论文标题
单元A*用于在部分已知环境中导航无人机
Cell A* for Navigation of Unmanned Aerial Vehicles in Partially-known Environments
论文作者
论文摘要
适当的路径计划是移动机器人强大而有效的自动导航的第一步。同时，在没有完整的事先信息的情况下，机器人在复杂的环境中工作仍然具有挑战性。本文介绍了A*搜索算法及其变体的扩展，以在处理长距离任务的同时，以较少的计算负担来使路径计划稳定。该算法能够在线搜索到定义的目标位置时，可以在线搜索无冲突和平滑的路径。本文将算法部署在自主无人机平台上，并将其在遥控车上实现以进行算法效率验证。
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.
