基于队形变化的多无人机航迹规划算法

doi:10.16180/j.cnki.issn1007-7820.2023.07.006

Abstract

Abstract:

In view of the problem of trajectory planning of multiple UAVs in complex environments, a multi-UAV trajectory planning algorithm based on formation changes is proposed. Based on the topology of pilot-following UAV, a cost function with time and range as the metrics is designed to solve the optimal formation rendezvous point. The improved Informed-RRT* algorithm is used to solve the asymptotic optimal track of the leader, and the track planning and obstacle avoidance of the follower is realized by combining the formation change strategy. On the basis of defining formation variation, path length ratio, and heading stability performance indicators, simulation experiments are carried out and the generated tracks are evaluated and compared. The simulation results show that the UAV formation can achieve trajectory planning and obstacle avoidance in complex environments, and at the same time plan the optimal trajectory planning for the follower, which is less than 1% away from the optimal trajectory length of the leader, which improves the practicality and effectiveness of the algorithm.

Key words: UAV formation, leader-following method, informed-RRT*, formation assembly, path planning, formation change, optimal track, obstacle avoidance

CLC Number:

TP242

WANG Yangbin,ZHANG Wei,HU Zhi. Multi-UAV Path Planning Algorithm Based on Formation Change[J].Electronic Science and Technology, 2023, 36(7): 39-48.

Figures/Tables 13

Figure 1.

Table 1.

Table of formation change"

飞行阶段	领航者位置	队形参数矩阵
0	$V L 0$	$F 2 d$
1	$V L 1$	$F 1 d$
?	?	?
n	V_Ln	$F n d$

Table 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Table 2.

Figure 9.

Figure 10.

Figure 11.

References 18

[1]	夏令儒, 孙首群. 多无人机协同任务规划[J]. 电子科技, 2018, 31(1):4-8.
	Xia Lingru, Sun Shouqun. Planning route for UAV cooperative combat[J]. Electronic Science and Technology, 2018, 31(1):4-8.
[2]	韩晓微, 韩震, 岳高峰, 等. 救灾无人机的优化A*航迹规划算法[J]. 计算机工程与应用, 2021, 57(6):232-238. doi: 10.3778/j.issn.1002-8331.1912-0304
	Han Xiaowei, Han Zhen, Yue Gaofeng, et al. Path planning algorithm of disaster relief UAV based on optimized A*[J]. Computer Engineering and Applications, 2021, 57(6):232-238. doi: 10.3778/j.issn.1002-8331.1912-0304
[3]	陈昊, 沈景凤, 赵程. 无人机在抢险救灾中的优化应用[J]. 电子科技, 2019, 32(9):20-25.
	Chen Hao, Shen Jinfeng, Zhao Cheng. The application of UAV in emergency rescue and disaster relief[J]. Electronic Science and Technology, 2019, 32(9):20-25.
[4]	岳秀, 张伟. 基于智能算法的无人机航迹规划[J]. 电子科技, 2019, 32(2):9-13.
	Yue Xiu, Zhang Wei. UAV path planning based on intelligent algorithm[J]. Electronic Science and Technology, 2019, 32(2):9-13.
[5]	徐宏飞. 面向智慧避障的物流无人机航迹规划研究[D]. 北京: 北京交通大学, 2019:1-7.
	Xu Hongfei. The study about the track planning of express unmanned aerial vehicle(UAV) for intelligent obstacle avoidance[D]. Beijing: Beijing Jiaotong University, 2019:1-7.
[6]	贾高伟, 王建峰. 无人机集群任务规划方法研究综述[J]. 系统工程与电子技术, 2021, 43(1):99-111.
	Jia Gaowei, Wang Jianfeng. Research review of UAV swarm mission planning method[J]. Systems Engineering and Electronics, 2021, 43(1):99-111.
[7]	韩尧, 李少华. 基于改进人工势场法的无人机航迹规划[J]. 系统工程与电子技术, 2021, 43(11):3305-3311.
	Han Yao, Li Shaohua. UAV path planning based on improved artificial potential field[J]. Systems Engineering and Electronics, 2021, 43(11):3305-3311.
[8]	刘永建, 曾国辉, 黄勃, 等. 改进蚁群算法的机器人路径规划研究[J]. 电子科技, 2020, 33(1):13-18.
	Liu Yongjian, Zeng Guohui, Huang Bo, et al. Research on robot path planning based on improved ant colony algorithm[J]. Electronic Science and Technology, 2020, 33(1): 13-18.
[9]	张利民, 李茜, 李伟勋. 导弹定向定时航迹规划的改进PSO方法研究[J]. 航天控制, 2021, 39(4):36-42.
	Zhang Limin, Li Qian, Li Weixun. Improved PSO method research of trajectory planning with impact angle and time constraints of missile[J]. Aerospace Control, 2021, 39(4):36-42.
[10]	Devaurs D, Simeon T, Cortes J. Optimal path planning in complex cost spaces with sampling-based algorithms[J]. IEEE Transactions on Automation Science and Engineering, 2016, 13(2):415-424. doi: 10.1109/TASE.2015.2487881
[11]	Hao B, Yan Z. Recovery path planning for an agricultural mobile robot by Dubins-RRT* algorithm[J]. International Journal of Robotics & Automation, 2018, 33(2):202-207.
[12]	谭建豪, 肖友伦, 刘力铭, 等. 改进PRM算法的无人机航迹规划[J]. 传感器与微系统, 2020, 39(1):38-41.
	Tan Jianhao, Xiao Youlun, Liu Liming, et al. Improved PRM algorithm for path planning of UAV[J]. Transducer and Microsystem Technologies, 2020, 39(1):38-41.
[13]	张超省, 王健, 张林, 等. 面向复杂障碍场的多智能体系统集群避障模型[J]. 兵工学报, 2021, 42(1):141-150. doi: 10.3969/j.issn.1000-1093.2021.01.016
	Zhang Chaosheng, Wang Jian, Zhang Lin, et al. A multi-agent system flocking model with obstacle avoidance in complex obstacle field[J]. Acta Armamentarii, 2021, 42(1):141-150. doi: 10.3969/j.issn.1000-1093.2021.01.016
[14]	顾伟, 汤俊, 白亮, 等. 面向时间协同的多无人机队形变换最优效率模型[J]. 航空学报, 2019, 40(6):192-200.
	Gu Wei, Tang Jun, Bai Liang, et al. Time synergistic optimal efficiency model for formation transformation of multiple UAVs[J]. Acta Aeronautica et Astronautica Sinica, 2019, 40(6):192-200.
[15]	李樾, 韩维, 陈清阳, 等. 基于快速扩展随机树算法的多无人机编队重构方法研究[J]. 西北工业大学学报, 2019, 37(3):601-611. doi: 10.1051/jnwpu/20193730601
	Li Yue, Han Wei, Chen Qingyang, et al. Research on formation reconfigureuration of UAVs based on RRT algorithm[J]. Journal of Northwestern Polytechnical University, 2019, 37(3):601-611. doi: 10.1051/jnwpu/20193730601
[16]	范林飞. 基于鸽群算法的多无人机协同编队[D]. 南京: 南京航空航天大学, 2020:21-41.
	Fan Linfei. Cooperative formation of multi-UAVs based on pigeon algorithm[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2020:21-41.
[17]	任立敏, 王伟东, 杜志江, 等. 障碍环境下多移动机器人动态优化队形变换[J]. 机器人, 2013, 35(5):535-543. doi: 10.3724/SP.J.1218.2013.00535
	Ren Limin, Wang Weidong, Du Zhijiang, et al. Dynamic and optimized formation switching for multiple mobile robots in obstacle environments[J]. Robot, 2013, 35(5):535-543. doi: 10.3724/SP.J.1218.2013.00535
[18]	Gammell J D, Srinivasa S S, Barfot A. Informed-RRT: Optimal sampling-base path focused via direct sampling of an admissible ellipsoidal heuristic[C].Shanghai: International Conference on Intelligent Robots and Systems,IEEE, 2014:2997-3004.

航迹	航迹长度/m	I_P
D_L	195.80	1.000
D_F1	195.00	0.996
D_F2	200.82	1.026
D_F3	203.08	1.037

Multi-UAV Path Planning Algorithm Based on Formation Change

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