Detecting and dealing with hovering maneuvers in vision-aided inertial navigation systems

Dimitrios G. Kottas, Kejian J. Wu, Stergios Roumeliotis

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

20 Scopus citations

Abstract

In this paper, we study the problem of hovering (i.e., absence of translational motion) detection and compensation in Vision-aided Inertial Navigation Systems (VINS). We examine the system's unobservable directions for two common hovering conditions (with and without rotational motion) and propose a robust motion-classification algorithm, based on both visual and inertial measurements. By leveraging our observability analysis and the proposed motion classifier, we modify existing state-of-the-art filtering algorithms, so as to ensure that the number of the system's unobservable directions is minimized. Finally, we validate experimentally the proposed modified sliding window filter, by demonstrating its robustness on a quadrotor with rapid transitions between hovering and forward motions, within an indoor environment.

Original languageEnglish (US)
Title of host publicationIROS 2013
Subtitle of host publicationNew Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
Pages3172-3179
Number of pages8
DOIs
StatePublished - Dec 1 2013
Event2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan
Duration: Nov 3 2013Nov 8 2013

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
CountryJapan
CityTokyo
Period11/3/1311/8/13

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