Paper
14 May 2010 Control design for image tracking with an inertially stabilized airborne camera platform
Zdenek Hurák, Martin Rezáč
Author Affiliations +
Abstract
The paper reports on a few control engineering issues related to design and implementation of an image-based pointing and tracking system for an inertially stabilized airborne camera platform. A medium-sized platform has been developed by the authors and a few more team members within a joint governmental project coordinated by Czech Air Force Research Institute. The resulting experimental platform is based on a common double gimbal configuration with two direct drive motors and off-the-shelf MEMS gyros. Automatic vision-based tracking system is built on top of the inertial stabilization. Choice of a suitable control configuration is discussed first, because the decoupled structure for the inner inertial rate controllers does not extend easily to the outer imagebased pointing and tracking loop. It appears that the pointing and tracking controller can benefit much from availability of measurements of an inertial rate of the camera around its optical axis. The proposed pointing and tracking controller relies on feedback linearization well known in image-based visual servoing. Simple compensation of a one sample delay introduced into the (slow) visual pointing and tracking loop by the computer vision system is proposed. It relies on a simple modification of the well-known Smith predictor scheme where the prediction takes advantage of availability of the (fast and undelayed) inertial rate measurements.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zdenek Hurák and Martin Rezáč "Control design for image tracking with an inertially stabilized airborne camera platform", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76961H (14 May 2010); https://doi.org/10.1117/12.849902
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Cameras

Computing systems

Computer vision technology

Machine vision

Optical tracking

Visualization

Electroluminescence

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