多层优化蚁群算法的移动机器人路径规划研究

针对地图环境建模以及蚁群算法存在的问题,提出了一种移动机器人路径规划的多层优化方法.首先对U型陷阱栅格区域进行凸化处理,避免前期搜索混乱;设计新的状态转移规则,解决常规蚁群规划的路径过于紧贴障碍物的问题;改进距离启发式函数,有效提高算法收敛速度;设计平滑启发函数,增加蚂蚁局部探索时直行的机率,提升初始路径平滑性;提出按路程长度和平滑程度分配信息素的更新原则,利用优质蚂蚁进行全局信息素更新,进一步提高算法收敛速度;利用最大最小蚂蚁策略,防止蚁群陷入局部最优;通过二次路径优化策略,去除多余冗余点,进一步提升路径平滑性.仿真及实验结果表明,该方法能为移动机器人规划出一条安全且综合性能较好的路径,为路径规划的求解提供了一种切实可行的方法.

Multi-layer optimal ant colony algorithm for mobile robots path planning study

A multi-layer optimization method for mobile robot path planning is proposed for the problems of map environment modeling and ant colony algorithm. In this method, firstly, the U-trap raster region is convexized to avoid the pre-search confusion, a new state transfer rule is designed to solve the problem that the path of conventional ant colony planning is too close to the obstacles, the distance heuristic function is improved to effectively improve the convergence speed of the algorithm, the smoothing heuristic function is designed to increase the chance of ants going straight when local exploration is performed to improve the initial path smoothing, the update principle is proposed to allocate pheromones according to the distance length and The update principle of pheromone assignment by distance and smoothness is proposed to further improve the convergence speed of the algorithm by using high-quality ants for global pheromone update, the maximum-minimum ant strategy is used to prevent the ant colony from falling into local optimum, the redundant points are removed by the secondary path optimization strategy to further improve the path smoothness. Simulation and experimental results show that the method can plan a safe and comprehensive path for the mobile robot, which provides a practical method for the solution of path planning.