Semantic UFOMap : Semantic Information in Octree Occupancy Maps

Sammanfattning: Many autonomous robots operating in unknown and unstructured environments rely on building a dense 3D map of it during exploration. What tasks the robot can perform depends on the information stored in this map. Most 3D maps currently in use store information required for robot control and environment reconstruction – is this point in space occupied, or safe to navigate to? To enable more complex tasks additional information is required. We introduce Semantic UFOMap, an open-source octree based mapping framework designed for online use on limited hardware. Capable of real-time fusion and querying of semantic instances into the map – enabling high-level robot tasks and human-robot interaction. The online capabilities are evaluated using ground-truth data, where we show competitive results compared to voxel hashing, with optimizations still available. Additionally, we demonstrate a potential application with a simulated autonomous exploration and object navigation experiment. The evaluation shows that Semantic UFOMap is capable of real-time online performance. Storing semantic information in the map has the potential to open up new autonomous robot applications and yield improvements in existing tasks.