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Presenter: Pramod Khargonekar (Homepage)
Friday November 7, 2014 from 11:00am to 12:00pm
The main goal of this talk is to share thoughts and perspectives on key
opportunities and challenges in engineering research; education and
and innovation ecosystem as seen from my perspective at the National
Science Foundation. I will begin with a discussion of the overall
context, drivers, and trends that are driving our strategies.
Pramod Khargonekar received B. Tech. Degree in electrical engineering from the Indian Institute of Technology, Bombay, India, in 1977, and M.S. degree in mathematics and Ph.D. degree in electrical engineering from the University of Florida in 1980 and 1981, respectively.
Khargonekar was an assistant professor of electrical and computer engineering at the University of Florida from 1981 to 1984; associate professor from 1984 to 1988 and professor from 1988 to 1989 of electrical engineering at the University of Minnesota; and professor of electrical engineering and computer science from 1989 to 2001 at The University of Michigan. He was Chairman of the Department of Electrical Engineering and Computer Science from 1997 to 2001 and also held the position of Claude E. Shannon Professor of Engineering Science at The University of Michigan. From 2001 to 2009, he was Dean of the College of Engineering at the University of Florida. He has held the Eckis Professorship in Electrical and Computer Engineering the University of Florida from 2001. He served as Deputy Director of Technology at ARPA-E, U. S. Department of Energy in 2012-13. From March 2013, he has been serving as Assistant Director of the U. S. National Science Foundation leading its Engineering Directorate.
Khargonekar’s research and teaching interests are centered on theory and applications of systems and control. His early work was on mathematical control theory, specifically focusing on robust and H-infinity control analysis and design. During the 1990’s, he was involved in a large multidisciplinary project on applications of control and estimation techniques to semiconductor manufacturing. His current research and teaching interests include systems and control theory, machine learning, and applications to smart electric grid and neural engineering.
Presenter: Kostas Bekris (Homepage)
Friday October 31, 2014 from 11:00am to 12:00pm
Motion planning has progressed over the last couple of decades in
addressing complex challenges in robotics. An important milestone
was the development of practical sampling-based solutions, for
which recently the conditions that allow these methods to achieve
asymptotic optimality have been identified. Based on the
state-of-the-art, this talk will highlight a series of recent
foundational contributions by our research group in this area:
Kostas Bekris is an Assistant Professor of Computer Science at Rutgers University since 2012 and a member of the CBIM center. He received his BS in Computer Science at the University of Crete, Greece and completed his MS and PhD degrees in Computer Science at Rice University, Houston, TX, under the supervision of Prof. Lydia Kavraki. Between 2008 and 2012 he was an Assistant Professor at the University of Nevada, Reno. He works in robotics and his interests include motion planning, especially for systems with dynamics, manipulation, online replanning, motion coordination, as well as applications in cyber-physical systems and simulations. His research group is supported by the National Science Foundation, the National Aeronautics and Space Administration, the Department of Homeland Security and the Department of Defense. His research group is also affiliated with DIMACS and the DHS Center of Excellence CCICADA.
Presenter: Sonia Chernova (Homepage)
Friday October 24, 2014 from 11:00am to 12:00pm
Recent innovations in crowd computing, crowdsourcing and remote access
technologies have altered the way in which many traditional artificial
intelligence and robotics studies are designed, conducted and
evaluated. Research on shared autonomy, human-robot interaction and
robot learning has particularly benefited from the greater access to
data and users that such techniques enable, leading to new data-driven
techniques and more extensive evaluations. In this talk, I will present
ongoing projects aimed at enabling robots to learn from everyday
people, examining ho
Sonia Chernova is an Assistant Professor of Computer Science and Robotics Engineering at Worcester Polytechnic Institute and the director of the Robot Autonomy and Interactive Learning (RAIL) lab. She earned B.S. and Ph.D. degrees in Computer Science from Carnegie Mellon University in 2003 and 2009, and was a Postdoctoral Associate at the MIT Media Lab prior to joining WPI. Her research is focused on interactive machine learning, adjustable autonomy, crowdsourcing and human-robot interaction. This work is supported in part by NSF CAREER, NRI and ONR YIP awards.
Presenter: Torsten Kroeger (Homepage)
Friday October 17, 2014 from 11:00am to 12:00pm
Online and instantaneous robot motion generation is an important feature for
robot motion control systems to let robots respond instantaneously to
unforeseen events. An algorithmic concept that enables instantaneous changes
from sensor-guided robot motion control (e.g., force/torque or visual servo
control) to trajectory-following motion control, and vice versa, will be
presented. The resulting class of on-line trajectory generation algorithms
serves as an intermediate layer between low-level motion control and
high-level sensor-based motion planning.
Dr. Torsten Kroeger is a roboticist at Google and a visiting scholar at Stanford University. He received his Ph.D. in computer science from TU Braunschweig in Germany in 2009 (summa cum laude). In 2010, he joined the Stanford AI Lab as a lecturer and research associate. His research interests are focused on real-time trajectory generation and control of robotic systems. Application domains of his research include industrial robotics and automation, machine tools, haptic devices, surgical robotics, service robotics, mobile robotics, and space telescope control. He has been working as a research consultant for Volkswagen AG, KUKA Roboter GmbH, Manz Automation AG, Auris Surgical Robotics, Inc., and Redwood Robotics, Inc.. He is the founder of Reflexxes GmbH, a startup working on research and development of real-time motion generation software. In 2014, Reflexxes was acquired by Google, where Torsten now leads parts of R&D efforts in the domain of robotics. Torsten is an editor or an associate editor of multiple IEEE conference proceedings, books, and book series. He received the 2014 IEEE RAS Early Career Award, the 2011 Heinrich Buessing Award, the 2011 GFFT Award, two fellowships of the German Research Association, and he was a finalist of the 2012 IEEE/IFR IERA Award and the 2012 euRobotics TechTransfer Award.
Presenter: Timothy Bretl (Homepage)
Friday October 3, 2014 from 11:00am to 12:00pm
My talk in the language of robotics:
"I will show how to establish an appropriate configuration space for robotic manipulation of canonical 'deformable linear objects' like a Kirchhoff elastic rod (e.g., a flexible wire). This result leads to simple algorithms for manipulation and perception that are easy to implement and that work well in practice."
My talk in the language of mathematics:
Timothy Bretl received his B.S. in Engineering and B.A. in Mathematics from Swarthmore College in 1999, and his M.S. in 2000 and Ph.D. in 2005 both in Aeronautics and Astronautics from Stanford University. Subsequently, he was a Postdoctoral Fellow in the Department of Computer Science, also at Stanford University. Since 2006, he has been with the University of Illinois at Urbana-Champaign, where he is an Assistant Professor of Aerospace Engineering and a Research Assistant Professor in the Coordinated Science Laboratory. He received the National Science Foundation Faculty Early Career Development Award in 2010.
Presenter: Steve LaValle (Homepage)
Friday September 26, 2014 from 11:00am to 12:00pm
Using the latest technology, we can safely hijack your most trusted
senses, thereby fooling your brain into believing you are in another
world. Virtual reality (VR) has been around for a long time, but due
to the recent convergence of sensing, display, and computation
technologies, there is an unprecedented opportunity to explore this
form of human augmentation with lightweight, low-cost materials and
simple software platforms.
Steve LaValle started working with Oculus VR in September 2012, a few days after their successful Kickstarter campaign, and was the head scientist up until the Facebook acquisition in March 2014. He developed perceptually tuned head tracking methods based on IMUs and computer vision. He also led a team of perceptual psychologists to provide principled approaches to virtual reality system calibration and the design of comfortable user experiences. In addition to his continuing work at Oculus, he is also Professor of Computer Science at the University of Illinois, where he joined in 2001. He has worked in robotics for over 20 years and is known for his introduction of the Rapidly exploring Random Tree (RRT) algorithm of motion planning and his 2006 book, Planning Algorithms.
Presenter: GRASP Faculty Members (Homepage)
Friday September 5, 2014 from 11:00am to 12:00pm
Dr. Mark Yim (presented by Matt Piccoli)
Dr. CJ Taylor
Dr. Jianbo Shi (presented by Jihua Huang)
Presenter: Julie Shah (Homepage)
Friday September 19, 2014 from 11:00am to 12:00pm
Recent advances in computation,
sensing, and hardware enable robotics to perform an increasing percentage of
traditionally manual tasks in manufacturing. Yet, often the assembly mechanic
cannot be removed entirely from the process. This provides new economic
motivation to explore opportunities where human workers and industrial robots
may work in close physical collaboration. In this talk, I present the
development of new algorithmic techniques for collaborative plan execution that
scale to real-world industrial applications.
Julie Shah is an Assistant Professor in the Department of Aeronautics and Astronautics at MIT and leads the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory. Shah received her SB (2004) and SM (2006) from the Department of Aeronautics and Astronautics at MIT, and her PhD (2010) in Autonomous Systems from MIT. Before joining the faculty, she worked at Boeing Research and Technology on robotics applications for aerospace manufacturing. She has developed innovative methods for enabling fluid human-robot teamwork in time-critical, safety-critical domains, ranging from manufacturing to surgery to space exploration. Her group draws on expertise in artificial intelligence, human factors, and systems engineering to develop interactive robots that emulate the qualities of effective human team members to improve the efficiency of human-robot teamwork. Shah is the recipient of a 2014 NSF CAREER Award, and her work was recognized by the Technology Review as one of the 10 Breakthrough Technologies of 2013. She has received international recognition in the form of best paper awards and nominations from the International Conference on Automated Planning and Scheduling, the American Institute of Aeronautics and Astronautics, the IEEE/ACM International Conference on Human-Robot Interaction, and the International Symposium on Robotics.
Friday June 13, 2014
As reported by Agence France-Presse in the Bangkok Post, check out the video, http://www.bangkokpost.com/learning/learning-from-news/415172/robocup-world-cup-for-robots-video
In Yahoo! Sports...Football-playing robots eye their own cup, and beyond
Presenter: Jun Seo (Homepage)
Friday June 20, 2014 from 12:00pm to 1:00pm
* Alternate Location: Towne 337*
this talk, I will present my research on robotic grasping and
assembling: how to enable robots to grasp objects and assemble target
structures autonomously. They are fundamental problems in robotic
manipulation where we have robots rearrange our environment; they can be
applied to a wide range of scenarios such as manufacturing, disaster
response, space exploration, and assisted living. Modular robot
platforms can facilitate the problems with versatility and robustness.
Jun Seo is a Ph.D. candidate working in the GRASP Laboratory at the University of Pennsylvania. He is advised by Dr. Vijay Kumar and Dr. Mark Yim. Jun's research interests include robotic grasping/manipulation and robotic self-assembly/reconfiguration; he has been investigating theoretical and practical issues relating to the design of software and hardware for the problems. He received the B.S. degree from the Department of Mechanical and Aerospace Engineering at Seoul National University, Seoul, Korea.