Research on UAV 3D Path Planning with Improved A-Star Algorithm

The A-Star algorithm faces challenges in 3D path planning, such as low computational efficiency, high number of turning points, and non-smooth paths. Therefore, in view of the characteristics of small steering angle and need to maintain a safe distance from obstacles during the flight of UAVs, an enhanced version of the A-Star algorithm has been implemented for the 3D path planning of UAVs. Specifically, under the premise of adding obstacle virtual radius to ensure path safety, the search direction is primarily determined based on the positions of the start and target points, avoiding unnecessary expansion of nodes during the algorithm's search process. Additionally, for the extension search of waypoints, a variable step-size search strategy is proposed, utilizing the distance between waypoints and nearby threat points to determine the search step-size. A suitable flight path is planned by combining the A-Star algorithm enhancements with cubic B-spline curve smoothing. The simulation experiments of UAV 3D path planning indicate that the enhanced A-Star algorithm exhibits superior search effectiveness, reduced inflection points, and significant improvements.

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Publication Details

Published
2024-09-13
DOI
https://doi.org/10.1109/icacte62428.2024.10871252
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50

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article

Research on UAV 3D Path Planning with Improved A-Star Algorithm

Yibo Shu, Shurui Fan, Xiaoli Feng
2 citations
Robotic Path Planning Algorithms
0.50
article

Research on UAV 3D Path Planning with Improved A-Star Algorithm

Yibo Shu, Shurui Fan, Xiaoli Feng
article en
2 citations

Abstract

The A-Star algorithm faces challenges in 3D path planning, such as low computational efficiency, high number of turning points, and non-smooth paths. Therefore, in view of the characteristics of small steering angle and need to maintain a safe distance from obstacles during the flight of UAVs, an enhanced version of the A-Star algorithm has been implemented for the 3D path planning of UAVs. Specifically, under the premise of adding obstacle virtual radius to ensure path safety, the search direction is primarily determined based on the positions of the start and target points, avoiding unnecessary expansion of nodes during the algorithm's search process. Additionally, for the extension search of waypoints, a variable step-size search strategy is proposed, utilizing the distance between waypoints and nearby threat points to determine the search step-size. A suitable flight path is planned by combining the A-Star algorithm enhancements with cubic B-spline curve smoothing. The simulation experiments of UAV 3D path planning indicate that the enhanced A-Star algorithm exhibits superior search effectiveness, reduced inflection points, and significant improvements.

Hebei University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 32%
Robotic Path Planning Algorithms
0.50
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Research on UAV 3D Path Planning with Improved A-Star Algorithm — Yibo Shu, Shurui Fan, et al. · (2024) | TGRS Research Map | TGRS