Improved Butterfly Optimization Algorithm Based Power Cable UAV Trajectory Optimization Algorithm

As a new type of power optical cable inspection technology, UAV (unmanned aerial vehicle) inspection can improve inspection efficiency and reduce risk, but the UAV inspection trajectory optimization algorithm in three-dimensional environment is inefficient and inspection precision is low. To address the above problems, an improved butterfly optimization algorithm-based trajectory optimization algorithm for electrical optical cable (IBOA-TOA) is proposed. The algorithm improves the equilibrium of the initial solution distribution through chaotic numbers, reduces the randomness of the algorithm's global and local search, and thus improves the convergence speed of the algorithm; defines the fitness function based on the maximum trajectory, the minimum trajectory segment, the distance to the power optical cable, and the minimum turning radius, to overcome the problem of the UAV inspecting precision; and adopts the B-spline to smooth the trajectory, and improves the usability of the final trajectory.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/itnec60942.2024.10733293
Primary Topic
Robotic Path Planning Algorithms
Type
article
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Improved Butterfly Optimization Algorithm Based Power Cable UAV Trajectory Optimization Algorithm

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72 links
Robotic Path Planning Algorithms
article

Improved Butterfly Optimization Algorithm Based Power Cable UAV Trajectory Optimization Algorithm

Qingrui Guo, Rentao Zhao, Adil Barat, Qinghua Zhang, Ning Li
article en

Abstract

As a new type of power optical cable inspection technology, UAV (unmanned aerial vehicle) inspection can improve inspection efficiency and reduce risk, but the UAV inspection trajectory optimization algorithm in three-dimensional environment is inefficient and inspection precision is low. To address the above problems, an improved butterfly optimization algorithm-based trajectory optimization algorithm for electrical optical cable (IBOA-TOA) is proposed. The algorithm improves the equilibrium of the initial solution distribution through chaotic numbers, reduces the randomness of the algorithm's global and local search, and thus improves the convergence speed of the algorithm; defines the fitness function based on the maximum trajectory, the minimum trajectory segment, the distance to the power optical cable, and the minimum turning radius, to overcome the problem of the UAV inspecting precision; and adopts the B-spline to smooth the trajectory, and improves the usability of the final trajectory.

State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 81%
Robotic Path Planning Algorithms
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