<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"> <head> <meta http-equiv="Content-Type" content="text/html; charset=us-ascii"> <meta name="Generator" content="Microsoft Word 14 (filtered medium)"> <style></style> </head> <body lang="EN-US" link="blue" vlink="purple"> <div class="WordSection1"> RESEARCH SEMINAR<o:p></o:p> Resilient and Accurate Autonomous Vehicle Navigation via Signals of Opportunity<o:p></o:p> by<o:p></o:p> Zak Kassas, Assistant Professor of Electrical and Computer Engineering, University of California, Riverside<o:p></o:p> Director of the Autonomous Systems Perception, Intelligence, and Navigation (ASPIN) Laboratory.<o:p></o:p> <o:p> </o:p> Time & Place: Wednesday, November 16, 2016, 10:45-11:40am, ARC 321<o:p></o:p> <o:p> </o:p> Abstract:<o:p></o:p> The steady trend towards autonomous vehicles will come with a demand for full<o:p></o:p> situational awareness and extremely reliable and accurate navigation systems.<o:p></o:p> With no human in the loop, the cost of navigation system failure could be severe.<o:p></o:p> The vulnerability of GPS-only-based navigation has demonstrated the necessity<o:p></o:p> for a complementary navigation system. We propose a new navigation<o:p></o:p> framework that we call Collaborative Opportunistic Navigation. In this framework,<o:p></o:p> vehicle-mounted radios collaboratively draw relevant positioning and timing<o:p></o:p> information from ambient signals of opportunity (SOPs).<o:p></o:p> In this research, a number of radios with no a priori knowledge about their own<o:p></o:p> states are dropped in an environment comprising multiple unknown SOPs. The<o:p></o:p> radios draw pseudorange-type observations from the SOPs. The radios objective<o:p></o:p> is to build a high-fidelity signal landscape map of the environment within which<o:p></o:p> they localize themselves in space and time. Demonstrated research findings,<o:p></o:p> numerically and experimentally via specialized SOP-based navigation softwaredefined<o:p></o:p> radios mounted on ground vehicles and unmanned aerial vehicles<o:p></o:p> (UAVs) will be presented.<o:p></o:p> Bio:<o:p></o:p> Zak Kassas is an Assistant Professor of Electrical and Computer Engineering at<o:p></o:p> the University of California, Riverside and the Director of the Autonomous<o:p></o:p> Systems Perception, Intelligence, and Navigation (ASPIN) Laboratory. He<o:p></o:p> received a B.E. in E.E. from the Lebanese American University, an M.S. in<o:p></o:p> Electrical and Computer Engineering from The Ohio State University, and an<o:p></o:p> M.S.E. in Aerospace Engineering and a Ph.D. in Electrical and Computer<o:p></o:p> Engineering from The University of Texas at Austin. From 2004 through 2010 he<o:p></o:p> was a research and development engineer with the LabVIEW Control Design and<o:p></o:p> Dynamical Systems Simulation Group at National Instruments Corporation. He<o:p></o:p> has published over thirty refereed journal and conference articles, holds a U.S.<o:p></o:p> patent, and is a senior member of the IEEE. His research interests include cyberphysical<o:p></o:p> systems, navigation in GPS-challenged environments, autonomous<o:p></o:p> vehicles, target tracking, and intelligent transportation systems.<o:p></o:p> <o:p> </o:p> <o:p> </o:p> </div> </body> </html>

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