基于改进蚁群算法的移动机器人路径规划

Mobile Robot Path Planning Based on Improved Ant Colony Algorithm

针对蚁群算法进行机器人路径规划时存在搜索空间大、效率低、容易陷入局部最优解、易出现死锁现象等问题,提出了一种改进的蚁群算法。在蚁群算法基础上,只对较优蚂蚁路径进行信息素浓度更新;针对U型障碍物,提出了蚂蚁回退策略,以及一些仿真实验策略改进。仿真结果表明:改进后蚁群算法能快速搜索到最优路径,有效避免死锁现象,与其它算法相比,具有良好的路径寻优能力与避障性能。

When the ant colony algorithm（ACA）is used in mobile robot path planning,there are many problems such as large search space、inefficiency、easy to fail into locale optima、prove to deadlock and so on,an improved ant colony algorithm for robot path planning.At first,on the basic of ACA,phenomenon concentrations are updates only for the ant paths;Then the ant back off strategy is put forward for the U type obstacle;last some improvements in simulation experiments.Experiments proof：the improved ACA can fast search to optimal path and it can effectively avoided the deadlock phenomenon,compared with others algorithm,it has good route optimization ability and obstacle avoidance performance.