【摘要】 针对A＿Star(A*)算法路径规划存在转弯多、难以满足室内复杂场景应用等问题，提出了一种基于改进A*算法的全局路径规划新方法：首先，通过设计转弯惩罚因子改进了A*算法的启发式函数，以降低路径的转弯次数并提高算法的运行效率。其次，利用障碍物节点空间关联性改进了A*算法的邻域搜索函数，避免路径规划穿过障碍物，并保证路径规划结果的可用性。最后，在改进的A*算法中叠加路网状态信息，根据实时路网状态信息，驱动改进的A*算法实现动态路径规划，以增强算法对环境变化的适应能力。为了验证新方法的有效性，在室内开放环境和复杂环境下进行了路径规划对比试验，并在地图服务平台上进行了验证。实验结果显示，在室内开放空间场景下，新方法相对于A*算法，路径搜索耗时降低了26.28%,转弯次数降低了77.70%。在障碍物固定及障碍物动态变化场景下，地图服务平台能够利用新方法规划路径并避开障碍物，自适应调整路径，克服了A*算法在应对复杂障碍场景方面的不足。更多还原

【Abstract】 Aiming at the problems of many turns in the path planning of A＿Star(A*) algorithm, which was difficult to meet the application of indoor complex scenes, a new method of global path planning based on the improved A* algorithm was proposed: Firstly, the heuristic function of the A* algorithm was improved by designing the turning penalty factor to reduce the number of turns of the path and improved the operating efficiency of the algorithm. Secondly, the neighborhood search function of the A* algorithm was improved by using the spatial correlation of obstacle nodes to avoid path planning through obstacles and ensured the availability of path planning results. Finally, the road network status information was superimposed on the improved A* algorithm, and the improved A* algorithm was driven to realize dynamic path planning according to the real-time road network status information, so as to enhance the adaptability of the algorithm to environmental changes. In order to verify the effectiveness of the new method, a comparative experiment of path planning was carried out in indoor open environment and complex environment, and verified on the map service platform. The experimental results showed that in the indoor open space scene, the new method reduced the path search time by 26.28% and the number of turns by 77.70% compared with the A* algorithm. In the scene of fixed obstacles and dynamic changes of obstacles, the map service platform could use the new method to plan paths and avoid obstacles, and adjust paths adaptively, overcoming the shortcomings of the A* algorithm in dealing with complex obstacle scenes.更多还原