• 人工智能 •

### 融合改进A*蚁群和滚动窗口法的平滑路径规划

1. 1. 物联网技术应用教育部工程研究中心（江南大学 物联网工程学院），江苏 无锡 214122
2. 台州市产品质量安全检测研究院，浙江 台州 318000
• 出版日期:2021-10-01 发布日期:2021-09-30

### Smooth Path Planning Based on Improved A* Ant Colony and Rolling Window Method

YIN Shaowei, PENG Li, DAI Feifei

1. 1. Engineering Research Center of Internet of Things Technology Applications of the Ministry of Education, School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
2. Taizhou Institute of Product Quality and Safety Testing, Taizhou, Zhejiang 318000, China
• Online:2021-10-01 Published:2021-09-30

Abstract:

In order to solve the problems of deadlock, slow convergence, easy to get into local optimum and uneven path when ant colony algorithm is applied to the path planning of mobile robots, a smooth path planning method combining improved A* ant colony algorithm and the rolling window method is proposed. Firstly, the improved A* algorithm is used to initialize the ant colony pheromone to solve the problem of low ant colony efficiency. Then, the state transition probability function is improved to consider the feasible path “activity” and the end position in the function to avoid deadlock phenomenon. At the same time, based on the mechanism of inequality principle, the pheromone of ant colony is updated to avoid falling into the local optimal path and accelerate the convergence speed of the algorithm. Secondly, based on the global path planning, local real-time path planning is carried out by integ-rating the rolling window method and the dynamic obstacle avoidance strategy. Finally, Bessel curve is used to process the smoothness of the planned path, so that the smoothed path is closer to the actual motion path. In order to ensure the best performance of the algorithm, genetic algorithm with elite strategy is used to optimize the parameters of the algorithm. Three sets of experimental results show that the proposed algorithm is effective in the presence of simple or complex, static or dynamic obstacles.