum Grapevine,2016
[15] 田晓亮.无人机路径规划方法研究[D].西安:西安电子科技大学,2014:46-53TIAN Xiaoliang.Study on Unmanned Aerial Vehicle path planning[D].Xi′an,Xidian University,2014:46-53 (in Chinese)
[16] 欧超杰.多无人机编队控制技术研究[D].南京:南京航空航天大学,2015:20-21OU Chaojie.UAVs Formation Flight Control[D].Nanjing,Nanjing University of Aeronautics and Astronautics,2015:20-21 (in Chinese)
[17] 李猛.基于智能优化与RRT算法的无人机任务规划方法研究[D].南京:南京航空航天大学,2012:63-87LI Meng.Research on UAV Mission Planning Methods Based on Intelligent Optimization and RRT Algorithm[D].Nanjing,Nanjing University of Aeronautics and Astronautics,2012:63-87 (in Chinese)
[18] CARDENAS I L,FLORES G,SALAZA S.Dubins Path Generation for a Fixed Wing UAV[C]//Proceedings of 2014 International Conference on Unmanned Aircraft Systems,Orlando,2014:339-346
[19] 李樾,陈清阳,侯中喜.自适应引导长度的无人机航迹跟踪方法[J].北航学报,2017,43(7):1481-1489LI Yue,CHEN Qingyang,HOU Zhongxi.Path Following Method with Adaptive Guidance Length for Unmanned Aerial Vehicles[J].Journal of Beijing University of Aeronautics and Astronautics,2017,43(7):1481-1489 (in Chinese)
[20] 孙小雷,孟宇麟,齐乃明,等.多无人机交会过程的协同航迹规划方法[J].机器人,2015,37(5):621-627SUN Xiaolei,MENG Yulin,QI Naiming,et al.Cooperative Path Planning for Rendezvous of Unmanned Aerial Vehicles[J].Robot,2015,37(5):621-627 (in Chinese)
[21] MCCOURT M J,TON C T,MEHTA S S,et al.Adaptive Step-Length RRT Algorithm for Improved Coverage[C]//AIAA Guidance,Navigation,and Control Conference,2016
[22] PATTERSON M A,RAO A V.GPOPS-Ⅱ:A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using Hp-Adptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming[J].ACM Transactions on Mathematical Software,2014,41(1):1-37
[2] 潘华,毛海涛.无人机编队飞行面临问题及关键技术研究[J].现代电子技术,2014,37(16):77-79PAN Hua,MAO Haitao.Study on Problems Facing with UAV Formation Flight and Its Key Technology[J].Modern Electronics Technique,2014,37(16):77-79 (in Chinese)
[3] 宗群,王丹丹,邵士凯,等.多无人机协同编队飞行控制研究现状及发展[J].哈尔滨工业大学学报,2017,49(3):1-14ZONG Qun,WAN Dandan,SHAO Shikai,et al.Research Status and Development of Multi UAV Coordinated Formation Flight Control[J].Journal of Harbin Institute of Technology,2017,49(3):1-14 (in Chinese)
[4] MASOUD A A.Kinodynamic Motion Planning[J].Robotics and Automation,2010,17(1):85-99
[5] KIM S H,BHATTACHARYA R.Motion Planning in Obstacle Rich Environments[J].Journal of Aerospace Computing,Information,and Communication,2009(6):433-450
[6] LI Yue,CHEN Qingyang,HOU Zhongxi.Research on UAVs Formation Reconfiguration Based on Dubins Path[C]//Proceedings of 2016 IEEE Chinese Guidance,Navigation and Control Conference,2016:2745-2750
[7] HUMI M A,SEKHAVA P,ROSS I M.Autonomous Path Planning Using Real-time Inforrnation Updates[C]//AIAA Guidance,Navigation and Control Conference and Exhibit,2007
[8] LAVALLE S M.Rapidly-Exploring Random Trees:a New Tool for Path Planning[D].Ames,Iowa State University,1998
[9] 尹高扬,周绍磊,吴青坡.无人机快速三维航迹规划算法[J].西北工业大学学报,2016,34(4):563-569YIN Gaoyang,ZHOU Shaolei,WU Qingpo.Efficient Path Planning Algorithm in Three Dimensions for UAV[J].Journal of Northwestern Polytechnical University,2016,34(4):563-569 (in Chinese)
[10] 林娜,张亚伦.自适应RRT无人机航路规划算法研究与仿真[J].计算机仿真,2015,32(1):73-77LIN Na,ZHANG Yalun.Research and Simulation on Adaptive RRT Algorithm for UAVs Path Planning[J].Computer Simulation,2015,32(1):73-77 (in Chinese)
[11] BARES P,LAZARUSY S,TSOURDOSZ A,et al.Adaptive Guidance for UAV Based on Dubins Path[C]//AIAA Guidance,Navigation,and Control Conference,2013
[12] LEE H,LEE D,SHIM D H.Receding Horizon-Based RRT Algorithm for a UAV Realtime[C]//AIAA Sci Tech Forum Grapevine,2017
[13] SUN C C,LIU Y C,DAI R.Two Approaches for Path Planning of Unmanned Aerial Vehicles with Avoidance Zones[J].Journal of Guidance,Control,and Dynamics,2017,40(8):2076-2083
[14] FARINELL J,LAY C,BHANDARI S.UAV Collision Avoidance Using a Predictive Rapidly-Exploring Random Tree[C]//AIAA Sci Tech Forum Grapevine,2016
[15] 田晓亮.无人机路径规划方法研究[D].西安:西安电子科技大学,2014:46-53TIAN Xiaoliang.Study on Unmanned Aerial Vehicle path planning[D].Xi′an,Xidian University,2014:46-53 (in Chinese)
[16] 欧超杰.多无人机编队控制技术研究[D].南京:南京航空航天大学,2015:20-21OU Chaojie.UAVs Formation Flight Control[D].Nanjing,Nanjing University of Aeronautics and Astronautics,2015:20-21 (in Chinese)
[17] 李猛.基于智能优化与RRT算法的无人机任务规划方法研究[D].南京:南京航空航天大学,2012:63-87LI Meng.Research on UAV Mission Planning Methods Based on Intelligent Optimization and RRT Algorithm[D].Nanjing,Nanjing University of Aeronautics and Astronautics,2012:63-87 (in Chinese)
[18] CARDENAS I L,FLORES G,SALAZA S.Dubins Path Generation for a Fixed Wing UAV[C]//Proceedings of 2014 International Conference on Unmanned Aircraft Systems,Orlando,2014:339-346
[19] 李樾,陈清阳,侯中喜.自适应引导长度的无人机航迹跟踪方法[J].北航学报,2017,43(7):1481-1489LI Yue,CHEN Qingyang,HOU Zhongxi.Path Following Method with Adaptive Guidance Length for Unmanned Aerial Vehicles[J].Journal of Beijing University of Aeronautics and Astronautics,2017,43(7):1481-1489 (in Chinese)
[20] 孙小雷,孟宇麟,齐乃明,等.多无人机交会过程的协同航迹规划方法[J].机器人,2015,37(5):621-627SUN Xiaolei,MENG Yulin,QI Naiming,et al.Cooperative Path Planning for Rendezvous of Unmanned Aerial Vehicles[J].Robot,2015,37(5):621-627 (in Chinese)
[21] MCCOURT M J,TON C T,MEHTA S S,et al.Adaptive Step-Length RRT Algorithm for Improved Coverage[C]//AIAA Guidance,Navigation,and Control Conference,2016
[22] PATTERSON M A,RAO A V.GPOPS-Ⅱ:A MATLAB Software for Solving Multiple-Phase Optimal Control Problems Using Hp-Adptive Gaussian Quadrature Collocation Methods and Sparse Nonlinear Programming[J].ACM Transactions on Mathematical Software,2014,41(1):1-37