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3D models are an essential part of many robotic applications. In applications where the environment is unknown a-priori, or where only a part of the environment is known, it is important that the 3D model can handle the unknown space efficiently. Path planning, exploration, and reconstruction all fall into this category. In this letter we present an extension to OctoMap which we call UFOMap. UFOMap uses an explicit representation of all three states in the map, i.e., unknown, free, and occupied. This gives, surprisingly, a more memory efficient representation. We provide methods that allow for significantly faster insertions into the octree. Furthermore, UFOMap supports fast queries based on occupancy state using so called indicators and based on location by exploiting the octree structure and bounding volumes. This enables real-time colored octree mapping at high resolution (below 1 cm). UFOMap is contributed as a C++ library that can be used standalone but is also integrated into ROS.

UFOMap: An Efficient Probabilistic 3D Mapping Framework That Embraces the Unknown