Computer Science ›› 2021, Vol. 48 ›› Issue (12): 304-311.doi: 10.11896/jsjkx.201000021

• Artificial Intelligence • Previous Articles     Next Articles

Three-dimensional Path Planning of UAV Based on Improved Whale Optimization Algorithm

GUO Qi-cheng1,2, DU Xiao-yu1,3, ZHANG Yan-yu1,2, ZHOU Yi1,2   

  1. 1 School of Computer and Information Engineering,Henan University,Kaifeng,Henan 475004,China
    2 International Joint Research Laboratory for Cooperative Vehicular Networks of Henan,Kaifeng,Henan 475004,China
    3 Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,Henan 475004,China
  • Received:2020-10-05 Revised:2021-04-07 Online:2021-12-15 Published:2021-11-26
  • About author:GUO Qi-cheng,born in 1995,master's degree.His main research interests include collaborative technology of internet of vehicles.
    DU Xiao-yu,born in 1979,Ph.D,asso-ciate professor,master supervisor.Her main research interests include wireless sensor network positioning and cove-rage technology.
  • Supported by:
    National Natural Science Foundation of China(61701170) and Programs for Science and Technology Development of Henan Province(202102210327).

Abstract: The three-dimensional path planning of UAVs is a relatively complex global optimization problem.Its goal is to obtain the optimal or close to optimal flight path considering threats and constraints.Aiming at the problems of whale algorithm in the three-dimensional trajectory planning of UAVs,it is easy to fall into the local optimum,and the convergence speed is slow,and the convergence accuracy is not high enough.A whale optimization algorithm based on Lévy flight is proposed to solve the pro-blem of UAV three-dimensional path planning.In the iterative process of the algorithm,Levy flight is added to randomly disturb the optimal solution;an information exchange mechanism is introduced to update the individual's position through the current global optimal solution,the individual memory optimal solution and the neighborhood optimal solution;better trade-offs local convergence and global development.The simulation results show that the path planning algorithm proposed in this paper can effectively avoid the threat zone,the convergence speed is faster,the convergence accuracy is higher,and it is less likely to fall into the local optimal solution.When the number of iterations is 300 and the number of populations is 50,the cost function value obtained by the LWOA algorithm is 91.1% of the PSO algorithm,92.1% of the GWO algorithm,95.9% of the WOA algorithm,and the track cost is smaller.

Key words: Heuristic algorithm, Information exchange mechanism, Lévy flight, Three-dimensional path planning, Whale optimization algorithm

CLC Number: 

  • TP301
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