UAVs flight path optimization based on intelligent bionic optimization algorithm

With the rapid development and integration of the field of UAVs and artificial intelligence, it is necessary to carry out follow-up research for the research on the intelligent flight path of UAVs. In this paper, firstly, a particle swarm optimization (PSO) model was established to study the flight trajectory of the UAV. Secondly, the genetic algorithm (GA) model was established, and the GA model was integrated with the UAV flight trajectory model, and then the overall solution calculation was carried out. Finally, the MATLAB simulation platform was used to simulate the UAV flight trajectory under the two algorithms, and through the solution calculation of the UAV flight path under the two algorithms, the path under the PSO can be obtained to be 161.7343, and the path under the GA can be 217.7843.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/icetci64844.2025.11084200
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28
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article

UAVs flight path optimization based on intelligent bionic optimization algorithm

Shi-Liang Zhu
1 citations
Robotic Path Planning Algorithms
1.28
article

UAVs flight path optimization based on intelligent bionic optimization algorithm

Shi-Liang Zhu
article en
1 citations

Abstract

With the rapid development and integration of the field of UAVs and artificial intelligence, it is necessary to carry out follow-up research for the research on the intelligent flight path of UAVs. In this paper, firstly, a particle swarm optimization (PSO) model was established to study the flight trajectory of the UAV. Secondly, the genetic algorithm (GA) model was established, and the GA model was integrated with the UAV flight trajectory model, and then the overall solution calculation was carried out. Finally, the MATLAB simulation platform was used to simulate the UAV flight trajectory under the two algorithms, and through the solution calculation of the UAV flight path under the two algorithms, the path under the PSO can be obtained to be 161.7343, and the path under the GA can be 217.7843.

Zhejiang Gongshang University (CN)
Affordable and clean energy
Openalex Percentile: Top 18%
Robotic Path Planning Algorithms
1.28
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