Voxel Map to Occupancy Map Conversion Using Free Space Projection for Efficient Map Representation for Aerial and Ground Robots

This article introduces a novel method for converting 3D voxel maps, commonly utilized by robots for localization and navigation, into 2D occupancy maps for both autonomous aerial vehicles (AAVs) and autonomous ground vehicles (AGVs). The generated 2D maps can be used for more efficient global navigation for both AAVs and AGVs, in enabling algorithms developed for 2D maps to be useful in 3D applications, and allowing for faster transfer of maps between multiple agents in bandwidth-limited scenarios. During the 3D to 2D map conversion, the method conducts safety checks with respect to the robot's safety margins. This ensures that an aerial or ground robot can navigate safely, relying primarily on the 2D map generated by the method. Additionally, the method extracts the height of navigable free space and a local estimate of the slope of the floor from the 3D voxel map. The height data is utilized in converting paths generated using the 2D map into paths in 3D space for both AAVs and AGVs. The slope data identifies areas too steep for a ground robot to traverse, marking them as occupied, thus enabling a more accurate representation of the terrain for ground robots. The proposed method is compared to the existing state-of-the-art fixed projection method in two different environments, over static maps and with progressively expanding maps. The methods proposed in this article have been implemented in the widely-used robotics frameworks ROS and ROS2, and are open-sourced.