Research on improved A* path planning method for agricultural unmanned aerial vehicles

Aiming at the characteristics of Xinjiang and Corps with a vast area and diverse terrain, traditional A* path planning for agricultural UAV suffers from drawbacks such as excessive redundant nodes, long search times, and non-smooth path planning. In response, a novel path planning method based on improved A* is proposed, tailored for agricultural UAV operations in Xinjiang. This method employs diagonal distance in three-dimensional space as heuristic function, incorporates dynamic weighting factor. It utilizes node reduction rules and cubic B-spline curves for secondary optimized path planning, effectively reduces search path length and enhances route search efficiency. Through simulation experiments, the superiority of the improved A* method in the three-dimensional environment of UAV is validated.

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Publication Details

Published
2025-06-30
DOI
https://doi.org/10.1117/12.3067051
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

Research on improved A* path planning method for agricultural unmanned aerial vehicles

Za Kan, Haifeng Yuan, Jingbin Li, Hewei Meng
Robotic Path Planning Algorithms
article

Research on improved A* path planning method for agricultural unmanned aerial vehicles

Za Kan, Haifeng Yuan, Jingbin Li, Hewei Meng
article en

Abstract

Aiming at the characteristics of Xinjiang and Corps with a vast area and diverse terrain, traditional A* path planning for agricultural UAV suffers from drawbacks such as excessive redundant nodes, long search times, and non-smooth path planning. In response, a novel path planning method based on improved A* is proposed, tailored for agricultural UAV operations in Xinjiang. This method employs diagonal distance in three-dimensional space as heuristic function, incorporates dynamic weighting factor. It utilizes node reduction rules and cubic B-spline curves for secondary optimized path planning, effectively reduces search path length and enhances route search efficiency. Through simulation experiments, the superiority of the improved A* method in the three-dimensional environment of UAV is validated.

Shihezi University (CN)
Zero hunger
Openalex Percentile: Top 87%
Robotic Path Planning Algorithms
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