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Proceedings Paper

A comparison of pose estimation techniques: hardware vs. video
Author(s): Brad Grinstead; Andreas Koschan; Mongi A. Abidi
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Paper Abstract

Robotic navigation requires that the robotic platform have an idea of its location and orientation within the environment. This localization is known as pose estimation, and has been a much researched topic. There are currently two main categories of pose estimation techniques: pose from hardware, and pose from video (PfV). Hardware pose estimation utilizes specialized hardware such as Global Positioning Systems (GPS) and Inertial Navigation Systems (INS) to estimate the position and orientation of the platform at the specified times. PfV systems use video cameras to estimate the pose of the system by calculating the inter-frame motion of the camera from features present in the images. These pose estimation systems are readily integrated, and can be used to augment and/or supplant each other according to the needs of the application. Both pose from video and hardware pose estimation have their uses, but each also has its degenerate cases in which they fail to provide reliable data. Hardware solutions can provide extremely accurate data, but are usually quite pricey and can be restrictive in their environments of operation. Pose from video solutions can be implemented with low-cost off-the-shelf components, but the accuracy of the PfV results can be degraded by noisy imagery, ambiguity in the feature matching process, and moving objects. This paper attempts to evaluate the cost/benefit comparison between pose from video and hardware pose estimation experimentally, and to provide a guide as to which systems should be used under certain scenarios.

Paper Details

Date Published: 27 May 2005
PDF: 8 pages
Proc. SPIE 5804, Unmanned Ground Vehicle Technology VII, (27 May 2005); doi: 10.1117/12.602963
Show Author Affiliations
Brad Grinstead, The Univ. of Tennessee/Knoxville (United States)
Andreas Koschan, The Univ. of Tennessee/Knoxville (United States)
Mongi A. Abidi, The Univ. of Tennessee/Knoxville (United States)

Published in SPIE Proceedings Vol. 5804:
Unmanned Ground Vehicle Technology VII
Grant R. Gerhart; Charles M. Shoemaker; Douglas W. Gage, Editor(s)

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