Realtime Implementation of Visual-aided Inertial Navigation Using Epipolar Constraints
2012 (English)In: 2012 IEEE/ION Position Location and Navigation Symposium (PLANS), IEEE , 2012, 711-718 p.Conference paper (Refereed)
A real-time implementation and the related theory of a visual-aided inertial navigation system are presented. The entire system runs on a standard laptop with off-the-shelf sensory equipment connected via standard interfaces. The visual-aiding is based on epipolar constraints derived from a finite visual memory. The navigational states are estimated with a squareroot sigma-point Kalman filter. An adaptive visual memory based on statistical coupling is presented and used to store and discard images selectively. Timing and temporal ordering of sensory data are estimated recursively. The computational cost and complexity of the system is described, and the implementation is discussed in terms of code structure, external libraries, and important parameters. Finally, limited performance evaluation results of the system are presented.
Place, publisher, year, edition, pages
IEEE , 2012. 711-718 p.
, IEEE - ION Position Location and Navigation Symposium, ISSN 2153-358X
Kalman filters, computational complexity, inertial navigation, sensors, statistical analysis
IdentifiersURN: urn:nbn:se:kth:diva-101707DOI: 10.1109/PLANS.2012.6236948ISI: 000309273900092ScopusID: 2-s2.0-84866236072ISBN: 978-1-4673-0385-9OAI: oai:DiVA.org:kth-101707DiVA: diva2:548760
2012 IEEE/ION Position Location and Navigation Symposium (PLANS),23-26 April 2012, Myrtle Beach, SC
FunderICT - The Next Generation
© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
QC 201210012012-10-012012-08-312013-11-05Bibliographically approved