A comparative analysis of tightly-coupled monocular, binocular, and stereo VINS

Mrinal K. Paul, Kejian Wu, Joel A. Hesch, Esha D. Nerurkar, Stergios I. Roumeliotis

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

32 Scopus citations

Abstract

In this paper, a sliding-window two-camera vision-aided inertial navigation system (VINS) is presented in the square-root inverse domain. The performance of the system is assessed for the cases where feature matches across the two-camera images are processed with or without any stereo constraints (i.e., stereo vs. binocular). To support the comparison results, a theoretical analysis on the information gain when transitioning from binocular to stereo is also presented. Additionally, the advantage of using a two-camera (both stereo and binocular) system over a monocular VINS is assessed. Furthermore, the impact on the achieved accuracy of different image-processing frontends and estimator design choices is quantified. Finally, a thorough evaluation of the algorithm's processing requirements, which runs in real-time on a mobile processor, as well as its achieved accuracy as compared to alternative approaches is provided, for various scenes and motion profiles.

Original languageEnglish (US)
Title of host publicationICRA 2017 - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages165-172
Number of pages8
ISBN (Electronic)9781509046331
DOIs
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

Other

Other2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Country/TerritorySingapore
CitySingapore
Period5/29/176/3/17

Bibliographical note

Funding Information:
†This work was supported by Google, Project Tango. M. K. Paul and S. I. Roumeliotis are with the Department of Computer Science and Engineering, Univ. of Minnesota, Minneapolis, MN, USA. {paulx152,stergios}@umn.edu K. Wu is with the Department of Electrical and Computer Engineering, Univ. of Minnesota, Minneapolis, MN, USA. kejian@cs.umn.edu J. A. Hesch and E. D. Nerurkar are with Project Tango, Google, Mountain View, CA, USA. {joelhesch, eshanerurkar}@google.com

Publisher Copyright:
© 2017 IEEE.

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