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Prediction Error Method Estimation for Simultaneous Localisation and Mapping
Saab AB, Linköping, Sweden .
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2016 (English)In: Proceedings of the 19th International Conference on Information Fusion (FUSION), July 4-8 2016., Institute of Electrical and Electronics Engineers (IEEE), 2016, 927-934 p.Conference paper (Refereed)
Abstract [en]

This paper presents a batch estimation method for Simultaneous Localization and Mapping (SLAM) using the Prediction Error Method (PEM). The estimation problem considers landmarks as parameter while treating dynamics using state space models. The gradient needed for parameter estimation is computed recursively using an Extended Kalman Filter (EKF). Results using simulations with a monocular camera and inertial sensors are presented and compared to a Nonlinear Least- Squares (NLS) estimator. The presented method produce both lower RMSE’s and scale better to the batch length. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016. 927-934 p.
Keyword [en]
SLAM, Optimization
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-130490OAI: oai:DiVA.org:liu-130490DiVA: diva2:951773
Conference
International Conference on Information Fusion (FUSION), Heidelberg, Germany, July 5-8 2016.
Projects
LINK-SIC
Funder
VINNOVA
Available from: 2016-08-10 Created: 2016-08-10 Last updated: 2016-08-19

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Sjanic, ZoranSkoglund, Martin A.
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