Incremental Optimization of Large Robot-Acquired Maps

CSAIL Student Workshop Proceedings, 2005

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The heart of the SLAM problem is to determine the ``best'' map, the

physical locations of features such that the constraints have maximum

probability. We consider the case where the features are locations

visited by the robot; as shown by \cite{Montemerlo_2003}, positions of

other features can be efficiently computed once the robot trajectory

is known. In this paper, we present an algorithm for optimizing pose graphs that

is dramatically faster than the published state of the art.

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    AUTHOR     = {Edwin Olson},
    TITLE      = {Incremental Optimization of Large Robot-Acquired Maps},
    BOOKTITLE  = {CSAIL Student Workshop Proceedings},
    YEAR       = {2005},