Popular navigation stacks implemented on top of open-source frameworks such as ROS(Robot Operating System) and ROS2 represent the robot workspace using a discretized 2D occupancy grid. This method, while requiring less computation, restricts the use of such navigation stacks to wheeled robots navigating on flat surfaces. In this paper, we present a navigation stack that uses a volumetric representation of the robot workspace, and hence can be extended to aerial and legged robots navigating through uneven terrain. Additionally, we present a new sampling-based motion planning algorithm which introduces a bi-directional approach to the Batch Informed Trees (BIT*) motion planning algorithm, whilst wrapping it with a strategy switching approach in order to reduce the initial time taken to find a path, in addition to the time taken to find the shortest path.
翻译:在开放源码框架(如ROS(机器人操作系统)和ROS2)之上执行的大众导航堆,它们代表了使用离散的 2D 占用网格的机器人工作空间。这种方法虽然需要较少的计算,但将这种导航堆的使用限制为在平坦表面航行的轮式机器人。在本文中,我们提出了一个导航堆,它使用机器人工作空间的体积代表,因此可以扩大到在不均匀的地形中航行的空中和腿式机器人。此外,我们提出了一个新的基于取样的运动规划算法,它引入了对批量知情树(BIT*)运动规划算法的双向方法,同时用战略转换法将其包起来,以便缩短寻找路径的最初时间,除了找到最短路径所需的时间之外。