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

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 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. KEY WORDS--SLAM, robot navigation, localization, mapping

• Type: Journal
• Year: 2006
• Where: IJRR
• Authors: Sebastian Thrun, Michael Montemerlo
• Keywords: IJRR 2006, Offline Slam Problem, Optimization Techniques, Slam Problems