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Popular navigation stacks implemented on top of open-source frameworks suchas ROS(Robot Operating System) and ROS2 represent the robot workspace using adiscretized 2D occupancy grid. This method, while requiring less computation,restricts the use of such navigation stacks to wheeled robots navigating onflat surfaces. In this paper, we present a navigation stack that uses avolumetric representation of the robot workspace, and hence can be extended toaerial and legged robots navigating through uneven terrain. Additionally, wepresent a new sampling-based motion planning algorithm which introduces abi-directional approach to the Batch Informed Trees (BIT*) motion planningalgorithm, whilst wrapping it with a strategy switching approach in order toreduce the initial time taken to find a path, in addition to the time taken tofind the shortest path.

ARC Nav -- A 3D Navigation Stack for Autonomous Robots