A self-organization formation configuration based assignment probability and collision detection

doi:10.23919/JSEE.2024.000016

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (1): 222-232.doi: 10.23919/JSEE.2024.000016

• CONTROL THEORY AND APPLICATION • Previous Articles

A self-organization formation configuration based assignment probability and collision detection

Wei SONG¹(), Tong WANG¹(), Guangxin YANG¹(), Peng ZHANG²^,*()

¹ School of Harbin Engineering University , Harbin 150001, China
² Chinese Aeronautical Establishment, Beijing 100010, China

Received:2022-10-06 Online:2024-02-18 Published:2024-03-05
Contact: Peng ZHANG E-mail:weisong@hrbeu.edu.cn;wangtong@hrbeu.edu.cn;1803669455@hrbeu.edu.cn;my2ndemail@126.com
About author:
SONG Wei was born in 1992. He received his M.S. degree in communication and information systems from School of Electronic Information Engineering, Anhui University in 2019. He is currently a Ph.D. candidate of Information and Communication Engineering from Harbin Engineering University. His research interests include the formation of unmanned aerial vehicles (UAVs), the obstacle avoidance of multiple UAVs (single-obstacle and multiple obstacles environment), the control theory (the model prediction method, and the consensus control method), and the channel code (the puncture of polar code, the low density parity check code, and the turbo code). E-mail: weisong@hrbeu.edu.cn

WANG Tong was born in 1977. He received his M.S. degree in computer application from Harbin Engineering University in 2003. He received his Ph.D. degree in computer application from Harbin Engineering University in 2006. He is a professor and Ph.D. supervisor at Information and Communication Engineering College, Harbin Engineering University. His research interests include wireless network, vehicular ad hoc network, and Internet of Things. E-mail: wangtong@hrbeu.edu.cn

YANG Guangxin was born in 1994. He received his B.E. degree in measurement and control technology and instrumentation program (signal processing and instrumentation) from Jilin University. He is currently a Ph.D. candidate of information and communication engineering from Harbin Engineering University. His research interests are internet of vehicles, traffic prediction and control. E-mail: 1803669455@hrbeu.edu.cn

ZHANG Peng was born in 1986. He received his B.S. and M.S. degrees from East China Normal University (ECNU) University, Shanghai, China and Ph.D. degree frm UNIVERSI-UPECTE DE PARIS (UPEC), Paris, France, in 2008, 2011 and 2014, respectively, all in mathematics. His current research interests include autonomous multi-agent systems and artificial intelligence (AI). E-mail: my2ndemail@126.com
Supported by:
This work was supported by the Basic Scientific Research Business Expenses of Central Universities (3072022QBZ0806).

Abstract

Abstract:

The formation control of multiple unmanned aerial vehicles (multi-UAVs) has always been a research hotspot. Based on the straight line trajectory, a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption. In order to avoid the collision between UAVs in the formation process, the concept of safety ball is introduced, and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs. Based on the idea of game theory, a method of UAV motion form setting based on the maximization of interests is proposed, including the maximization of self-interest and the maximization of formation interest is proposed, so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance. Finally, through simulation verification, the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length, and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Key words: straight line trajectory, assignment probability, collision detection, lane occupation detection, maximization of interests

Wei SONG, Tong WANG, Guangxin YANG, Peng ZHANG. A self-organization formation configuration based assignment probability and collision detection[J]. Journal of Systems Engineering and Electronics, 2024, 35(1): 222-232.

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A self-organization formation configuration based assignment probability and collision detection

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