Machine Learning for Robotics: High-Performance Flight Control in Unknown and Changing Conditions
Angela Schoellig is an Assistant Professor at the University of Toronto Institute for Aerospace Studies (UTIAS) and an Associate Director of the Centre for Aerial Robotics Research and Education (CARRE). With her team, she conducts research at the interface of robotics, controls and machine learning. Her goal is to enhance the performance, safety and autonomy of robots by enabling them to learn from past experiments and from each other. You can watch her robots, both aerial and ground vehicles, perform slalom races and flight dances athttps://www.youtube.com/user/angelaschoe.
She is the recipient of a 2017 Sloan Research Fellowship (as one of two in robotics in the US/Canada), a Ministry of Research, Innovation & Science Early Researcher Award, a Connaught New Researcher Award, and the Best Robotics Paper Award at CRV 2014. She is one of Robohub’s “25 women in robotics you need to know about (2013)”, winner of MIT’s Enabling Society Tech Competition, finalist of Dubai’s 2015 $1M “Drones for Good” competition, and youngest member of the 2014 Science Leadership Program, which promotes outstanding scientists in Canada. She has been a keynote speaker at various outreach events including TEDxUofT, Lift China, and the Girls Leadership in Engineering Experience weekend.
Angela received her Ph.D. from ETH Zurich (with Prof. Raffaello D’Andrea), and holds both an M.Sc. in Engineering Science and Mechanics from the Georgia Institute of Technology (Prof. Magnus Egerstedt) and a Masters degree in Engineering Cybernetics from the University of Stuttgart, Germany (Prof. Frank Allgower). Her Ph.D. was awarded the ETH Medal and the 2013 Dimitris N. Chorafas Foundation Award (as one of 35 worldwide).
Geoffrey Spedding (University of Southern California)
Professor, Aerospace & Mechanical Engineering
Old and New Problems in Low Reynolds Number Aerodynamics
Aeronautics is a mature and powerful discipline, and great success has been achieved in predicting flows and designing aircraft configurations at quite large scales, where the effects of viscosity can be modeled as minor modifications to basically inviscid dynamics. That is not the case at smaller scales, those of the new generation of drones, and of smaller birds and bats. Here the competing inertial and viscous terms lead to a delicate balance in solutions that have extreme sensitivity to variations in boundary and initial conditions. In this talk we will show how, in a Reynolds number regime that is only now becoming of practical interest, nominally simple problems do not necessarily have simple solutions, and how seemingly modest computational and experimental goals remain elusive.
Geoffrey Spedding received his Ph.D. in 1981 from the University of Bristol, England. He began work as a Research Associate in the Department of Aerospace Engineering at the University of Southern California in the same year, where he worked on models of insect wings and models of atmospheres and oceans. He became a full Professor in 2005, and Chair of the Aerospace and Mechanical Engineering Department in 2010. His current research has three themes: (i) Geophysical Fluids: particularly the evolution of turbulence in oceans and atmospheres, and its relation to the persistence of wakes of islands and submarines; (ii) Advanced imagining and data analysis including accurate particle imagining velocimetry (PIV) techniques and novel 2D wavelet transforms and interpolation routines for scattered data; (iii) Aerodynamics of small flying devices, especially those where birds and bats coexist in engineering design space. In 2010 he was elected Fellow of the American Physical Society. In 2013 he was awarded the Chaire Joliot at ESPCI, Paris.
Gretar Tryggvason (University of Notre Dame)
Viola D. Hank Professor
Chair, Aerospace & Mechanical Engineering
Direct Numerical Simulations of Complex Multiphase Flows
Direct numerical simulations (DNS), where every continuum length and time scale is fully resolved, allow us to follow the evolution of complex flows for sufficiently long time so that meaningful statistical quantities can be gathered. Results for relatively simple multifluid and multiphase systems with bubbles and drops in turbulent flows are now available, but new challenges are emerging. First of all, DNS of very large systems are yielding enormous amount of data that, in addition to providing physical insights, opens up new opportunities for the development of lower order models that describe the average or large-scale behavior. Recent results for bubbly flows and the application of statistical learning tools to extract closure models from the data suggest one possible strategy. Secondly, success with relatively simple systems calls for simulations of more complex problems. Multiphase flows often produce features such as thin films, filaments, and drops that are much smaller than the dominant flow scales and are often well-described by analytical or semi-analytical models. Recent efforts to combine semi-analytical models for thin films using classical thin film theory, and to compute mass transfer in high Schmidt number bubbly flows using boundary layer approximations, in combination with fully resolved numerical simulations of the rest of the flow, are described.
Gretar Tryggvason is the Viola D. Hank professor at the University of Notre Dame and the chair of the Department of Aerospace and Mechanical Engineering. He received his PhD from Brown University in 1985 and was on the faculty of the University of Michigan in Ann Arbor until 2000, when he moved to Worcester Polytechnic Institute as the head of the Department of Mechanical Engineering. He moved to the University of Notre Dame in 2010. Professor Tryggvason is well known for his contributions to computational fluid dynamics; particularly the development of methods for computations of multiphase flows and for pioneering direct numerical simulations of such flows. He served as the editor-in-chief of the Journal of Computational Physics 2002-2015, is a fellow of APS, ASME and AAAS, and the recipient of several awards, including the 2012 ASME Fluids Engineering Award.