基于视野和自适应半径的无人机集群避障算法

doi:10.16182/j.issn1004731x.joss.23-1269

摘要/Abstract

摘要：

针对大规模无人机集群跟踪航线飞行时遇到障碍物的规避问题，提出了一种基于分布式模型预测控制结合视野和自适应避障半径的无人机集群避障算法。集群飞行过程中，无人机根据自身位置获取当前时刻的参考航线信息，通过局部信息交互获取周围邻居的预测轨迹，当遇到障碍物时，结合提出的自适应避障半径法以及视野拓扑，有效解决了集群避障时内部安全距离无法保持且部分无人机和障碍物发生碰撞的问题，实现了集群飞行的外部避障与内部防撞。

关键词: 无人机集群, 避障, 自适应避障半径, 视野拓扑, 分布式模型预测控制

Abstract:

Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route, a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed. In the process of swarm flight, the UAV obtains the reference route information of the current moment according to its own position, and obtains the predicted trajectory of its neighbors through local information interaction. When encountering obstacles, the adaptive obstacle avoidance radius and field of view topology method are combined to effectivelysolve the problem that the internal safety distance cannot be maintained and some UAVs collide with obstacles during obstacle avoidance, the external obstacle avoidance and internal collision avoidance of swarm flight are realized.

Key words: UAV swarm, obstacle avoidance, adaptive obstacle avoidance radius, field of view topology, distributed model predictive control

中图分类号:

V279

艾高航,李春涛 . 基于视野和自适应半径的无人机集群避障算法[J]. 系统仿真学报, 2024, 36(12): 2945-2959.

Ai Gaohang,Li Chuntao . UAV Swarm Obstacle Avoidance Based on Visual Filed and Adaptive Radius[J]. Journal of System Simulation, 2024, 36(12): 2945-2959.

图/表 35

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表1

表2

参数设置

参数名称	集群模式	避障模式
$Q k 1$	1	1
$Q k 2$	0.2	0.08
$Q k 3$	0.1	0.003
$Q k 4$	20 000	60 000
$Q k 5$	10 000	4 000
$R k 1$	1 000	100
$R k 2$	1 000	100
$S k 1$	100	100
$S k 2$	100	100
$K o, n$	10 000	25 000
$K o, b$	0	100 000
$K n 1$	10 000	0
$K n 2$	10 000	0

表2

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表3

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参考文献 15

1	陆浩然, 王永峰, 鞠兴龙. 固定翼无人机编队的启发分布式模型预测控制[J]. 导航定位与授时, 2021, 8(6): 43-51.
	Lu Haoran, Wang Yongfeng, Ju Xinglong. Fixed Wing UAVs Formation Control Based on Heuristic Distributed Model Predictive Control Method[J]. Navigation Positioning and Timing, 2021, 8(6): 43-51.
2	Reynolds C W. Flocks, Herds and Schools: A Distributed Behavioral Model[C]//Proceedings of the 14th Annual Conference on Computer Graphics and Interactive Techniques. New York: Association for Computing Machinery, 1987: 25-34.
3	Olfati-Saber R. Flocking for Multi-agent Dynamic Systems: Algorithms and Theory[J]. IEEE Transactions on Automatic Control, 2006, 51(3): 401-420.
4	伍友利, 叶圣涛, 方洋旺, 等. 固定翼无人机群的集群和避障控制[J]. 国防科技大学学报, 2019, 41(5): 103-110.
	Wu Youli, Ye Shengtao, Fang Yangwang, et al. Flocking and Obstacles Avoidance for Fixed-wing Unmanned Aerial Vehicle Swarm[J]. Journal of National University of Defense Technology, 2019, 41(5): 103-110.
5	Wang Xun, Wang Xiangke, Zhang Daibing, et al. A Liquid Sphere-inspired Physicomimetics Approach for Multiagent Formation Control[J]. International Journal of Robust and Nonlinear Control, 2018, 28(15): 4565-4583.
6	桂雪琪, 李春涛. 基于视野和速度引导的无人机集群避障算法[J]. 系统仿真学报, 2024, 36(3): 545-554.
	Gui Xueqi, Li Chuntao. UAV Swarm Obstacle Avoidance Algorithm Based on Visual Field and Velocity Guidance[J]. Journal of System Simulation, 2024, 36(3): 545-554.
7	陈浩. 复杂条件下固定翼无人机集群编队控制研究[D]. 长沙: 国防科技大学, 2020.
	Chen Hao. Research on Formation Control of Fixed-wing UAV Swarm in Complex Environments[D]. Changsha: National University of Defense Technology, 2020.
8	Richards A, How J P. Robust Distributed Model Predictive Control[J]. International Journal of Control, 2007, 80(9): 1517-1531.
9	苏延旭. 约束系统分布式模型预测控制与优化方法研究[D]. 南京: 东南大学, 2021.
	Su Yanxu. Distributed Model Predictive Control and Optimization for Constrained Systems[D]. Nanjing: Southeast University, 2021.
10	Müller Matthias A, Reble Marcus, Allgöwer Frank. Cooperative Control of Dynamically Decoupled Systems Via Distributed Model Predictive Control[J]. International Journal of Robust and Nonlinear Control, 2012, 22(12): 1376-1397.
11	秦明星, 王忠, 李海龙, 等. 基于分布式模型预测的无人机编队避障控制[J]. 北京航空航天大学学报, 2024, 50(6): 1969-1981.
	Qin Mingxing, Wang Zhong, Li Hailong, et al. Obstacle Avoidance Control of UAV Formation Based on Distributed Model Prediction[J]. Journal of Beijing University of Aeronautics and Astronautics, 2024, 50(6): 1969-1981.
12	Zhang Boyang, Sun Xiuxia, Liu Shuguang, et al. Adaptive Differential Evolution-based Distributed Model Predictive Control for Multi-UAV Formation Flight[J]. International Journal of Aeronautical and Space Sciences, 2020, 21(2): 538-548.
13	Dunbar W B, Murray R M. Distributed Receding Horizon Control for Multi-vehicle Formation Stabilization[J]. Automatica, 2006, 42(4): 549-558.
14	黄朝阳. 基于分布式预测控制的多机器人协同避障[D]. 哈尔滨: 哈尔滨工业大学, 2022.
	Huang Chaoyang. Multi-robot Obstacle Avoidance Based on Distributed Model Predictive Control[D]. Harbin: Harbin Institute of Technology, 2022.
15	Müller M A, Allgöwer F. Distributed MPC for Consensus and Synchronization[M]//José M Maestre, Rudy R Negenborn. Distributed Model Predictive Control Made Easy. Dordrecht: Springer Netherlands, 2014: 89-100.

无人机序列	位置	航迹方位角/rad	航迹倾斜角/rad
UAV1	[248, 1, 401]	0	0
UAV2	[184, 51, 401]	0	0
UAV3	[184, -50, 401]	0	0
UAV4	[184, 1, 452]	0	0
UAV5	[184, 1, 350]	0	0
UAV6	[184, 1, 400]	0	0
UAV7	[120, 101, 400]	0	0
UAV8	[120, -100, 400]	0	0
UAV9	[120, 1, 502]	0	0
UAV10	[120, 1, 299]	0	0
UAV11	[120, 50, 451]	0	0
UAV12	[120, 50, 350]	0	0
UAV13	[120, -50, 451]	0	0
UAV14	[120, -50, 350]	0	0
UAV15	[120, 1, 400]	0	0
UAV16	[56, 0, 400]	0	0
UAV17	[56, 51, 400]	0	0
UAV18	[56, -51, 400]	0	0
UAV19	[56, 0, 451]	0	0
UAV20	[56, 0, 348]	0	0

无人机序列	位置	航迹方位角/rad	航迹倾斜角/rad
UAV1	[245, 196, 411]	0.26	0.01
UAV2	[175, 218, 410]	0.50	0.03
UAV3	[176, 115, 412]	0.32	0.07
UAV4	[176, 167, 462]	0.45	0.07
UAV5	[176, 168, 358]	0.45	0.00
UAV6	[176, 167, 411]	0.35	0.06
UAV7	[107, 217, 407]	0.60	0.04
UAV8	[102, 21, 407]	0.78	0.04
UAV9	[105, 118, 505]	0.66	-0.03
UAV10	[105, 118, 309]	0.66	0.09
UAV11	[106, 167, 455]	0.63	0.00
UAV12	[106, 167, 358]	0.63	0.07
UAV13	[104, 69, 455]	0.69	0.01
UAV14	[104, 69, 359]	0.68	0.09
UAV15	[105, 118, 407]	0.66	0.04
UAV16	[36, 42, 404]	0.71	0.09
UAV17	[36, 94, 403]	0.82	0.05
UAV18	[38, -8, 404]	0.68	0.09
UAV19	[34, 45, 455]	0.86	0.09
UAV20	[34, 45, 351]	0.86	0.03

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