安全性A*算法融合动态窗口法的路径规划

针对移动机器人在路径寻优过程中，传统A*算法搜索效率差、所规划路径缺乏安全性、拐点多、转角大 且无法实现动态避障等问题，提出一种安全性A*算法和动态窗口法(dynamic window approach，DWA)结合的融合算 法。全局路径规划中，在传统A*算法的评价函数中引入安全估值，并拓展启发式搜索邻域和精简搜索方向；进行二 次路径优化，删除冗余节点，并平滑路径；运用改进的动态窗口评价函数，将安全性A*算法与动态窗口法融合实现 机器人沿全局路径行进中的动态避障。仿真实验结果表明：改进A*算法相比文献算法在路径长度上和拐角数量上平 均减少了2.39%和25%，并在动态复杂环境下验证了其动态避障效果，能满足机器人路径规划的实际需求，具有一 定的应用价值。

Path Planning Based on Security A* Algorithm and Dynamic Window Method

In the process of mobile robot path optimization, the traditional A * algorithm has some problems, such as poor search efficiency, lack of safety, many turning points, large turning angles and unable to achieve dynamic obstacle avoidance, etc. To solve these problems, this paper proposes a fusion algorithm which combines the safety A * algorithm with the dynamic window approach (DWA). In the global path planning, the safety estimation is introduced into the evaluation function of the traditional A * algorithm, and the heuristic search neighborhood is expanded and the search direction is simplified. Then, the secondary path optimization is carried out to delete redundant nodes and smooth the path. By using the improved dynamic window evaluation function, the safety A * algorithm and the dynamic window method are integrated to realize the dynamic obstacle avoidance of the robot along the global path. The simulation results show that the improved A * algorithm reduces the path length and the number of corners by 2. 39% and 25% on average compared with the literature algorithm, and verifies its dynamic obstacle avoidance effect in the dynamic complex environment, which can meet the actual needs of robot path planning and has certain application value.