Formation Obstacle Avoidance Algorithm Based on Joint Virtual Sub-target and Boundary Force

doi:10.16182/j.issn1004731x.joss.22-0538

Abstract

Abstract:

In view of the formation control of leader-follower swarm and obstacle avoidance in artificial potential field method in unmanned aerial vehicle (UAV) swarm formation system under complex environmental conditions, an obstacle avoidance algorithm for UAV swarm formation based on joint virtual sub-target and boundary force (JVBF) is proposed. The leader-follower method based on a virtual sub-target is used, and the modified force function is optimized to realize the formation control of the UAV swarm, so as to help the follower UAV to recover the formation quickly; the artificial potential field method based on boundary force is used for local path planning, so as to solve the disadvantages of unreachable targets and oscillation in narrow channels of UAVs. Simulation results show that the proposed algorithm has higher formation consistency and time efficiency than the traditional algorithm.

Key words: artificial potential field, leader-follower, virtual sub-target, modified force, boundary force

CLC Number:

TP391.9

Wang Man, Li Dapeng, Ding Lianghui, Zhu Tianlin. Formation Obstacle Avoidance Algorithm Based on Joint Virtual Sub-target and Boundary Force[J]. Journal of System Simulation, 2023, 35(9): 1918-1930.

Figures/Tables 12

Table 1

Main parameters

符号	描述
R_L	领航无人机
R_F	跟随无人机
R_i	第i架无人机
R_i′	R_i 对应的虚拟子目标
q_i (t)	R_i 在t时刻的位置向量
p_i (t)	R_i 在t时刻的速度向量
u_i (t)	R_i 在t时刻的输入控制
D_r1	R_i 与障碍物之间的边界距离
D_r2	R_i 与目标点之间的边界距离
D_b_n	R_i 与第n个障碍物之间的距离
D_t	R_i 与目标点之间的距离
D_o	障碍物的斥力作用范围大小
$ζ$	大于0的修正系数
$ξ$	大于1的常系数
F_c	修正力
F_d	边界力
F_at	R_i 受到的引力
F_re	R_i 受到的斥力
F_sum	R_i 受到的合力

Table 1

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 2

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次数	本文	文献[12]	次数	本文	文献[12]
1	24.45	81.23	6	27.58	84.23
2	25.13	85.34	7	27.77	85.63
3	25.61	79.68	8	26.68	87.61
4	26.54	84.53	9	25.31	82.74
5	24.97	86.32	10	26.97	88.69

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