一种蚂蚁遗传融合的机器人路径规划新算法

Novel Path Planning for Robots Syncretizing Ant Algorithm and Genetic Algorithm

针对栅格法建模的不足,本文研究一种全新的蚂蚁算法与遗传算法融合的机器人路径规划算法.该方法首先用栅格法建立机器人运动空间模型,在此基础上利用蚂蚁算法进行全局搜索得到全局导航路径,然后用遗传算法局部调节全局导航路径上的路径点,得到更优路径.计算机仿真实验表明,即使在复杂的环境下,利用本算法也可以规划出一条全局优化路径,且能安全避障.

A based on Ant Algorithm （AA） and Genetic algorithm（GA） for path planning of the robot is proposed. First the grid method is built to describe the working space of the mobile robot ,then the Ant algorithm is used to obtain the global navigation path, and the Genetic algorithm is adopted to get the better path. Computer experiment results demonstrate that this novel algorithm can plan an optimal path rapidly in a cluttered environment. The successful obstacle avoidance is achieved, and the model is robust and performs reliably.