Planar-Based Visual Inertial Navigation: Observability Analysis and Motion Estimation
2015 (English)In: Journal of Intelligent and Robotic Systems, ISSN 0921-0296, E-ISSN 1573-0409, 1-23 p.Article in journal, Editorial material (Refereed) Published
In this paper, we address the problem of ego-motion estimation by fusing visual and inertial information. The hardware consists of an inertial measurement unit (IMU) and a monocular camera. The camera provides visual observations in the form of features on a horizontal plane. Exploiting the geometric constraint of features on the plane into visual and inertial data, we propose a novel closed form measurement model for this system. Our first contribution in this paper is an observability analysis of the proposed planar-based visual inertial navigation system (VINS). In particular, we prove that the system has only three unobservable states corresponding to global translations parallel to the plane, and rotation around the gravity vector. Hence, compared to general VINS, an advantage of using features on the horizontal plane is that the vertical translation along the normal of the plane becomes observable. As the second contribution, we present a state-space formulation for the pose estimation in the analyzed system and solve it via a modified unscented Kalman filter (UKF). Finally, the findings of the theoretical analysis and 6-DoF motion estimation are validated by simulations as well as using experimental data.
Place, publisher, year, edition, pages
Springer Netherlands, 2015. 1-23 p.
Visual-inertial navigation, Motion estimation, Observability analysis
IdentifiersURN: urn:nbn:se:kth:diva-141496DOI: 10.1007/s10846-015-0257-4ISI: 000373575500007ScopusID: 2-s2.0-84941357455OAI: oai:DiVA.org:kth-141496DiVA: diva2:698215
QC 201509282014-02-202014-02-172016-08-31Bibliographically approved