基于改进蚁群算法的机器人全局路径规划研究

针对蚁群算法在机器人路径规划过程中出现的收敛速度慢的缺陷,提出了基于改进蚁群算法规划机器人全局路径,在栅格地图中划定优选区域,并建立新的初始信息素浓度设置模型,对各点初始信息素浓度进行差异化设置,避免寻优的盲目性,提高了算法的收敛速度。实验结果表明,改进后的蚁群算法的收敛速度明显加快,优于传统算法,表明了该算法的有效性。

Global path planning of robots based on improved ant colony algorithm

Aiming at the shortcomings of ant colony algorithm in robot path planning, this paper proposes a global path planning method of robots based on improved ant colony algorithm. This method delineates the preferred region in the grid map and establishes a new initial pheromone concentration setting model, differentiating the initial pheromone concentration at each point to avoid the blindness of optimization and improving the convergence speed of the algorithm. The experimental results show that the improved ant colony algorithm has significantly higher convergence rate than the traditional algorithm, verifying the effectiveness of the algorithm.