Proper path planning is the first step of robust and efficient autonomous navigation for mobile robots. Meanwhile, it is still challenging for robots to work in a complex environment without complete prior information. This paper presents an extension to the A* search algorithm and its variants to make the path planning stable with less computational burden while handling long-distance tasks. The implemented algorithm is capable of online searching for a collision-free and smooth path when heading to the defined goal position. This paper deploys the algorithm on the autonomous drone platform and implements it on a remote control car for algorithm efficiency validation.

中文翻译：

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用于在部分已知环境中导航无人驾驶飞行器的 Cell A*

正确的路径规划是移动机器人稳健高效自主导航的第一步。同时，机器人在没有完整先验信息的复杂环境中工作仍然具有挑战性。本文提出了对 A* 搜索算法及其变体的扩展，以在处理长距离任务时使路径规划稳定，计算负担更小。实现的算法能够在前往定义的目标位置时在线搜索无碰撞且平滑的路径。本文将算法部署在自主无人机平台上，并在遥控车上实现算法效率验证。