中文摘要：

路径规划是机器人关键技术之一。利用改进的蚁群算法进行机器人的路径规划。针对传统蚁群算法收敛速度慢且易陷入局部最优解的缺陷,在Ant Colony System算法基础上,对每代蚁群动态随机统计分析,提取最优、平均和最差的蚂蚁信息,构成自适应算子用于局部信息素的自适应更新。仿真实验结果证明该自适应算子在平衡增加收敛速度和陷入局部最优解矛盾的问题中是有效的。

英文摘要：

Path planning is one of the key technologies of robot. In this paper, the improved ant colony algorithm is applied to robot path planning. Aiming at the shortcoming of traditional ant colony algorithm which is slow to converge and easy to fall into local optimum, the dynamic random statistical analysis of each ant colony is performed based on the Ant Colony System algorithm. The optimal, average and worst ant information are extracted to form an adaptive operator for the local pheromone adaptive updating. Simulation results show that the proposed adaptive operator is effective in solving the problem of increasing the convergence speed and falling into the local optimal solution.