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Willow Garage's office map as created by PR2
Willow Garage's office map as created by PR2
A SLAM (Simultaneous localization and mapping) is a technique used by robots and Autonomous vehicles to build a map within an unknown environment, or to update a map within a known environment, while keeping track of their current location. So basicly you attempt to build a map of your environment while moving, to identify where you are in relation to your sorroundings.

In recent years, the success of single-robot SLAM has led to more multi-robot SLAM (MR-SLAM) research. A team of robots with MR-SLAM can explore an environment more efficiently and reliably.

SLAM can be thought of as a chicken and egg problem: An accurate map is needed for localization while a absolute pose estimate is needed to build that map. This is the starting condition for iterative process. The complexity of the technical processes of locating and mapping under conditions of errors and noise do not allow for a coherent solution of both tasks. Simultaneous localization and mapping (SLAM) is a concept that binds these processes in a loop and therefore supports the continuity of both aspects in separated processes; iterative feedback from one process to the other enhances the results of both consecutive steps.

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