Modified Mayfly Algorithm for UAV Path Planning

The unmanned aerial vehicle (UAV) path planning problem is primarily concerned with avoiding collision with obstacles while determining the best flight path to the target position. This paper first establishes a cost function to transform the UAV route planning issue into an optimization issue that...

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Bibliographic Details
Published in:Drones (Basel) 2022-05, Vol.6 (5), p.134
Main Authors: Wang, Xing, Pan, Jeng-Shyang, Yang, Qingyong, Kong, Lingping, Snášel, Václav, Chu, Shu-Chuan
Format: Article
Language:English
Subjects:
adaptive Cauchy mutation
Aircraft
Algorithms
Animal reproduction
Collision avoidance
Configuration space path planning
Cost function
Drones
enhanced crossover operator
exponent decreasing inertia weight
Females
Ground stations
modified mayfly algorithm
Mutation
Operators (mathematics)
Optimization
path planning
Planning
Route planning
Unmanned aerial vehicles
Velocity
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Summary:The unmanned aerial vehicle (UAV) path planning problem is primarily concerned with avoiding collision with obstacles while determining the best flight path to the target position. This paper first establishes a cost function to transform the UAV route planning issue into an optimization issue that meets the UAV’s feasible path requirements and path safety constraints. Then, this paper introduces a modified Mayfly Algorithm (modMA), which employs an exponent decreasing inertia weight (EDIW) strategy, adaptive Cauchy mutation, and an enhanced crossover operator to effectively search the UAV configuration space and discover the path with the lowest overall cost. Finally, the proposed modMA is evaluated on 26 benchmark functions as well as the UAV route planning problem, and the results demonstrate that it outperforms the other compared algorithms.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones6050134