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.).

Text torma10a.pdf - Published Version Restricted to Registered users only Download (2MB)

Abstract

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

Update Item