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Octomap is a compact way to encode the environment about obstacles and even colors. These maps are very useful for self-localization, although not so much to navigate when the robot is on the ground and there are no obstacles in height that prevent the robot from passing through.

Source:
J. Ginés, F. Martín, V. Matellán, F. J. Lera, and J. Balsa, “Dynamics maps for long-term autonomy,” in 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Apr. 2017, pp. 85–90, doi: 10.1109/ICARSC.2017.7964057.