UAV Path Planning based on Improved Whale optimization Algorithm

In order to solve the problem of path planning for Unmanned Aerial Vehicle (UAV) in complex battlefield environment, an improved whale optimization algorithm (IWOA) is proposed in this paper. The algorithm is improved by adding adaptive weights. Then, the linear convergence factor of the algorithm i...

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Bibliographic Details
Published in2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE) pp. 569 - 573
Main Authors Liu, Kun, Xv, Cheng, Huang, Daqing, Ye, Xinning
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.01.2021
Subjects
Algorithms
Convergence
inertia weight
nonlinear convergence factor
Optimization
Path planning
Simulation
UAV
Unmanned aerial vehicles
Whales
WOA
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Summary:In order to solve the problem of path planning for Unmanned Aerial Vehicle (UAV) in complex battlefield environment, an improved whale optimization algorithm (IWOA) is proposed in this paper. The algorithm is improved by adding adaptive weights. Then, the linear convergence factor of the algorithm is modified into a nonlinear convergence factor, which is beneficial to balance the global searching ability and local development ability. The simulation results show that the IWOA algorithm has better convergence than the other three algorithms.
DOI:10.1109/ICCECE51280.2021.9342329