Consistent map-based 3D localization on mobile devices

Ryan C. Dutoit, Joel A. Hesch, Esha D. Nerurkar, Stergios Roumeliotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations


In this paper, we seek to provide consistent, real-time 3D localization capabilities to mobile devices navigating within previously mapped areas. To this end, we introduce the Cholesky-Schmidt-Kalman filter (C-SKF), which explicitly considers the uncertainty of the prior map, by employing the sparse Cholesky factor of the map's Hessian, instead of its dense covariance-as is the case for the Schmidt-Kalman filter. By doing so, the C-SKF has memory requirements typically linear in the size of the map, as opposed to quadratic for storing the map's covariance. Moreover, and in order to bound the processing needs of the C-SKF (between linear and quadratic in the size of the map), we introduce two relaxations of the C-SKF algorithm: (i) The sC-SKF, which operates on the Cholesky factors of independent sub-maps resulting from dividing the map into overlapping segments. (ii) We formulate an efficient method for sparsifying the Cholesky factor by selecting and processing a subset of loop-closure measurements based on their temporal distribution. Lastly, we assess the processing and memory requirements of the proposed algorithms, and compare their positioning accuracy against other inconsistent map-based localization approaches that employ measurement-noise-covariance inflation to compensate for the map's uncertainty.

Original languageEnglish (US)
Title of host publicationICRA 2017 - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781509046331
StatePublished - Jul 21 2017
Event2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore
Duration: May 29 2017Jun 3 2017

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729


Other2017 IEEE International Conference on Robotics and Automation, ICRA 2017

Bibliographical note

Funding Information:
† R. C. Dutoit and S. I. Roumeliotis are with the Department of Computer Science, University of Minnesota {dutoit,stergios} ‡ J. A. Hesch and E. D. Nerurkar are with Google Inc. {joelhesch, eshanerurkar} This work was supported by Google, Project Tango.

Publisher Copyright:
© 2017 IEEE.


Dive into the research topics of 'Consistent map-based 3D localization on mobile devices'. Together they form a unique fingerprint.

Cite this