Exploiting Ground Plane Constraints for Visual-Inertial Navigation
2012 (English)In: 2012 IEEE/ION Position Location and Navigation Symposium (PLANS), IEEE , 2012, 527-534 p.Conference paper (Refereed)
In this paper, an ego-motion estimation approach is introduced that fuses visual and inertial information, using a monocular camera and an inertial measurement unit. The system maintains a set of feature points that are observed on the ground plane. Based on matched feature points between the current and previous images, a novel measurement model is introduced that imposes visual constraints on the inertial navigation system to perform 6 DoF motion estimation. Furthermore, feature points are used to impose epipolar constraints on the estimated motion between current and past images. Pose estimation is formulated implicitly in a state-space framework and is performed by a Sigma-Point Kalman filter. The presented experiments, conducted in an indoor scenario with real data, indicate the ability of the proposed method to perform accurate 6 DoF pose estimation.
Place, publisher, year, edition, pages
IEEE , 2012. 527-534 p.
, IEEE - ION Position Location and Navigation Symposium, ISSN 2153-358X
Ego-motion estimation, vision-aided INS, ground plane feature detection, epipolar geometry
IdentifiersURN: urn:nbn:se:kth:diva-93895DOI: 10.1109/PLANS.2012.6236923ISI: 000309273900067ScopusID: 2-s2.0-84866233498ISBN: 978-146730386-6OAI: oai:DiVA.org:kth-93895DiVA: diva2:524620
2012 IEEE/ION Position, Location and Navigation Symposium, PLANS 2012; Myrtle Beach, SC; 23 April 2012 through 26 April 2012
FunderICT - The Next Generation
QC 201206182012-06-182012-05-022013-04-15Bibliographically approved