Eric Frew
University of Colorado Boulder
Seminar Information
Room 479
Professor Frew will describe the design, analysis, implementation, and evaluation of new fast planning and control algorithms for small uncrewed aircraft systems. The ability to understand and predict the dynamic behavior of our environment over multiple scales remains an outstanding challenge at the intersection of science and engineering. New autonomous air mobility and sensing paradigms are enabling the shift from remote observation to in situ science in which autonomous systems actively assimilate data and explore. Ultra-fast planning and replanning algorithms enable online reasoning over orders of magnitude of temporal and spatial scales compared to existing approaches. Such reasoning can increase the safety, efficiency, resiliency, and affordability of future assured autonomous aviation platforms, systems, and networks. This presentation describes several key challenges to creating a dispersed autonomy architecture that reasons jointly over mobility, sensing, communication, and computation to move sensors and information to the best locations at the best times to make the best forecasts. A dispersed autonomy architecture will be introduced and main elements will be described. Targeted observation of the atmosphere is the motivating application but individual components generalize to a wide range of applications. Details will be discussed for a constant-time planning algorithm for complex motion in flow fields, for a learning-enhanced model predictive control approach, and for future extensions using hardware acceleration for ultra-fast performance.
Dr. Eric W. Frew is a professor in the Ann and H.J. Smead Aerospace Engineering Sciences Department. He received his B.S. in mechanical engineering from Cornell University in 1995 and his M.S and Ph.D. in aeronautics and astronautics from Stanford University in 1996 and 2003, respectively. Dr. Frew has been designing and deploying uncrewed aircraft systems for over twenty-five years. His research efforts focus on autonomous flight of heterogeneous uncrewed aircraft systems (UAS), guidance and control of uncrewed aircraft in complex atmospheric phenomena, optimal distributed information-gathering by autonomous robot teams, miniature self-deploying systems, and field robotics. Dr. Frew was co-leader of the team that performed the first-ever sampling of a severe supercell thunderstorm by an uncrewed aircraft. He is currently the Center Director for the National Science Foundation Industry / University Cooperative Research Center (IUCRC) for Autonomous Air Mobility and Sensing (CAAMS).