
The Graph SLAM Algorithm with Applications to LargeScale Mapping of Urban Structures
Sebastian Thrun and Micheal MontemerloThis 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 loglikelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lowerdimensional 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 LargeScale Mapping of Urban Structures}, JOURNAL = {International Journal on Robotics Research}, YEAR = {2005}, VOLUME = {25}, NUMBER = {5/6}, PAGES = {403430} } 