Path planning for UAVs formation reconfiguration based on Dubins trajectory

Qing-yang Chen , Ya-fei Lu , Gao-wei Jia , Yue Li , Bing-jie Zhu , Jun-can Lin

Journal of Central South University ›› 2018, Vol. 25 ›› Issue (11) : 2664 -2676.

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Journal of Central South University ›› 2018, Vol. 25 ›› Issue (11) : 2664 -2676. DOI: 10.1007/s11771-018-3944-z
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Path planning for UAVs formation reconfiguration based on Dubins trajectory

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Abstract

Multiple UAVs are usually deployed to provide robustness through redundancy and to accomplish surveillance, search, attack and rescue missions. Formation reconfiguration was inevitable during the flight when the mission was adjusted or the environment varied. Taking the typical formation reconfiguration from a triangular penetrating formation to a circular tracking formation for example, a path planning method based on Dubins trajectory and particle swarm optimization (PSO) algorithm is presented in this paper. The mathematic model of multiple UAVs formation reconfiguration was built firstly. According to the kinematic model of aerial vehicles, a process of dimensionality reduction was carried out to simplify the model based on Dubins trajectory. The PSO algorithm was adopted to resolve the optimization problem of formation reconfiguration path planning. Finally, the simulation and vehicles flight experiment are executed. Results show that the path planning method based on the Dubins trajectory and the PSO algorithm can generate feasible paths for vehicles on time, to guarantee the rapidity and effectiveness of formation reconfigurations. Furthermore, from the simulation results, the method is universal and could be extended easily to the path planning problem for different kinds of formation reconfigurations.

Keywords

unmanned aerial vehicles / formation reconfiguration / path planning / Dubins trajectory / particle swarm optimization

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Qing-yang Chen, Ya-fei Lu, Gao-wei Jia, Yue Li, Bing-jie Zhu, Jun-can Lin. Path planning for UAVs formation reconfiguration based on Dubins trajectory. Journal of Central South University, 2018, 25(11): 2664-2676 DOI:10.1007/s11771-018-3944-z

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References

[1]

ColominaI, MolinaP. Unmanned aerial systems for photogrammetry and remote sensing: A review [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014, 92: 79-97

[2]

ChenY, Yuj-q, SuX, LuoGuan. Path planning for multi-UAV formation [J]. Journal of Intelligent and Robotic Systems, 2015, 77: 229-246

[3]

ZhuX, ZhangX, YanM, QuYao. Three-dimensional formation keeping of multi-UAV based on consensus [J]. Journal of Central South University, 2017, 24: 1387-1395

[4]

ThomasL, SteohenB. Minimum-time speed optimisation over a fixed path [J]. International Journal of Control, 2014, 87(6): 1297-1311

[5]

BuzoganyL E, PachterM, DazzoJ JAutomated control of aircraft in formation flight [C]//Proc. AIAA Guidance, 1993, CA, Navigation and Control Conf., Monterey

[6]

PachterM, AzzoJ J, VethM. Proportional and integral control of nonlinear systems [J]. International Journal of Control, 1996, 64(4): 679-692

[7]

JohnsonN, CaliseJ, SattigeriRApproaches to vision-based formation flight control [C]//Proceeding of IEEE Conference on Decision and Control. Atlantis, 2004, Bahamas, Paradise Island

[8]

GuY, SeansorB, CampaG, NapolitanoM R, RoweL. Design and flight testing evaluation of formation control law [J]. IEEE Transaction of Control System Technology, 2006, 14(6): 1105-1112

[9]

LiY, ChenQ, HouZhongResearch on UAVs formation reconfiguration based on Dubins path [C]//Proceedings of 2016 IEEE Chinese Guidance, 2016, Jiangsu, Navigation and Control Conference. Nanjing

[10]

QiN, SunX, DongC, YaoWei. Mission planning based on path prediction for multiple UAVs [J]. Journal of Harbin Institute of Technology, 2016, 48(4): 32-36

[11]

YuanS, LiF, WangL, ZhangYu. An optimal coordination trajectory planning method of multiple unmanned air vehicles based on hierarchy strategy [J]. Journal of Air Force Engineering University(Natural Science Edition), 2015, 16(2): 33-37

[12]

ErgezerH, LeblebiciogluK. 3D Path planning for multiple UAVs for maximum information collection [J]. Journal of Intelligent and Robotic Systems, 2014, 73: 737-762

[13]

GaoC, ZhenZ, GongHua. Collaborative path-planning of multiple UAV in radar threatening environment [J]. Journal of Applied Sciences, 2014, 32(3): 287-292

[14]

ZhangX, MaP, JiJ, ZhuLiang. Cooperative planning control of multi UAV with time constraint [J]. Electronics Optics and Control, 2015, 22(9): 42-45

[15]

ManyamG S, RathinamS, CasbeerD, GarciaE. Tightly bounding the shortest Dubins paths through a sequence of points [J]. Journal of Intelligent and Robotic Systems, 2017, 88: 495-511

[16]

ChenQ, LiYueUAVs formation flight control based on following of the guidance points [C]//Proceedings of 2016 IEEE Chinese Guidance, 2016, Nanjing, China, Navigation and Control Conference.

[17]

MadhavanS, AntoniosT, BrianW. Co-operative path planning of multiple UAVs using Dubins paths with clothoid arcs [J]. Control Engineering Practice, 2010, 18: 1084-1092

[18]

HyondongO, SeungkeunK, AntoniosTCooperative road-network search planning of multiple UAVs using dubins paths [C]//AIAA Guidance, 2011, Oregon, Portland, Navigation, and Control Conference.

[19]

IsraelL, GerardoF, SergioSDubins path generation for a fixed wing UAV [C]//2014 International Conference on Unmanned Aircraft Systems (ICUAS), 2014339346

[20]

LiuX, PengZ, ChangY, ZhangLi. Multi-objective evolutionary approach for UAV cruise route planning to collect traffic information [J]. Journal of Central South University, 2012, 19: 3614-3621

[21]

LiY, ChenQ, HouZhong. Path following method with adaptive guidance length for unmanned aerial vehicles [J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(7): 1481-1490

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