Please wait a minute...
浙江大学学报(工学版)  2018, Vol. 52 Issue (7): 1398-1405    DOI: 10.3785/j.issn.1008-973X.2018.07.021
丁强, 陶伟明
浙江大学 航空航天学院, 浙江 杭州 310027
Improved Tau-H strategy for four-dimensional cooperative route planning of multi-UAVs
DING Qiang, TAO Wei-ming
School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China
 全文: PDF(1678 KB)   HTML



An improved Tau-H strategy was proposed for route planning and optimization of multiple unmanned aerial vehicles (UAVs) flight cooperation to satisfy various constraints. The improved Tau-H strategy overcame the original shortcomings of common-used Tau-H motion strategy by introducing the correlative term of initial velocity into the motion formula, which was only applicable to problems with initial and ending velocity of zero. Then the strategy can be employed to plan four-dimensional (4D) motion of UAVs with nonzero initial and ending velocity to match the arrival time and velocity. Global trajectories were generated by using particle swarm optimization (PSO) algorithm to search the initial coupling coefficient of UAVs. Then the trajectories were constantly updated by solving the local planning problem by the rolling optimization method with double drive of sampling interval and collision detection based on the established communication topology among UAVs. Simulation results of several examples indicate that the improved Tau-H strategy based method can satisfy relevant application requirements for receiving the continuous 4D cooperative route planning and optimization of multi-UAVs with great flight capability and high flight safety.

收稿日期: 2017-11-21 出版日期: 2018-06-26
CLC:  V249  


通讯作者: 陶伟明,男,教授     E-mail:
作者简介: 丁强(1993-),男,硕士生,从事无人机航迹规划方法研究
E-mail Alert


丁强, 陶伟明. 多无人机协同四维航迹规划的改进的Tau-H策略[J]. 浙江大学学报(工学版), 2018, 52(7): 1398-1405.

DING Qiang, TAO Wei-ming. Improved Tau-H strategy for four-dimensional cooperative route planning of multi-UAVs. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(7): 1398-1405.


[1] RADMANESH M, KUMAR M. Flight formation of UAVs in presence of moving obstacles using fast-dynamic mixed integer linear programming[J]. Aerospace Science and Technology, 2016, 50:149-160.
[2] 肖刘. 基于多智能体的多无人机编队算法[J]. 航空电子技术, 2014, 45(2):4-7. XIAO Liu. Multiple uav formation arithmetic based on multi-agent[J]. Avionics Technology, 2014, 45(2):4-7.
[3] TANG X M, HAN Y X. 4D trajectory estimation for air traffic control automation system based on hybrid system theory[J].Promet-Traffic and Transportation, 2012, 24(2):91-98.
[4] SUPATCHA C, DANIEL D, MARCEL M. A hybrid metaheuristic optimization algorithm for strategic planning of 4D aircraft trajectories at the continental scale[J]. Computational Intelligence Magazine, 2014, 9(4):46-61.
[5] WU P P, CAMPBELL D, MERZ T. Multi-objective four-dimensional vehicle motion planning in large dynamic environments[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B:Cyberbetics, 2011, 41(3):621-634.
[6] 杨祖强. 生物启发的多无人机协同四维航迹规划方法研究[D].杭州:浙江大学,2016. YANG Zu-qiang. Bio-inspired 4D trajectory generation for multi-uav cooperation[D]. Hangzhou:Zhejiang University, 2016.
[7] MOON S, OH E, SHIM D H. An integral framework of task assignment and path planning for multiple unmanned aerial vehicles in dynamic environments[J]. Journal of Intelligent and Robotic Systems, 2013, 70(1-4):303-313.
[8] BARRIENTOS A, GUTIERREZ P, COLORADO J. Advanced uav trajectory generation:planning and guidance[M]//Aerial Vehicles.:in-tech, 2009.
[9] BERRY A J, HOWITT J, GU D W. A continuous local motion planning framework for unmanned vehicles in complex environments[J]. Journal of Intelligent and Robotic Systems, 2012, 66(4):477-494.
[10] LEE D N. A theory of visual control of braking based on information about time-to-collision[J]. Perception, 1976, 5(4):437-459.
[11] 冯建立,张宏杰.运动技能操作的知觉理论辨析-基于间接知觉和直接知觉理论[J].成都体育学院学报, 2013, 39(2):15-19. FENG Jian-li, ZHANG Hong-jie.Analysis on the perception theory of sports skill operation-based on indirect perception and direct perception theory[J]. Journal of Chengdu Sport University, 2013, 39(2):15-19.
[12] LEE D N, MARK N D, PATRICK R G. Visual control of velocity of approach by pigeons when landing[J].Journal of Experimental Biology, 1993, 180(1):85-104.
[13] LEE D N. General tau theory:evolution to date[J]. Perception, 2009, 38(6):837-858.
[14] SCHOGLER B, PEPPING G J, LEE D N. Tau-G guidance of transients in expressive musical performance[J]. Experimental Brain Research, 2008, 189(3):361-372.
[15] YANG Zhu-qiang, FANG Zhou, LI Ping. Bio-inspired collision-free 4D trajectory generation for uavs using tau strategy[J]. Journal of Bionic Engineering, 2016, 13(1):84-97.
[16] 张书涛, 张震, 钱晋武. 基于Tau理论的机器人抓取运动仿真轨迹规划[J].机械工程学报,2014, 50(13):42-51. ZHANG Shu-tao, ZHANG Zhen, QIAN Jin-wu. Bio inspired trajectory planning for robot catching movements based on the tau theory[J]. Journal of Mechanical Engineering, 2014, 50(13):42-51.
[17] ZHANG Z, ZHANG S T, XIE P, et al. Bioinspired 4D trajectory generation for a UAS rapid point-to-point movement[J]. Journal of Bionic Engineering, 2014, 11(1):72-81.
[18] ALEJO D, COBANO J A, HEREDIA G, et al. Particle swarm optimization for collision-free 4D planning in unmanned aerial vehicles[C]//International Conference on Unmanned Aircraft Systems. Piscataway:IEEE, 2013:298-307.
[19] ALEJO D, COBANO J A, HEREDIA G, et al. Collsion-free 4D trajectory planning in unmanned aerial vehicles for assembly and structure construction[J]. Journal of Intelligent and Systems, 2014, 73(1-4):783-795.

[1] 胡淼淼, 敬忠良, 董鹏, 周贵荣, 郑智明. 基于T分布变分贝叶斯滤波的SINS/GPS组合导航[J]. 浙江大学学报(工学版), 2018, 52(8): 1482-1488.
[2] 侯鑫, 李平, 韩波, 等. 小型无人直升机分层混杂控制系统[J]. J4, 2009, 43(5): 796-800.