An Efficient and Unified Method for Extracting the Shortest Path from the Dubins Set

Path planning is crucial for the efficient operation of Autonomous Mobile Robots (AMRs) in factory environments. Many existing algorithms rely on Dubins paths, which have been adapted for various applications. However, an efficient method for directly determining the shortest Dubins path remains underdeveloped. This paper presents a comprehensive approach to efficiently identify the shortest path within the Dubins set. We classify the initial and final configurations into six equivalency groups based on the quadrants formed by their orientation angle pairs. Paths within each group exhibit shared topological properties, enabling a reduction in the number of candidate cases to analyze. This pre-classification step simplifies the problem and eliminates the need to explicitly compute and compare the lengths of all possible paths. As a result, the proposed method significantly lowers computational complexity. Extensive experiments confirm that our approach consistently outperforms existing methods in terms of computational efficiency.

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Publication Details

Published
2025-08-17
DOI
https://doi.org/10.1109/case58245.2025.11164160
Primary Topic
Data Management and Algorithms
Type
article
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article

An Efficient and Unified Method for Extracting the Shortest Path from the Dubins Set

Chao‐Bo Yan, Xuanhao Huang
Data Management and Algorithms
article

An Efficient and Unified Method for Extracting the Shortest Path from the Dubins Set

Chao‐Bo Yan, Xuanhao Huang
article en

Abstract

Path planning is crucial for the efficient operation of Autonomous Mobile Robots (AMRs) in factory environments. Many existing algorithms rely on Dubins paths, which have been adapted for various applications. However, an efficient method for directly determining the shortest Dubins path remains underdeveloped. This paper presents a comprehensive approach to efficiently identify the shortest path within the Dubins set. We classify the initial and final configurations into six equivalency groups based on the quadrants formed by their orientation angle pairs. Paths within each group exhibit shared topological properties, enabling a reduction in the number of candidate cases to analyze. This pre-classification step simplifies the problem and eliminates the need to explicitly compute and compare the lengths of all possible paths. As a result, the proposed method significantly lowers computational complexity. Extensive experiments confirm that our approach consistently outperforms existing methods in terms of computational efficiency.

Xi'an Jiaotong University (CN)
Openalex Percentile: Top 68%
Data Management and Algorithms
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