Vision based collaborative localization for multirotor vehicles

Sai Vemprala, Srikanth Saripalli

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

6 Scopus citations

Abstract

We present a framework for vision based localization for two or more multirotor aerial vehicles relative to each other. This collaborative localization technique is built upon a relative pose estimation strategy between two or more cameras with the capability of estimating accurate metric poses between each other even through fast motion and continually changing environments. Through synchronized feature detection and tracking with a robust outlier rejection process, classical multiple view geometry concepts have been utilized for obtaining scale-ambiguous relative poses, which are then refined through reconstruction and pose optimization to provide a metric estimate. Furthermore, we present the implementation details of this technique followed by a set of results which involves evaluation of the accuracy of the pose estimates through test cases in both simulated and real experiments. Test cases include keeping one camera stationary as the other is mounted on a quadrotor which is then flown through various types of trajectories. We also perform a quantitative comparison with a GPS/IMU localization technique to demonstrate the accuracy of our method.

Original languageEnglish (US)
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1653-1658
Number of pages6
Volume2016-November
ISBN (Electronic)9781509037629
DOIs
StatePublished - Nov 28 2016
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: Oct 9 2016Oct 14 2016

Other

Other2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
CountryKorea, Republic of
CityDaejeon
Period10/9/1610/14/16

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Vemprala, S., & Saripalli, S. (2016). Vision based collaborative localization for multirotor vehicles. In IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 2016-November, pp. 1653-1658). [7759266] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2016.7759266