Multi-UAV Synchronous Approaching Using Homotopy-Based Trajectory Planning

被引：3

作者：

Yao, Weiran ^{[1
]}

Chen, Yang ^{[2
]}

Tian, Haoyu ^{[1
]}

Wu, Chengwei ^{[1
]}

Wu, Ligang ^{[1
]}

机构：

[1] Harbin Inst Technol, Sch Astronaut, Harbin 150001, Peoples R China

[2] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China

来源：

GUIDANCE NAVIGATION AND CONTROL | 2022年 / 02卷 / 02期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

Multi-UAV; synchronous approaching; homotopic method; trajectory planning; BOUNDED CURVATURE; DUBINS PATHS; VEHICLES; LENGTH;

D O I：

10.1142/S2737480722500121

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Synchronous approaching is an important capability for autonomous cooperation of multiple unmanned aerial vehicles (UAVs). In this paper, a homotopy-based trajectory planning method is presented for the multi-UAV synchronous approaching problem. A homotopic trajectory description is employed to construct the trajectory solution space of the UAVs. A novel onion-like homotopy structure is proposed to decouple the performance indexes of the trajectory planning problem. Local trajectory homotopy structures are designed based on the detouring model and the hovering model of UAV. The optimal trajectories for synchronous approaching are searched within the homotopy structures. Simulation results show how synchronous the UAVs are, by using the proposed homotopy-based trajectory planning method.

引用

页数：26

共 50 条

[21] Multi-UAV Velocity and Trajectory Scheduling Strategies for Target Classification by a Single Human Operator [J].

Ortiz, Andres ;

Kingston, Derek ;

Langbort, Cedric .

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2013, 70 (1-4) :255-274

[22] Deep Reinforcement Learning Approach for Joint Trajectory Design in Multi-UAV IoT Networks [J].

Xu, Shu ;

Zhan, Xiangyu ;

Li, Chunguo ;

Wang, Dongming ;

Yang, Luxi .

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (03) :3389-3394

[23] ISAC-Enabled Multi-UAV Cooperative Perception and Trajectory Optimization [J].

Wang, Qinyuan ;

Chai, Rong ;

Sun, Ruijin ;

Pu, Renyan ;

Chen, Qianbin .

IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (24) :40982-40995

[24] Multi-UAV Wireless Networks: Jointly Trajectory Optimization and Resource Allocation [J].

Alsheyab, Huda Y. ;

Bedeer, Ebrahim ;

Choudhury, Salimur ;

Ikki, Salama .

2022 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2022, :1053-1058

[25] A multi-UAV fast search path planning algorithm research [J].

Yu, Xiang ;

Wang, Binbin ;

Wang, Ziyi ;

Deng, Fuigui .

2023 IEEE 97TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-SPRING, 2023,

[26] Research on Optimization Method of Multi-UAV Collaborative Task Planning [J].

Cao Ze-ling ;

Wang Qi ;

Yang Ye-qing .

2018 IEEE CSAA GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2018,

[27] Multi-UAV Area Coverage Track Planning Based on the Voronoi Graph and Attention Mechanism [J].

Wang, Jubo ;

Wang, Ruixin .

APPLIED SCIENCES-BASEL, 2024, 14 (17)

[28] Autonomous Multi-UAV Path Planning in Pipe Inspection Missions Based on Booby Behavior [J].

Aljalaud, Faten ;

Kurdi, Heba ;

Youcef-Toumi, Kamal .

MATHEMATICS, 2023, 11 (09)

[29] Mathematical modelling of multi-UAV scenario planning based on 3D LiDAR [J].

Chai R. .

International Journal of Information and Communication Technology, 2024, 24 (06)

[30] Solving complex multi-UAV mission planning problems using multi-objective genetic algorithms [J].

Ramirez-Atencia, Cristian ;

Bello-Orgaz, Gema ;

R-Moreno, Maria D. ;

Camacho, David .

SOFT COMPUTING, 2017, 21 (17) :4883-4900

← 1 2 3 4 5 →