Hierarchical cooperative path planning method using three-dimensional velocity-obstacle strategy for multiple fixed-wing UAVs

doi:10.23919/JSEE.2025.000087

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (5): 1342-1352.doi: 10.23919/JSEE.2025.000087

• CONTROL THEORY AND APPLICATION • Previous Articles

Hierarchical cooperative path planning method using three-dimensional velocity-obstacle strategy for multiple fixed-wing UAVs

Zhenlin ZHOU¹^,²(), Teng LONG¹^,²^,³^,*(), Jingliang SUN¹^,²^,³(), Junzhi LI¹^,²()

¹ School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
² Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing 100081, China
³ Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401121, China

Received:2024-05-06 Online:2025-10-18 Published:2025-10-24
Contact: Teng LONG E-mail:bit_zzl@sina.com;tenglong@bit.edu.cn;sunjingliangac@163.com;junzhi_lee@163.com
About author:
ZHOU Zhenlin was born in 1997. He received his B.S. degree in mechanical engineering from Beijing Institute of Technology, Beijing, China, in 2019. He is currently working toward his Ph.D. degree in aeronautical and astronautical science and technology with Beijing Institute of Technology. His research interests include multiagent path planning and cooperative task assignment. E-mail: bit_zzl@sina.com

LONG Teng was born in 1982. He received his B.S. degree in flight vehicle propulsion engineering and Ph.D. degree in aeronautical and astronautical science and technology from Beijing Institute of Technology, Beijing, China, in 2004 and 2009, respectively. He is a professor and Executive Dean with the School of Aerospace Engineering, Beijing Institute of Technology. His research interests include multi-disciplinary design optimization theory and its applications to flight vehicle conceptual design and multi-aircraft collaborative mission planning and decision-making. E-mail: tenglong@bit.edu.cn

SUN Jingliang was born in 1990. He received his B.S. degree in automation from Tianjin University of Technology, Tianjin, China, and Ph.D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China. He is an associate professor at the School of Aerospace Engineering, Beijing Institute of Technology. His current research interests include adaptive dynamic programming, cooperative guidance and control, cooperative mission planning, and applications in aerospace engineering. E-mail: sunjingliangac@163.com

LI Junzhi was born in 1998. He received his B.S. degree in flight vehicle design and engineering from the School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China, in 2020. He is currently working toward his Ph.D. degree in aeronautical and astronautical science and technology with Beijing Institute of Technology. His research interests include control of unmanned flight vehicles and cooperative trajectory optimization. E-mail: junzhi_lee@163.com
Supported by:
This work was supported by the National Science Fund for Distinguished Young Scholars (52425211) and BIT Research Fund Program for Young Scholars (XSQD-202201005).

Abstract

Abstract:

A three-dimensional path-planning approach has been developed to coordinate multiple fixed-wing unmanned aerial vehicles (UAVs) while avoiding collisions. The hierarchical path-planning architecture that divides the path-planning process into two layers is proposed by designing the velocity-obstacle strategy for satisfying timeliness and effectiveness. The upper-level layer focuses on creating an efficient Dubins initial path considering the dynamic constraints of the fixed wing. Subsequently, the lower-level layer detects potential collisions and adjusts its flight paths to avoid collisions by using the three-dimensional velocity obstacle method, which describes the maneuvering space of collision avoidance as the intersection space of half space. To further handle the dynamic and collision-avoidance constraints, a priority mechanism is designed to ensure that the adjusted path is still feasible for fixed-wing UAVs. Simulation experiments demonstrate the effectiveness of the proposed method.

Key words: three-dimensional path planning, Dubins path method, velocity obstacle, collision avoidance

Zhenlin ZHOU, Teng LONG, Jingliang SUN, Junzhi LI. Hierarchical cooperative path planning method using three-dimensional velocity-obstacle strategy for multiple fixed-wing UAVs[J]. Journal of Systems Engineering and Electronics, 2025, 36(5): 1342-1352.

Figures/Tables 15

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Table 1

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References 32

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Number	Start point	Terminal point
1	(800, 0, 0)	(−800, 0, 0)
2	(566,566,0)	(−566,−566,0)
3	(0, 800, 0)	(0, −800, 0)
4	(−566,566,0)	(566,−566,0)
5	(−800,0,0)	(800,0,0)
6	(−566,−566,0)	(566,566,0)
7	(0,800,0)	(0,−800,0)
8	(566,−566,0)	(−566,566,0)

Number	Start point	Terminal point	Number	Start point	Terminal point	Number	Start point	Terminal point
1	(800,0,50)	(−800,0,−50)	18	(−429,675,41)	(429,−675,−41)	35	(−341,−724,67)	(341,724,−67)
2	(794,100,49)	(−794,−100,−49)	19	(−510,616,59)	(510,−616,−59)	36	(−247,−761,32)	(247,761,−32)
3	(775,199,51)	(−775,−199,−51)	20	(−583,548,40)	(583,−548,−40)	37	(−150,−786,68)	(150,786,−68)
4	(744,295,48)	(−744,−295,−48)	21	(−647,470,60)	(647,−470,−60)	38	(−50,−798,31)	(50,798,−31)
5	(701,385,52)	(−701,−385,−52)	22	(−701,385,39)	(701,−385,−39)	39	(50,−798,69)	(−50,798,−69)
6	(647,470,47)	(−647,−470,−47)	23	(−744,295,61)	(744,−295,−61)	40	(150,−786,30)	(−150,786,−30)
7	(583,548,53)	(−583,−548,−53)	24	(−775,199,38)	(775,−199,−38)	41	(247,−761,70)	(−247,761,−70)
8	(510,616,46)	(−510,−616,−46)	25	(−794,100,62)	(794,−100,−62)	42	(341,−724,29)	(−341,724,−29)
9	(429,675,54)	(−429,−675,−54)	26	(−800,0,37)	(800,0,−37)	43	(429,−675,71)	(−429,675,−71)
10	(341,724,45)	(−341,−724,−45)	27	(−794,−100,63)	(794,100,−63)	44	(510,−616,28)	(−510,616,−28)
11	(247,761,55)	(−247,−761,−55)	28	(−775,−199,36)	(775,199,−36)	45	(583,−548,72)	(−583,548,−72)
12	(150,786,44)	(−150,−786,−44)	29	(−744,−295,64)	(744,295,−64)	46	(647,−470,27)	(−647,470,−27)
13	(50,798,56)	(−50,−798,−56)	30	(−701,−385,35)	(701,385,−35)	47	(701,−385,73)	(−701,385,−73)
14	(−50,798,43)	(50,−798,−43)	31	(−647,−470,65)	(647,470,−65)	48	(744,−295,26)	(−744,295,−26)
15	(−150,786,57)	(150,−786,−57)	32	(−583,−548,34)	(583,548,−34)	49	(775,−199,74)	(−775, 199,−74)
16	(−247,761,42)	(247,−761,−42)	33	(−510,−616,66)	(510,616,−66)	50	(794,−100,25)	(−794,100,−25)
17	(−341,724,58)	(341,−724,−58)	34	(−429,−675,33)	(429,675,−33)	−	−	−

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Hierarchical cooperative path planning method using three-dimensional velocity-obstacle strategy for multiple fixed-wing UAVs

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