Research on hexagonal grid off-road path planning algorithm considering multiple factors

Abstract This article proposes a hexagonal grid off-road path planning algorithm that takes into account multiple factors for the path planning problem of motor vehicles in complex off-road environments. This method first uses a hexagonal grid model to abstract and quantify the terrain factors that affect off-road vehicles. Then, the Analytic Hierarchy Process is used to determine the weight of each factor on the impact of off-road vehicle traffic. Finally, by comprehensively considering the elevation, slope, and surface coverage elements, as well as the search efficiency of the algorithm, the cost function and heuristic function of the A * algorithm are further designed and optimized. The experimental results show that the method proposed in this paper outperforms existing algorithms in terms of pathfinding results and search efficiency, thus verifying the effectiveness and feasibility of the algorithm proposed in this paper.

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Publication Details

Journal
Journal of Physics Conference Series
Published
2024-10-01
DOI
https://doi.org/10.1088/1742-6596/2863/1/012030
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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Research on hexagonal grid off-road path planning algorithm considering multiple factors

Rui Liang, Ming Chang, Zhixin Zhang, Xi Zhao et al.
1 citations
Journal of Physics Conference Series
Robotic Path Planning Algorithms
0.25
article

Research on hexagonal grid off-road path planning algorithm considering multiple factors

Rui Liang, Ming Chang, Zhixin Zhang, Xi Zhao, Yunbo Kong
article en
1 citations

Abstract

Abstract This article proposes a hexagonal grid off-road path planning algorithm that takes into account multiple factors for the path planning problem of motor vehicles in complex off-road environments. This method first uses a hexagonal grid model to abstract and quantify the terrain factors that affect off-road vehicles. Then, the Analytic Hierarchy Process is used to determine the weight of each factor on the impact of off-road vehicle traffic. Finally, by comprehensively considering the elevation, slope, and surface coverage elements, as well as the search efficiency of the algorithm, the cost function and heuristic function of the A * algorithm are further designed and optimized. The experimental results show that the method proposed in this paper outperforms existing algorithms in terms of pathfinding results and search efficiency, thus verifying the effectiveness and feasibility of the algorithm proposed in this paper.

Journal of Physics Conference SeriesVol. 2863(1)
Beijing Satellite Navigation Center (CN), Smart Material (Germany) (DE)
Openalex Percentile: Top 46%
Robotic Path Planning Algorithms
0.25
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