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Friday, Dec. 11, 2020, 2:30 p.m.
Opto-mechanics: A vision of long-range manipulation enabled by subwavelength metamaterials and metasurfaces
In this MnRI Seminar Rewind, Dr. Ilic discusses his team's approach to engineer artificial materials with subwavelength structure—i.e., metamaterials and metasurfaces—that exhibit self-stabilizing mechanical behavior.
About Dr. Ognjen Ilic
Ognjen Ilic is a Benjamin Mayhugh Assistant Professor of Mechanical Engineering at the University of Minnesota, Twin Cities. He completed his Ph.D. in physics at MIT and was a postdoctoral scholar in applied physics and materials science at Caltech. His research themes encompass wave-matter interactions in nanoscale structures and low-dimensional materials. His recent awards include the 3M Non-Tenured Faculty Award and the Bulletin Prize of the Materials Research Society. More details can be found at z.umn.edu/ilic.
Friday, Dec. 4, 2020, 2:30 p.m.
Our oceans drive worldwide weather-climate systems; our rivers serve as nutrient conduits; and our marine ecosystems house the largest repository of biodiversity and mineral resources on the planet. Humans have relied on rivers, lakes, and oceans for transportation, energy generation, farming, and recreation throughout our history. And today, robots are critical tools in our stewardship of these resources. However, there are significant autonomy challenges when working in dynamic and uncertain environments like oceans and rivers. Robot dynamics are tightly coupled to those of the environment, while communication and localization are limited.
M. Ani Hsieh is a Research Associate Professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania. She is also the Deputy Director of the General Robotics, Automation, Sensing, and Perception (GRASP) Laboratory. Her research interests lie at the intersection of robotics, multi-agent systems, and dynamical systems theory. Hsieh and her team design algorithms for estimation, control, and planning for multi-agent robotic systems with applications in environmental monitoring, estimation and prediction of complex dynamics, and design of collective behaviors. She received her B.S. in Engineering and B.A. in Economics from Swarthmore College and her PhD in Mechanical Engineering from the University of Pennsylvania. Prior to Penn, she was an Associate Professor in the Department of Mechanical Engineering and Mechanics at Drexel University. Hsieh is the recipient of a 2012 Office of Naval Research (ONR) Young Investigator Award and a 2013 National Science Foundation (NSF) CAREER Award.
Friday, Dec. 4, 2020, 2:30 p.m.
Field imaging of flow and particle transport: how can robots help?
Presenting an exciting opportunity to integrate innovative flow and particle sensors with robots that can potentially revolutionize our field measurement approaches and open up space for a broad range of applications.
Friday, Nov. 20, 2020, 2:30 p.m.
Design and Manufacture of Multifunctional Yarns and Textiles
Highlighting recent advancements in the design and manufacture of yarns and textiles fabricated from shape memory alloys.
About Dr. Abel
Dr. Julianna Abel is a Benjamin Mayhugh Assistant Professor in the Department of Mechanical Engineering at the University of Minnesota. Dr. Abel earned her Ph.D. and M.S. in Mechanical Engineering from the University of Michigan and her B.S. from the University of Cincinnati. She is a NSF CAREER Award recipient, Toyota Programmable Systems Innovation Fellow, Glenn Research Center Faculty Fellow, and recently earned the 2020 ASME Ephrahim Garcia Best Paper Award. Her research combines innovative design processes and advanced manufacturing techniques with material and structural modeling to lay the scientific foundation necessary for the design of multifunctional yarns and textiles.
AEM Seminar: Enabling Robots to Cooperate with Distributed Optimization and Compete with Game Theory
Friday, Oct. 30, 2020, 2:30 p.m.
For robots to effectively operate in our world, they must master the skills of dynamic interaction. Autonomous cars must safely negotiate their trajectories with other vehicles and pedestrians as they drive to their destinations. UAVs must avoid collisions with other aircraft, as well as dynamic obstacles on the ground. Disaster response robots must coordinate to explore and map new disaster sites.
In this talk, Dr. Schwager will describe recent work in my lab using distributed optimization to obtain algorithms for robots to cooperate, and game-theoretic methods to obtain algorithms for robots to compete. He will describe a general and flexible method, called SOVA, for deriving distributed optimization algorithms for a variety of multi-robot collaborative problems. He will present an algorithm for fleets of autonomous cars to cooperatively track a large number of vehicles and pedestrians in a city, an algorithm for multiple robots to manipulate an object to a goal while avoiding collisions, and a distributed multi-robot SLAM algorithm, all derived using the SOVA method.
Additionally, Dr. Schwager will also discuss algorithms based on the theory of dynamic games, in which each actor has its own objective and constraints. I will describe examples in autonomous drone racing, car racing, and autonomous driving that use game theoretic principles to solve for Nash equilibrium trajectories in real-time, in a receding horizon fashion. Throughout the talk, he will show results from hardware experiments with ground robots, autonomous cars, and quadrotor UAVs collaborating and competing in the scenarios above.
About Dr. Schwager
Mac Schwager is an Assistant Professor of Aeronautics and Astronautics at Stanford University. He directs the Multi-robot Systems Lab (MSL) where he studies distributed algorithms for control, perception, and learning in groups of robots and autonomous systems. He is interested in a range of applications including cooperative surveillance with teams of UAVs, autonomous driving in traffic, cooperative robotic manipulation, distributed SLAM, distributed trajectory planning, and autonomous drone and car racing. He obtained his BS degree from Stanford, and his MS and PhD degrees from MIT. He was a postdoctoral researcher at the University of Pennsylvania and at MIT. Prior to joining Stanford, he was an assistant professor at Boston University from 2012 to 2015. He received the NSF CAREER award in 2014, the DARPA YFA in 2018, and has received numerous best paper awards in conferences and journals including the IEEE Transactions on Robotics best paper award in 2016, the Best Paper Award in Robot Manipulation in ICRA 2018, and the Best Paper Award in Multi-Robot Systems in ICRA 2020.
Friday, Oct. 23, 2020, 2:30 p.m.
Using technology to study disorders and shift neurodevelopment