Multi-objective optimization in mobile robot path planning: a joint strategy of A* and simulated annealing algorithms

This paper proposes a novel optimization method for the A* algorithm to address the search efficiency problem in multi-objective path planning. The approach combines the A* algorithm with an annealing algorithm to enhance the quality and efficiency of path planning. Specifically, the traditional A* algorithm is improved by reducing the search direction, thereby decreasing the search space complexity and improving search efficiency. Additionally, an annealing algorithm is embedded within the A* framework. The annealing algorithm, based on the principle of simulated annealing, can avoid local optima by accepting inferior solutions with a certain probability. A series of experiments were conducted in a simulated environment, comparing the improved A* algorithm with other standard multi-objective path planning algorithms. The experimental results demonstrate the effectiveness of the proposed method in enhancing the quality of path planning.

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Published
2024-08-08
DOI
https://doi.org/10.1109/cis-ram61939.2024.10672742
Primary Topic
Robotic Path Planning Algorithms
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article
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article

Multi-objective optimization in mobile robot path planning: a joint strategy of A* and simulated annealing algorithms

Zihan Jiang, Rui Yang, Fumin Li
Robotic Path Planning Algorithms
article

Multi-objective optimization in mobile robot path planning: a joint strategy of A* and simulated annealing algorithms

Zihan Jiang, Rui Yang, Fumin Li
article en

Abstract

This paper proposes a novel optimization method for the A* algorithm to address the search efficiency problem in multi-objective path planning. The approach combines the A* algorithm with an annealing algorithm to enhance the quality and efficiency of path planning. Specifically, the traditional A* algorithm is improved by reducing the search direction, thereby decreasing the search space complexity and improving search efficiency. Additionally, an annealing algorithm is embedded within the A* framework. The annealing algorithm, based on the principle of simulated annealing, can avoid local optima by accepting inferior solutions with a certain probability. A series of experiments were conducted in a simulated environment, comparing the improved A* algorithm with other standard multi-objective path planning algorithms. The experimental results demonstrate the effectiveness of the proposed method in enhancing the quality of path planning.

Xi’an Jiaotong-Liverpool University (CN)
Sustainable cities and communities
Openalex Percentile: Top 85%
Robotic Path Planning Algorithms
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Multi-objective optimization in mobile robot path planning: a joint strategy of A* and simulated annealing algorithms — Zihan Jiang, Rui Yang, et al. · (2024) | TGRS Research Map | TGRS