The graph SLAM algorithm with applications to large-scale mapping of urban structures
S Thrun, M Montemerlo - The International Journal of …, 2006 - journals.sagepub.com
S Thrun, M Montemerlo
The International Journal of Robotics Research, 2006•journals.sagepub.comThis 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 …
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 …
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.