A Markov-chain Monte Carlo approach to simultaneous localization and mapping

Torma, Péter and György, András and Szepesvári, Csaba (2010) A Markov-chain Monte Carlo approach to simultaneous localization and mapping. In: AISTATS 2010. Proceedings of The thirteenth international conference on artificial intelligence and statistics. Sardinia, 2010. (JMLR workshop and conference proceedings 9.).

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A Markov-chain Monte Carlo based algorithm is provided to solve the Simultaneous localization and mapping (SLAM) problem with general dynamics and observation model under open-loop control and provided that the map-representation is nite dimensional. To our knowledge this is the first provably consistent yet (close-to) practical solution to this problem. The superiority of our algorithm over alternative SLAM algorithms is demonstrated in a dicult loop closing situation.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Markov Chain Monte Carlo, Simultaneous Localization and Mapping, loop closing
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Depositing User: Eszter Nagy
Date Deposited: 12 Dec 2012 08:38
Last Modified: 12 Dec 2012 08:38
URI: https://eprints.sztaki.hu/id/eprint/6352

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