NDLI: A comparison of scale estimation schemes for a quadrotor UAV based on optical flow and IMU measurements

Content Provider	IEEE Xplore Digital Library
Author	Grabe, V. Bulthoff, H.H. Giordano, P.R.
Copyright Year	2013
Description	Author affiliation: Max Planck Inst. for Biol. Cybern., Tubingen, Germany (Grabe, V.; Bulthoff, H.H.) \|\| IRISA, Rennes, France (Giordano, P.R.)
Abstract	For the purpose of autonomous UAV flight control, cameras are ubiquitously exploited as a cheap and effective onboard sensor for obtaining non-metric position or velocity measurements. Since the metric scale cannot be directly recovered from visual input only, several methods have been proposed in the recent literature to overcome this limitation by exploiting independent `metric' information from additional onboard sensors. The flexibility of most approaches is, however, often limited by the need of constantly tracking over time a certain set of features in the environment, thus potentially suffering from possible occlusions or loss of tracking during flight. In this respect, in this paper we address the problem of estimating the scale of the observed linear velocity in the UAV body frame from direct measurement of the instantaneous (and non-metric) optical flow, and the integration of an onboard Inertial Measurement Unit (IMU) for providing (metric) acceleration readings. To this end, two different estimation techniques are developed and critically compared: a standard Extended Kalman Filter (EKF) and a novel nonlinear observer stemming from the adaptive control literature. Results based on simulated and real data recorded during a quadrotor UAV flight demonstrate the effectiveness of the approach.
Sponsorship	IEEE Ind. Electron. Soc.
Starting Page	5193
Ending Page	5200
File Size	1328477
Page Count	8
File Format	PDF
ISSN	21530858
DOI	10.1109/IROS.2013.6697107
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Estimation Cameras Vectors Acceleration Optical filters Optical sensors Nonlinear optics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications Computer Vision and Pattern Recognition Software

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