The map is stored efficiently, both in memory and onĭisk. Scale from coarse overviews to detailed close-up views. This also allows for efficient visualizations which Is multi-resolution so that, for instance, a high-level planner isĪble to use a coarse map, while a local planner may operate using aįine resolution. Instead, the map is dynamically expanded as needed. The extent of the map does not have to be known inĪdvance. Furthermore, multiple robots areĪble to contribute to the same map and a previously recorded map is Measurements which result from dynamic changes in the environment,Į.g., because of dynamic objects. Modeling and updating is done inĪ probabilistic fashion. It is possible to add new information or sensor Unknown areas is important, e.g., for autonomous exploration of an Space is essential for safe robot navigation, information about While the distinction between free and occupied The representation models occupiedĪreas as well as free space. The map is able to model arbitrary environments The map implementation is based on an octree and is designed to meet the following OctoMap An Efficient Probabilistic 3D Mapping Framework Based on OctreesĪpproach, providing data structures and mapping algorithms in C++ particularly suited for robotics.
