The OctoMap library implements a 3D occupancy grid mapping approach, providing
data structures and mapping algorithms in C++ particularly suited for robotics.
The map implementation is based on an octree and is designed to meet the
following requirements:
* Full 3D model. The map is able to model arbitrary environments without prior
  assumptions about it. The representation models occupied areas as well as free
  space. Unknown areas of the environment are implicitly encoded in the map.
  While the distinction between free and occupied space is essential for safe
  robot navigation, information about unknown areas is important, e.g., for
  autonomous exploration of an environment.
* Updatable. It is possible to add new information or sensor readings at any
  time. Modeling and updating is done in a probabilistic fashion. This accounts
  for sensor noise or measurements which result from dynamic changes in the
  environment, e.g., because of dynamic objects.
* Flexible. The extent of the map does not have to be known in advance. Instead,
  the map is dynamically expanded as needed. The map is multi-resolution so
  that, for instance, a high-level planner is able to use a coarse map, while a
  local planner may operate using a fine resolution.
  close-up views.
* Compact. The map is stored efficiently, both in memory and on disk. It is
  possible to generate compressed files for later usage or convenient exchange
  between robots even under bandwidth constraints.

WWW: https://octomap.github.io/