Accession Number : ADA535663


Title :   Spectrally Queued Feature Selection for Robotic Visual Odometery


Corporate Author : ARMY TANK AUTOMOTIVE RESEARCH DEVELOPMENT AND ENGINEERING CENTER WARREN MI


Personal Author(s) : Pirozzo, David M ; Frederick, Philip A ; Hunt, Shawn ; Theisen, Bernard ; Del Rose, Mike


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a535663.pdf


Report Date : 23 Nov 2010


Pagination or Media Count : 12


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.


Descriptors :   *OPTICAL RADAR , *UNMANNED , *GROUND VEHICLES , HYPERSPECTRAL IMAGERY , AUTONOMOUS NAVIGATION , PATTERN RECOGNITION , DETECTORS , ROBOTICS


Subject Categories : Optical Detection and Detectors


Distribution Statement : APPROVED FOR PUBLIC RELEASE