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FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges

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Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1151-1155.

Abstract

In [15], Montemerlo eta!. proposed an algorithm called Fa s tSLAM as an efficient and robust solution to the simultaneous localization and mapping problem. This paper describes a modified version of FastSLAM that overcomes important deficiencies of the original algorithm. We prove convergence of this new algorithm for linear SLAM problems and provide real-world experimental results that illustrate an order of magnitude improvement in accuracy over the original FastSLAM algorithm.

Michael Montemerlo, Sebastian Thrun, Daphne Koller, and Ben Wegbreit. 2003. FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03. IJCAI, 1151–1155. https://ijcai.org/proceedings/2003/164
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