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# Multi-objective and Multi-constrained UAV Path Plan Optimum Selection Based on GRA*

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### Multi-objective and Multi-constrained UAV Path Plan Optimum Selection Based on GRA*

1. 1. The Journal of Grey System 1 (2011 ) 35-46 35 Multi-objective and Multi-constrained UAV Path Plan Optimum Selection Based on GRA* Hu Zhong-hua*, Zhao Min, Yao Min, Zhang Ke^ 1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China 2. College of Economics and Management, Nanjing University ofAeronautics and Astronautics, Nanjing, 210016, China Corresponding Author: E-mail: chzhualong@yahoo.com.cn Received January 2010 Abstract — To solve two-dimensional route planning problems of the Unmanned Aerial Vehicle (UAV), optimal decision-making system of UAV flight path is established. And optimal mathematical model of UAV flight path is also constructed. Grey relational analysis method is applied to deal with the gray relational information among the various indicators and to solve the model. Finally, the optimal model is used to plan optimum seeking for flight path planning problem with seventeen radar threat nodes, five missile threat nodes, ten artillery threat nodes and two climate threat nodes. The flight path with the best overall performance and minimum comprehensive cost was obtained and the research provides a theoretical basis for further study of the three-dimensional UAV flight path optimization. Keywords: Grey Relational Analysis (GRA); UAV; Path planning; Radar; Missile; Artillery.IntroductionUnmanned Aerial Vehicle (UAV) path plan optimum selection is the design of a flightpath from take-off area to the target area, and it must consider the fuel consumptionand avoid threats of radars, missiles, artilleries and climate, and then minimize theoverall comprehensive cost. Flight path planning is the most important part of UAV•This research is supported by the foundation of Aviation Science Fund (Project no: 2009ZC52041) and National Natural Science Foundation (Project no: 60974104).