【摘要】 针对传统蚁群算法收敛速度较慢,易陷入局部最优,初始信息素匮乏等缺点,提出一种改进的蚁群算法。初始阶段在起点与终点的连线上额外增加信息素,提高算法的收敛速度;对原有启发函数中的启发因子进行改进,提高算法的寻优效率;改进了信息素浓度的挥发公式,使其服从高斯分布,使信息素挥发动态化。仿真结果表明:改进后的蚁群算法收敛速度更快,收敛性能更稳定,缩短了寻径距离,使机器人有效避开障碍物,在移动机器人路径规划方面有很好的实用性。更多还原

【Abstract】 Aiming at the shortcomings of traditional ant colony algorithm, such as slow convergence speed, easy to fall into local optimum, and lack of initial pheromone, an improved ant colony algorithm is proposed. In the initial stage, the pheromone is additionally added on the connecting line between the starting point and the ending point to improve the convergence speed of the algorithm; the heuristic factor in the original heuristic function is improved to improve the optimizing efficiency of the algorithm; and the volatilization formula of the pheromone concentration is improved, which let it obeys the Gaussian distribution and makes the pheromone volatilization dynamic.The simulation results show that the improved ant colony algorithm has faster convergence speed, more stable convergence performance, shortens the path-finding distance, and makes the robot effectively avoid obstacles, it has good practicality, in mobile robot path.更多还原