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Research Article | Open Access |

Robot Path Planning Model Based on Improved A* Algorithm

Author 1: Jing Xie Author 2: Chunyuan Xu Author 3: Qianxi Yang
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 16, No. 5 · Published 2025

DOI: https://doi.org/10.14569/IJACSA.2025.0160523

Abstract

Robot path planning is a key technology for achieving autonomous navigation and efficient operation of robots. In order to improve the autonomous navigation capability of mobile robots, a global path planning model based on an improved A* algorithm and a local path planning model based on an improved artificial potential field method were designed. The results showed that the turns in the optimal path under the improved A* algorithm were 8, 5, 9, and 5, respectively. The improved artificial potential field method achieved a maximum planning time of 0.17s and a minimum planning time of 0.11s. The designed global and local path planning models for mobile robots have good performance and can provide technical support for improving the autonomous navigation capability of mobile robots for industrial manufacturing.

Keywords

How to Cite this Article

Xie, J., Xu, C., & Yang, Q. (2025). Robot Path Planning Model Based on Improved A* Algorithm. International Journal of Advanced Computer Science and Applications, 16(5). https://doi.org/10.14569/IJACSA.2025.0160523

Xie, Jing, et al.. "Robot Path Planning Model Based on Improved A* Algorithm." International Journal of Advanced Computer Science and Applications, vol. 16, no. 5, 2025, https://doi.org/10.14569/IJACSA.2025.0160523.

@article{Xie2025,
  title     = {Robot Path Planning Model Based on Improved A* Algorithm},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {5},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Jing Xie and Chunyuan Xu and Qianxi Yang},
  doi       = {10.14569/IJACSA.2025.0160523},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160523}
}

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