Path planning using Hybrid Routing Algorithm

The aim of this hybrid algorithm is to design and refine a path-finding technique that integrates A * (A-star) and Dijkstra's algorithms, enhancing the efficiency of route planning by utilizing the advantages of both approaches. The method applies the advantages of the two algorithms by adapting them according to the density of the environment. Dijkstra's algorithm is an optimal search algorithm that tries all possible paths to find the shortest path, but is resource-intensive in complex or large environments. The A *(A-star) algorithm optimizes performance by using heuristics to estimate the cost of reaching the goal, thus focusing on dependency and avoiding unnecessary computations. The hybrid strategy attempts to achieve performance and efficiency by combining A * 's efficiency in sparse setting and Dijkstra's extensive search in dense setting. Thus, it maximizes optimal path-finding while minimizing computational effort. Large-scale simulations were performed in MATLAB to compare the algorithm's performance in different environments with varying challenges. The comparison involves the evaluation of the efficiency, effectiveness, and computational complexity of the hybrid algorithm with respect to the standalone A * algorithm and Dijkstra's algorithm implementations.

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Publication Details

Published
2025-04-29
DOI
https://doi.org/10.1109/aimla63829.2025.11040851
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Path planning using Hybrid Routing Algorithm

N. Janarthanan, Pardeep Kumar, G Abishek, Gokul Vasan P
Robotic Path Planning Algorithms
article

Path planning using Hybrid Routing Algorithm

N. Janarthanan, Pardeep Kumar, G Abishek, Gokul Vasan P
article en

Abstract

The aim of this hybrid algorithm is to design and refine a path-finding technique that integrates A * (A-star) and Dijkstra's algorithms, enhancing the efficiency of route planning by utilizing the advantages of both approaches. The method applies the advantages of the two algorithms by adapting them according to the density of the environment. Dijkstra's algorithm is an optimal search algorithm that tries all possible paths to find the shortest path, but is resource-intensive in complex or large environments. The A *(A-star) algorithm optimizes performance by using heuristics to estimate the cost of reaching the goal, thus focusing on dependency and avoiding unnecessary computations. The hybrid strategy attempts to achieve performance and efficiency by combining A * 's efficiency in sparse setting and Dijkstra's extensive search in dense setting. Thus, it maximizes optimal path-finding while minimizing computational effort. Large-scale simulations were performed in MATLAB to compare the algorithm's performance in different environments with varying challenges. The comparison involves the evaluation of the efficiency, effectiveness, and computational complexity of the hybrid algorithm with respect to the standalone A * algorithm and Dijkstra's algorithm implementations.

Openalex Percentile: Top 87%
Robotic Path Planning Algorithms
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Path planning using Hybrid Routing Algorithm — N. Janarthanan, Pardeep Kumar, et al. · (2025) | TGRS Research Map | TGRS