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Observability analysis of a vision-aided inertial navigation system using planar features on the ground
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
University of Minnesota, Minneapolis.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6855-5868
University of Minnesota, Minneapolis.
2013 (English)In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE conference proceedings, 2013, 4187-4194 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point feature are considered as state variables. In particular, we prove that the system has only three unobservable directions corresponding to global translations along the x and y axes, and rotations around the gravity vector. Hence, compared to general VINS, an advantage of using only ground features is that the vertical translation becomes observable. The findings of the theoretical analysis are validated through real-world experiments.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 4187-4194 p.
Series
IEEE International Conference on Intelligent Robots and Systems. Proceedings, ISSN 2153-0858
Keyword [en]
Downward looking, Gravity vectors, Inertial sensor, Observability analysis, Parameter vectors, Real world experiment, State variables, Vision-aided inertial navigation
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-124370DOI: 10.1109/IROS.2013.6696956ISI: 000331367404038Scopus ID: 2-s2.0-84893775956ISBN: 978-146736358-7 (print)OAI: oai:DiVA.org:kth-124370DiVA: diva2:634378
Conference
2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013; Tokyo; Japan; 3 November 2013 through 8 November 2013
Note

QC 20140130

Available from: 2013-06-30 Created: 2013-06-30 Last updated: 2014-04-10Bibliographically approved

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Jansson, Magnus

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