The Graph SLAM Algorithm with Applications to Large-Scale Mapping of Urban Structures

Sebastian Thrun and Micheal Montemerlo

This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lower-dimensional problems that is then solved using conventional optimization techniques. As a result, GraphSLAM can generate maps with 108 or more features. The paper discusses a greedy algorithm for data association, and presents results for SLAM in urban environments with occasional GPS measurements.

The full paper is available in PDF

Bibtex Entry:

@ARTICLE{Thrun05,
  AUTHOR	= {Thrun, S. and Montemerlo, M.},
  TITLE		= {The {GraphSLAM} Algorithm With Applications to Large-Scale Mapping of Urban Structures},
  JOURNAL	= {International Journal on Robotics Research},
  YEAR		= {2005},
  VOLUME	= {25},
  NUMBER	= {5/6},
  PAGES		= {403--430}
}