Research on the Design of Flight Paths for Mountain Patrol Drones Based on Bionic Optimization Algorithms

With the rapid development of drone applications in mountain patrol, there is an increasing demand for intelligent flight capabilities of drones. This paper first established a Wolf Pack Optimization Algorithm (WPA) model and applied it to the design of flight paths for mountain patrol drones. Secondly, an Ant Colony Algorithm (ACA) model was constructed and utilized to determine the optimal flight path for the drones. Finally, the MATLAB simulation platform was employed to simulate and solve the flight paths under both algorithms. The computational results demonstrate that both optimization algorithm models were capable of determining the shortest flight paths for the drones. The simulation results validate the feasibility and effectiveness of these two intelligent bionic optimization algorithms, providing a solid foundation for subsequent system design and tuning.

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Publication Details

Published
2025-06-28
DOI
https://doi.org/10.1109/icipca65645.2025.11138146
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Research on the Design of Flight Paths for Mountain Patrol Drones Based on Bionic Optimization Algorithms

Qiurui Li, Ying Hao, Ke Tang
Robotic Path Planning Algorithms
article

Research on the Design of Flight Paths for Mountain Patrol Drones Based on Bionic Optimization Algorithms

Qiurui Li, Ying Hao, Ke Tang
article en

Abstract

With the rapid development of drone applications in mountain patrol, there is an increasing demand for intelligent flight capabilities of drones. This paper first established a Wolf Pack Optimization Algorithm (WPA) model and applied it to the design of flight paths for mountain patrol drones. Secondly, an Ant Colony Algorithm (ACA) model was constructed and utilized to determine the optimal flight path for the drones. Finally, the MATLAB simulation platform was employed to simulate and solve the flight paths under both algorithms. The computational results demonstrate that both optimization algorithm models were capable of determining the shortest flight paths for the drones. The simulation results validate the feasibility and effectiveness of these two intelligent bionic optimization algorithms, providing a solid foundation for subsequent system design and tuning.

Shandong University (CN)
Openalex Percentile: Top 77%
Robotic Path Planning Algorithms
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Research on the Design of Flight Paths for Mountain Patrol Drones Based on Bionic Optimization Algorithms — Qiurui Li, Ying Hao, et al. · (2025) | TGRS Research Map | TGRS