Matthew Bays presents “Challenges and Opportunities within Maritime Autonomy and the Naval Surface Warfare Center, Panama City Division” as part of the IRIM Robotics Seminar Series. The event will be held in MiRC, Rooms 102 A&B from 11 a.m.–12 p.m. and is open to the public.
Interest in unmanned systems has increased considerably within the maritime domain and specifically the U.S. Navy over the last several decades. However, the littoral (shallow water) and undersea environments offer unique challenges resulting in the need for more autonomous, more reliable, and more modular unmanned systems than is often found in other domains. In this talk we will provide an overview of the particular challenges the U.S. Navy is attempting to solve within the littoral environment and solutions currently in development. We will provide a brief overview of the Naval Surface Warfare Center, Panama City Division and then discuss select projects related to our key autonomy thrust areas of payload autonomy, architecture design, behavior/algorithm development, and test/evaluation of autonomous systems to meet these challenges. Finally, we will provide an overview of multiple U.S. Navy and DoD opportunities for collaboration.
Dr. Matthew J. Bays is a research engineer and the Autonomy Group Lead for the Science & Technology Department of the Naval Surface Warfare Center, Panama City Division (NSWC PCD). He leads multiple investigations into using formal optimization methods and the development of novel software to solve problems of relevance to the U.S. Navy related to maritime autonomy. His active research projects include optimization of heterogeneous underwater sensor fields, automated scheduling for teams of unmanned systems performing mine countermeasure operations, and research into quickly deployable autonomy software. His research interests include optimization, path planning, statistical decision theory, and operations research.
Bays holds a B.S. in Mechanical Engineering from Cornell University (2007), and M.Eng. and Ph.D. in Mechanical Engineering from Virginia Tech (2009, 2012), focusing on robotics, systems, and control. He has extensive experience related to autonomy specific to mine countermeasure (MCM) and re-acquire & identify (RI) mission operations. At the Autonomous Systems & Controls Laboratory at Virginia Tech and in collaboration with NSWC PCD, he developed novel algorithms for efficient RI mission path planning that meet desired probability thresholds for proper classification. He has authored more than 20 publications in refereed journals and conferences, including in Ocean Engineering, the IEEE International Conference on Robotics and Automation, and the American Control Conference. These contributions are both theoretical and practical, with methods rigorously demonstrated with both mathematical proofs and implementation on U.S. Navy autonomous underwater vehicles.