101. 融合蚁群-A*算法的移动机器人路径规划.
- Author
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马 军, 宋栓军, 韩军政, 熊继淙, 张周强, and 阎文利
- Subjects
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ANT algorithms , *SIMULATION software , *MOBILE robots , *PROBLEM solving - Abstract
When the path planning is carried out for the traditional ant colony algorithm, the convergence speed is slow and it is easy to fall into the “self-locking”, and it is not easy to find the optimal path. A fusion ant colony-A* algorithm is proposed to solve the problem. The evaluation function of A* algorithm is introduced to improve and adjust the heuristic function and pheromone update mode of traditional ant colony algorithm, and reduce the possibility of “self-locking”, so that the optimal path can be quickly found. Finally, experiments are carried out on MATLAB simulation software. The experimental results show that the proposed algorithm improves the convergence speed by nearly 40%, and the optimal paths in environmental models 1 and 2 are 35.670 6 m and 29.799 0 m better than the 39.799 0 m and 32.213 2 m of the ant colony algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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