Abstract: Given the defects that the global static path planning algorithm cannot effectively avoid dynamic obstacles, and the local dynamic path planning algorithm lacks the guidance of global environmental information that the planning path quality is poor or cannot successfully reach the target point. A global dynamic path planning algorithm combining an improved ant colony algorithm and a dynamic window approach is proposed in this paper to realize the globally optimal path real-time planning in the dynamic environment. For the traditional ant colony algorithm, the improved strategies such as uneven and bidirectional distribution of the initial pheromone, increasing the difference of heuristic information between adjacent grids by introducing the increasing coefficient [A,] and considering the influence of turning times when selecting the optimal path are proposed. The distance evaluation sub-function and initial heading angle of the dynamic window approach are improved. The turning point of the globally optimal path planned by the improved ant colony algorithm is extracted as the sub-target point to guide the dynamic window method to carry out real-time dynamic path planning along the direction of the globally optimal path. Simulation experiments in different environments show that the global dynamic path planning algorithm proposed in this paper can effectively plan the globally optimal path while avoiding dynamic obstacles through real-time dynamic path planning.

Key words: improved ant colony algorithm, dynamic window approach, global dynamic path planning

摘要： 针对全局静态路径规划算法无法有效躲避动态障碍物、局部动态路径规划算法缺少全局环境信息指导规划路径质量差或无法成功到达目标点等问题，提出了一种结合改进蚁群算法和动态窗口法的全局动态路径规划算法，实现在动态环境中的全局最优路径实时规划。对传统蚁群算法提出了初始信息素不均匀、双向分布、引入放大系数[A]增大相邻栅格启发信息差异、选择最优路径时考虑转弯次数的影响等改进策略；改进动态窗口法的距离评价子函数和初始航向角；提取改进蚁群算法规划的全局最优路径的转折点作为子目标点来引导动态窗口法沿着全局最优路径方向进行实时动态路径规划。经过不同环境下的仿真实验结果表明，提出的全局动态路径规划算法可以通过实时动态路径规划实现有效躲避动态障碍物的同时规划全局最优路径。

关键词: 改进蚁群算法, 动态窗口法, 全局动态路径规划