Special Robotics Seminar: John Baras, "Trusted Autonomy: Theory and Applications"

Friday, February 26, 2021
2:00 p.m.
Online seminar. Registration is required.

Registration Link: https://umd.zoom.us/webinar/register/WN_pcq5TLooQD6KLnc5GUzDKQ

Lockheed Martin Robotics Seminar

Trusted Autonomy: Theory and Applications 

John S. Baras
Lockheed Martin Chair in Systems Engineering
Distinguished University Professor
Electrical and Computer Engineering
The Institute for Systems Research
Mechanical Engineering
Fischell Department of Bioengineering
Maryland Robotics Center
University of Maryland
College Park, MD 


Autonomous systems (e.g. robots, cars, UAVs) are becoming ubiquitous rapidly. They are also  increasingly interacting with humans. Safety is a critical and indispensable requirement for  autonomous systems and for their interactions with humans. Trusted autonomy is essential for  autonomy. It encompasses self-monitoring, self-adjustment, learning to accomplish safe and high performance complex task execution in time varying, complex and unknown environments. I will  describe our approach to these challenging problems via a methodology that utilizes dynamical  systems, optimization, formal models (timed automata, model checking, contracts), and novel  approaches to learning and monitoring. I will illustrate the results in diverse applications including  teaching robots manipulation tasks, autonomous cars, human-robot collaboration, collaborative  UAVs, communication network automation, health care management, smart manufacturing. A key  ingredient of the methodology is the development of efficient formal models of tasks and missions  and associated safety monitoring methods that combine timed automata and reachability analysis.  I will also illustrate why such formal task models are indispensable in executing tasks by different  robots, learned in different environments. Two fundamental and universally applicable  methodologies will be described: one based on multi-criteria constrained optimization with  numerical and logical variables, and one integrating formal logic with constraint-based reasoning  and optimization methods. I will close with future research directions and challenges including the  fundamental need for systems science and engineering methodologies and software tool suites.


John S. Baras is a Distinguished University Professor, holding the Lockheed Martin Chair in  Systems Engineering and a Permanent Joint Appointment with the Institute for Systems Research  (ISR) and the ECE Department at the University of Maryland College Park (UMD). He received  his Ph.D. degree in Applied Mathematics from Harvard University, in 1973, and he has been with  UMD since then. From 1985 to 1991, he was the Founding Director of the ISR. Since 1992, he  has been the Director of the Maryland Center for Hybrid Networks (HYNET), which he co-founded. He is a Fellow of IEEE (Life), SIAM, AAAS, NAI, IFAC, AMS, AIAA, Member of the  National Academy of Inventors (NAI) and a Foreign Member of the Royal Swedish Academy of  Engineering Sciences (IVA). Major honors and awards include the 1980 George Axelby Award from the IEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE  Communications Society, the 2017 IEEE Simon Ramo Medal, the 2017 AACC Richard E.  Bellman Control Heritage Award, and the 2018 AIAA Aerospace Communications Award. In  2016 he was inducted in the University of Maryland A. J. Clark School of Engineering Innovation  Hall of Fame. In June 2018 he was awarded a Doctorate Honoris Causa by his alma mater the  National Technical University of Athens, Greece. His research interests include systems, control,  optimization, autonomy, communication networks, applied mathematics, signal processing and  understanding, robotics, computing systems, formal methods and logic, network security and trust,  systems biology, healthcare management, model-based systems engineering. He has been awarded  twenty patents and honored with many awards as innovator and leader of economic development.


Pratap Tokekar

Contact: appicard@umd.edu

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