Path Planning and Waypoints Optimization for Amphibious Vehicles Based on Improved A-Star Algorithm

Path planning for amphibious vehicles presents unique challenges due to the diverse and complex terrains they must navigate. Traditional A* algorithms, while effective in simpler environments, often yield suboptimal paths in multi-waypoint scenarios, resulting in inefficient and impractical routes. An improved A* path planning algorithm is presented in this paper, which integrates directional information from consecutive path segments and considers the vehicle's dynamic constraints. The proposed approach incorporates mechanisms for obstacle grid dilation and mandatory waypoint optimization, ensuring smoother transitions and enhanced navigability. Simulations conducted in a real-world environment demonstrate superior performance of the algorithm in terms of path length, number of inflection points, average turning angle, and computation time, compared to traditional methods. The results highlight the method's effectiveness in balancing path smoothness and computational efficiency, making it a viable solution for complex navigation tasks.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icus61736.2024.10839953
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Path Planning and Waypoints Optimization for Amphibious Vehicles Based on Improved A-Star Algorithm

Rui Song, Tianhong Chen, Yan Peng, Junxiong Pan
Robotic Path Planning Algorithms
article

Path Planning and Waypoints Optimization for Amphibious Vehicles Based on Improved A-Star Algorithm

Rui Song, Tianhong Chen, Yan Peng, Junxiong Pan
article en

Abstract

Path planning for amphibious vehicles presents unique challenges due to the diverse and complex terrains they must navigate. Traditional A* algorithms, while effective in simpler environments, often yield suboptimal paths in multi-waypoint scenarios, resulting in inefficient and impractical routes. An improved A* path planning algorithm is presented in this paper, which integrates directional information from consecutive path segments and considers the vehicle's dynamic constraints. The proposed approach incorporates mechanisms for obstacle grid dilation and mandatory waypoint optimization, ensuring smoother transitions and enhanced navigability. Simulations conducted in a real-world environment demonstrate superior performance of the algorithm in terms of path length, number of inflection points, average turning angle, and computation time, compared to traditional methods. The results highlight the method's effectiveness in balancing path smoothness and computational efficiency, making it a viable solution for complex navigation tasks.

Shanghai University (CN)
Sustainable cities and communities
Openalex Percentile: Top 74%
Robotic Path Planning Algorithms
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