Editing Robotic mapping (section)

== Map representation ==
The internal representation of the map can be "metric" or "topological":<ref>[[Sebastian Thrun|Thrun, Sebastian]]. "[https://core.ac.uk/download/pdf/82741752.pdf Learning metric-topological maps for indoor mobile robot navigation]." Artificial Intelligence 99.1 (1998): 21-71.</ref> 
*The metric framework is the most common for humans and considers a two-dimensional space in which it places the objects. The objects are placed with precise coordinates. This representation is very useful, but is sensitive to noise and it is difficult to calculate the distances precisely.
*The topological framework only considers places and relations between them. Often, the distances between places are stored. The map is then a [[Graph (discrete mathematics)|graph]], in which the nodes corresponds to places and arcs correspond to the paths.

Many techniques use probabilistic representations of the map, in order to handle uncertainty.

There are three main methods of map representations, i.e., free space maps, object maps, and composite maps. These employ the notion of a grid, but permit the resolution of the grid to vary so that it can become finer where more accuracy is needed and more coarse where the map is uniform.