基于速度障碍法的无人机避障与航迹恢复策略

doi:10.3969/j.issn.1001-506X.2020.08.16

Abstract

Abstract:

Aiming at the problem of flight conflict resolution and track recovery of unmanned aerial vehicle (UAV) with complex obstacles in the fusion airspace, a geometric optimization method based on the velocity obstacle method is proposed, and the problem is described in strict mathematics. Firstly, according to the relative position and speed relationship between the UAV and the obstacle, the conflict type is determined based on the track pre-propelling model, and whether the conditions of each resolution strategy are met is also determined. Secondly, the corresponding resolution strategy is selected. After the resolution of the conflict is completed, the UAV will resume the original flight path. Then, geometric analysis and theoretical derivation prove that the model can effectively solve the flight conflict, and give the specific time of conflict resolution and track recovery. Finally, in the simulation, the proposed method chooses the conflict resolution strategy autonomously according to different scenaries, which shows that this method is simple and efficient.

Key words: speed obstacle, conflict detection, conflict resolution, track recovery, geometric optimization algorithm

CLC Number:

V249.1

Honghong ZHANG, Xusheng GAN, Ang LI, Zhiqiang GAO, Xinyu XU. UAV obstacle avoidance and track recovery strategy based onvelocity obstacle method[J]. Systems Engineering and Electronics, 2020, 42(8): 1759-1767.

Figures/Tables 18

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Table 1

Fig.10

Fig.11

Fig.12

Fig.13

Fig.14

Table 2

Table 3

Table 4

References 28

1	SHIN H S, TSOURDOS A, WHITE B A, et al. UAV conflict detection and resolution for static and dynamic obstacles[C]//Proc.of the Guidance, Navigation and Control Conference and Exhibit, 2008: AIAA 2008-6521.
2	DU Y, NAN Y. Research of robot path planning based on improved artificial potential field[C]//Proc.of the International Conference on Advances in Mechanical Engineering and Industrial Informatics, 2016: 1025-1030.
3	ZHAO J, BIN Y, RUN Y. The flight navigation planning based on potential field ant colony algorithm[C]//Proc.of the International Conference on Advanced Control, Automation and Artificial Intelligence, 2018: 200-204.
4	ZHANG N, ZHANG Y, MA C, et al. Path planning of six-DOF serial robots based on improved Artificial potential field method[C]//Proc.of the IEEE International Conference on Robots and Biomimetics, 2017: 617-621.
5	OROZCO-ROSAS U , MONTIEL O , SEPULVEDA R . Mobile robot path planning using membrane evolutionary artificial field[J]. Applied Soft Computing, 2019, 77, 236- 251.
6	ZHANG W , GONG X , HAN G , et al. An improved ant colony algorithm for path planning in one scenic area with many pots[J]. IEEE Access, 2017, 5, 13260- 13269.
7	MAC T T , COPOT C , TRAN D T , et al. A hierarchical global path planning approach for mobile robots based on multi-objective particle swarm optimization[J]. Applied Soft Computing, 2017, 59, 68- 76.
8	YEN C T , CHENG M F . A study of fuzzy control with ant colony algorithm used in mobile robot for shortest path planning and obstacle avoidance[J]. Microsystem Technologies, 2018, 24 (1): 125- 135.
9	DARWISH A H , JOUKHADAR A , KASHKASH M . Using the bees algorithm for wheeled mobile robot path planning in an indoor dynamic environment[J]. Cogent Engineering, 2018, 5 (1): 1- 23.
10	PRANDINI M , HU J , LYGEROS J , et al. A probabilistic approach to aircraft conflict detection[J]. IEEE Trans.on Intelligent Transportation Systems, 2000, 1 (4): 199- 200.
11	聂俊岚, 张庆杰, 王艳芬. 基于加权Voronoi图的无人飞行器航迹规划[J]. 飞行力学, 2015, 33 (4): 339- 343.
	NIE J L , ZHANG Q J , WANG Y F . Flight path planning of uav based on weighted voronoi diagram[J]. Flight Dynamics, 2015, 33 (4): 339- 343.
12	BILLIMORIA K D. A geometric optimization approach to aircraft conflict resolution[C]//Proc.of the 18th Applied Aerodynamics Conference, 2000: AIAA 2000-4265.
13	BILLIMORIA K D , SRIDHAR B , CHATTERJI G B , et al. Facet: future ATM concepts evaluation tool[J]. Air Traffic Control Quarterly, 2001, 9 (1): 1- 20.
14	WHITE B A, SHIN H S, TSOURDOS A. UAV obstacle avoi- dance using differential geometry concepts[C]//Proc.of the 18th World Congress, International Federation of Automatic Control, 2011: 6325-6330.
15	GESER A, MUNOZ C. A geometric approach to strategic conflict detection and resolution[C]//Proc.of the Digital Avionics Systems Conference. Piscataway, 2002.
16	ZHANG Y, ZHANG M, YU J. Realtime flight conflict detection and release based on multi-agent system[C]//Proc.of the IOP Conference Series: Earth and Environmental Science, 2018: 032053.
17	FIORINI P . Motion planning in dynamic environments using velocity obstacles[J]. International Journal of Robotics Research, 1998, 17 (7): 760- 772.
18	Durand N , BARNIER N . Does ATM need centralized coordination? Autonomous conflict resolution analysis in a constrained speed environment[J]. Air Traffic Control Quarterly, 2015, 23 (4): 710- 712.
19	杨秀霞, 张毅, 周硙硙. 一种动态不确定环境下UAV自主避障算法[J]. 系统工程与电子技术, 2017, 39 (11): 2546- 2552.
	YANG X X , ZHANG Y , ZHOU W W . Automatic obstacle avoidance algorithm for UAV in dynamic uncertain environment[J]. Systems Engineering and Electronics, 2017, 39 (11): 2546- 2552.
20	王泽坤, 吴明功, 温祥西. 基于速度障碍法的飞行冲突解脱与恢复策略[J]. 北京航空航天大学学报, 2019, 45 (7): 1294- 1302.
	WANG Z K , WU M G , WEN X X , et al. Flight collision resolution and recovery strategy based on velocity obstacle method[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45 (7): 1294- 1302.
21	魏建, 李相民, 代进进. 基于速度障碍法的无人机避免机动障碍物问题[J]. 火力与指挥控制, 2016, 41 (8): 84- 92.
	WEI J , LI X M , DAI J J . Avoidance of maneuvering obstacles in UAV based on speed obstacle method[J]. Firepower and command and control, 2016, 41 (8): 84- 92.
22	杨秀霞, 周硙硙, 张毅. 基于速度障碍圆弧法的UAV自主避障规划研究[J]. 系统工程与电子技术, 2017, 39 (11): 168- 176.
	YANG X X , ZHOU W W , ZHANG Y . Automatic obstacle avoi- dance planning for UAV based on velocity obstacle arc method[J]. Systems Engineering and Electronics, 2017, 39 (11): 168- 176.
23	XU Y J, XIN M, WANG J N. Unmanned aerial vehicle formation flight via a hierarchical cooperative control approach[C]//Proc.of the AIAA Guidance, Navigation, and Control Confe-rence, 2011: 500-507.
24	DURAND N . Constant speed optimal reciprocal collision avoida-nce[J]. Transportation Research Part C: Emerging Technologies, 2018, 96, 366- 379.
25	全权, 李刚, 柏艺琴, 等. 低空无人机交通管理概览与建议[J]. 航空学报, 2020, 41 (1): 023238.
	QUAN Q , LI G , BAI Y Q , et al. Low altitude UAV traffic management: An introductory overview and proposal[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41 (1): 023238.
26	蒋旭瑞, 吴明功, 温祥西, 等. 基于合作博弈的多机飞行冲突解脱策略[J]. 系统工程与电子技术, 2018, 40 (11): 2482- 2489.
	JIANG X R , WU M G , WEN X X , et al. Multi-aircraft conflict resolution strategy based on cooperative game[J]. Systems engineering and electronic technology, 2018, 40 (11): 2482- 2489.
27	张玮, 马焱, 赵捍东, 等. 基于改进烟花-蚁群混合算法的智能移动体避障路径规划[J]. 控制与决策, 2019, 34 (2): 335- 343.
	ZHANG W , MA Y , ZHAO H D , et al. Intelligent moving body obstacle avoidance path planning based on the improved fireworks and ant colony hybrid algorithm[J]. Control and decision, 2019, 34 (2): 335- 343.
28	任彦, 赵海波, 肖永健. 改进势场蚁群法的机器人避障及路径规划[J]. 电光与控制, 2019, 26 (11): 75- 79.
	REN Y , ZHAO H B , XIAO Y J . Robot obstacle avoidance and path planning based on improved potential field ant colony method[J]. Electronics Optics & Control, 2019, 26 (11): 75- 79.

场景	类型	起点/km	航向/(°)	速度/(m/s)	仿真步长/h
1	无人机	(0, 0)	45	50	0.001
1	障碍物	(30, 30)	225	40	0.001
2	无人机	(0, 15)	0	50	0.001
2	障碍物	(15, 0)	90	50	0.001
3	无人机	(0, 0)	30	60	0.000 1
3	障碍物	(20, 0)	150	50	0.000 1

场景	类型	解脱坐标/km	最大航向改变量/(°)	解脱速度/(m/s)	判断	解脱方式
1	无人机	(12.86, 12.86)	42.8	50	$\Delta \theta \in\left[-\frac{\pi}{3}, \frac{\pi}{3}\right] $	航向解脱
1	障碍物	(19.72, 19.72)	0	40		航向解脱
2	无人机	(8.1, 15)	62.7	76.5	$\Delta \theta \notin\left[-\frac{\pi}{3}, \frac{\pi}{3}\right], v_{1}^{\prime} \in[\underline{v}, \bar{v}] $	速度解脱
2	障碍物	(15, 8.1)	0	50		速度解脱
3	无人机	(5.46, 3.15)	19.6	60	-	混合调配
	障碍物	(15.45, 2.63)	0	50		混合调配
	无人机	(5.46, 3.15)	59.3	40		混合调配
	障碍物	(15.45, 2.63)	0	50		混合调配

场景	求解时间/s	解脱时间/s	飞行距离(解脱前)/km	飞行距离(解脱后)/km	绕飞距离/km	绕飞距离占比/%	机动次数
1	0.01	2.69	10.20	10.98	0.78	7.6	2次
2	0.009	1.82	9.8	9.8	0	0	2次
3	0.009	1.45	13.04	13.24	0.20	1.5	2次
3	0.008	1.55	13.52	15.44	1.92	12.4	2次

指标	文献[26]	文献[27]	文献[28]	本文算法
求解时间/s	3.13	0.83	17.7	约0.01
机动次数	两次	多次	多次	两次
可操作性	强	弱	弱	强

[1]	Chengzhao LU, Jianxing GONG, Lei ZHU, Quan LIU. Research on task scheduling algorithm in resource-constrained environments [J]. Systems Engineering and Electronics, 2021, 43(12): 3586-3593.
[2]	Jiayi LIU, Shaohua YUE, Gang WANG, Jie ZHANG, Xiaoqiang YAO. Design of command control model based on MPC-MAS under multi-platform distributed cooperative operation [J]. Systems Engineering and Electronics, 2020, 42(7): 1582-1589.
[3]	WU Minggong, WANG Zekun, WEN Xiangxi, JIANG Xurui, SUN Qianrui. Aircraft conflict resolution model based on geometric optimization [J]. Systems Engineering and Electronics, 2019, 41(4): 863-869.
[4]	FU Xiaowei, FENG Peng, GAO Xiaoguang, LIU Zhong. Conflict resolution in multi-UAV cooperative tasks assignment withcommunication delay [J]. Systems Engineering and Electronics, 2018, 40(7): 1491-1497.
[5]	JIANG Xurui, WU Minggong, WEN Xiangxi, TU Congliang, NIE Dangmin. Conflict resolution of multi-aircraft based on the cooperative game [J]. Systems Engineering and Electronics, 2018, 40(11): 2482-.
[6]	SU Zhi-gang, FU Xiao-xian, HAO Jing-tang. Dynamic triangulation based method for screening potential conflicts [J]. Systems Engineering and Electronics, 2016, 38(6): 1456-1461.
[7]	SHI Lei，WU Ren-biao，ZHANG Zhe. Conflict detection algorithm based on hybrid system and #br# position space discretization [J]. Systems Engineering and Electronics, 2014, 36(4): 624-629.
[8]	SU Zhi-gang， WANG Zheng， WU Ren-biao. Robust dynamic Delaunay triangulation technology for moving points [J]. Journal of Systems Engineering and Electronics, 2013, 35(8): 1764-1768.
[9]	WANG Hai-bo, XU Min-qiang, WANG Ri-xin, LI Yu-qing. Long-term acquisition plan method for small satellites constellation [J]. Journal of Systems Engineering and Electronics, 2011, 33(6): 1293-1298.
[10]	YANG Ping, LIU Wei-dong, BI Yi-ming. Goal conflict resolution of multi-agent systems based on distributed negotiation evolution algorithm [J]. Journal of Systems Engineering and Electronics, 2009, 31(8): 1918-1922.

UAV obstacle avoidance and track recovery strategy based onvelocity obstacle method

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 18

References 28

Related Articles 10

Recommended Articles

Metrics

Comments