Research and Simulation of the A* Algorithm in Matlab
DOI:
https://doi.org/10.54097/n2x2e183Keywords:
Matlab; Path planning; A* algorithm; Weighted A* algorithm; Dynamic A* algorithm.Abstract
With the rapid advancement of artificial intelligence and networking, path planning has found widespread applications across various domains, including artificial intelligence, mechanical control, robotics, and the automotive industry. The A* algorithm is a very common path-planning algorithm. Traditional research mainly focuses on the application of the A* algorithm and its combination with other algorithms, while neglecting the study of the A* algorithm itself, such as its heuristic function. This article will conduct an in-depth study of the A* algorithm using MATLAB, introduce the weighted A* and dynamic A* algorithm, and study the parameter influence and improvement of the A* algorithm. Research has shown that when the weight is greater than 1, it will reduce the optimality of the results; Smaller weights usually lead to better exploration, but the search process may slow down. The dynamic A* algorithm has many characteristics such as dynamic updates and reverse search. Therefore, this study is of great significance for improving the efficiency of path planning.
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[1] Duchoň, F., Babinec, A., Kajan, M., Beňo, P., Florek, M., Fico, T., & Jurišica, L. Path planning with modified a star algorithm for a mobile robot. Procedia Engineering, 2014, 96, 59-69. DOI: https://doi.org/10.1016/j.proeng.2014.12.098
[2] Ju, C., Luo, Q., & Yan, X. Path planning using an improved a-star algorithm. In 2020 11th International Conference on Prognostics and System Health Management (PHM-2020 Jinan) IEEE, 2020, pp. 23-26. DOI: https://doi.org/10.1109/PHM-Jinan48558.2020.00012
[3] Shi Y., Yang J., Bu S., Zhu L. Intelligent vehicle path planning algorithm based on improved RRT. Computing Technology and Automation, 2019, 38 (04): 81-86.
[4] Sariff, N., & Buniyamin, N. An overview of autonomous mobile robot path planning algorithms. In 2006 4th student conference on research and development. IEEE, 2006, pp. 183-188. DOI: https://doi.org/10.1109/SCORED.2006.4339335
[5] Bortoff, S. A. Path planning for UAVs. In Proceedings of the 2000 American Control Conference. IEEE. 2000, 1(6), pp. 364-368. DOI: https://doi.org/10.1109/ACC.2000.878915
[6] Wang, C., Wang, L., Qin, J., Wu, Z., Duan, L., Li, Z., et al. Path planning of automated guided vehicles based on improved A-Star algorithm. In 2015 IEEE International Conference on Information and Automation. IEEE, 2015, pp. 2071-2076. DOI: https://doi.org/10.1109/ICInfA.2015.7279630
[7] Tang, G., Tang, C., Claramunt, C., Hu, X., & Zhou, P. Geometric A-star algorithm: An improved A-star algorithm for AGV path planning in a port environment. IEEE Access, 2021, 9, 59196-59210. DOI: https://doi.org/10.1109/ACCESS.2021.3070054
[8] Erke, S., Bin, D., Yiming, N., Qi, Z., Liang, X., & Dawei, Z. An improved A-Star based path planning algorithm for autonomous land vehicles. International Journal of Advanced Robotic Systems, 2020, 17(5), 1729881420962263. DOI: https://doi.org/10.1177/1729881420962263
[9] Candra, A., Budiman, M. A., & Pohan, R. I. Application of a-star algorithm on pathfinding game. In Journal of Physics: Conference Series. 2021, 1898(1), p. 012047. DOI: https://doi.org/10.1088/1742-6596/1898/1/012047
[10] XiangRong, T., Yukun, Z., & XinXin, J. Improved A-star algorithm for robot path planning in static environment. In Journal of Physics: Conference Series. 2021, 1792(1), p. 012067. DOI: https://doi.org/10.1088/1742-6596/1792/1/012067
[11] Liu, L., Wang, B., & Xu, H. Research on path-planning algorithm integrating optimization A-star algorithm and artificial potential field method. Electronics, 2022, 11(22), 3660. DOI: https://doi.org/10.3390/electronics11223660
[12] Cui, S. G., Wang, H., Yang, L., A Simulation Study of A-star Algorithm for Robot Path Planning. 16th international conference on mechatronics technology, 2012, pp. 506-510.
[13] Duchoň, F., Huňady, D., Dekan, M., & Babinec, A. Optimal navigation for mobile robot in known environment. Applied Mechanics and Materials, 2013, 282, 33-38. DOI: https://doi.org/10.4028/www.scientific.net/AMM.282.33
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