A Framework for Simultaneous Localization and Mapping Utilizing Model Structure
2007 (English)In: Proceedings of the 10th International Conference on Information Fusion, 2007, 1-8 p.Conference paper (Refereed)
This contribution aims at unifying two recent trends in applied particle filtering (PF). The first trend is the major impact in simultaneous localization and mapping (SLAM) applications, utilizing the FastSLAM algorithm. The second one is the implications of the marginalized particle filter (MPF) or the Rao-Blackwellized particle filter (RBPF) in positioning and tracking applications. An algorithm is introduced, which merges FastSLAM and MPF, and the result is an MPF algorithm for SLAM applications, where state vectors of higher dimensions can be used. Results using experimental data from a 3D SLAM development environment, fusing measurements from inertial sensors (accelerometer and gyro) and vision are presented.
Place, publisher, year, edition, pages
2007. 1-8 p.
Rao-Blackwellized/marginalized particle filter, Sensor fusion, Simultaneous localization and mapping, Inertial sensors, Vision
IdentifiersURN: urn:nbn:se:liu:diva-38847DOI: 10.1109/ICIF.2007.4408198Local ID: 45862ISBN: 978-0-662-45804-3OAI: oai:DiVA.org:liu-38847DiVA: diva2:259696
10th International Conference on Information Fusion, Quebec, Canada, July, 2007