基于改进蚁群算法与Morphin算法的机器人路径规划方法

 针对动态复杂环境下的机器人路径规划问题,建立栅格地图模型,研究一种改进蚁群算法与Morphin 算法相结合的动态路径规划方法。改进蚁群算法引入拐点参数评价路径优劣,并对路径进行拐角处理以及变更拐角处信息素更新机制,使规划的全局路径更加平滑;Morphin 算法则在机器人行走时,根据全局路径的局部环境实时规划局部路径,使机器人有效地躲避障碍物。仿真试验结果表明,该方法结合全局规划与局部规划的特点,能够使机器人沿着一条短而平滑的最优路径快速、安全地到达目标点。

Robot path planning method based on improved ant colony algorithm and Morphin algorithm

A hybrid planning method combining an improved ant colony algorithm with Morphin algorithm is proposed for dynamic path planning for robot in complicated environment. Grid method is adopted to establish the model. The robot uses the improved ant colony algorithm for global path planning first, then uses Morphin algorithm for partial obstacle avoidance when it is marching on. The improved ant colony algorithm introduces an inflection point parameter to evaluate the path, so that the corner of the path is disposed and the updating mechanism of corner pheromone is changed. The Morphin algorithm is disposed with adjacent grid to meet the grid environments. This method combines the characteristics of global planning with local planning, which can not only realize real-time path planning according to the environment, but also guide the robot to the target with the global optimal path. Simulation results indicate that this method can make the robot avoid obstacles along a short and smooth path to quickly reach the target point.