Share Email Print

Proceedings Paper

Spectrally queued feature selection for robotic visual odometery
Author(s): David M. Pirozzo; Philip A. Frederick; Shawn Hunt; Bernard Theisen; Mike Del Rose
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.

Paper Details

Date Published: 24 January 2011
PDF: 11 pages
Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 78780Q (24 January 2011); doi: 10.1117/12.876679
Show Author Affiliations
David M. Pirozzo, U.S. Army TARDEC (United States)
Philip A. Frederick, U.S. Army TARDEC (United States)
Shawn Hunt, U.S. Army TARDEC (United States)
Bernard Theisen, U.S. Army TARDEC (United States)
Mike Del Rose, U.S. Army TARDEC (United States)

Published in SPIE Proceedings Vol. 7878:
Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques
Juha Röning; David P. Casasent; Ernest L. Hall, Editor(s)

© SPIE. Terms of Use
Back to Top