Accession Number : ADA568672


Title :   Intelligent Behavioral Action Aiding for Improved Autonomous Image Navigation


Descriptive Note : Master's thesis


Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Eng, Kwee G


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a568672.pdf


Report Date : 13 Sep 2012


Pagination or Media Count : 111


Abstract : In egomotion image navigation, errors are common especially when traversing areas with few landmarks. Since image navigation is often used as a passive navigation technique in Global Positioning System (GPS) denied environments; egomotion accuracy is important for precise navigation in these challenging environments. One of the causes of egomotion errors is inaccurate landmark distance measurements, e.g., sensor noise. This research determines a landmark location egomotion error model that quantifies the effects of landmark locations on egomotion value uncertainty and errors. The error model accounts for increases in landmark uncertainty due to landmark distance and image centrality. A robot then uses the error model to actively orient to position landmarks in image positions that give the least egomotion calculation uncertainty. Two actions aiding solutions are proposed: (1) qualitative non-evaluative aiding action, and (2) quantitative evaluative aiding action with landmark tracking. Simulation results show that both action aiding techniques reduce the position uncertainty compared to no action aiding. Physical testing results substantiate simulation results. Compared to no action aiding, non-evaluative action aiding reduced egomotion position errors by an average 31.5%, while evaluative action aiding reduced egomotion position errors by an average 72.5%. Physical testing also showed that evaluative action aiding enables egomotion to work reliably in areas with few features, achieving 76% egomotion position error reduction compared to no aiding.


Descriptors :   *AUTONOMOUS NAVIGATION , ERRORS , IMAGES , NAVIGATION REFERENCE , POSITION FINDING , POSITION(LOCATION) , ROBOTS , THESES


Subject Categories : Navigation and Guidance


Distribution Statement : APPROVED FOR PUBLIC RELEASE