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Wednesday August 20, 2014
Congratulations to Yash Mulgaonkar!!! First Place at 2014 ASME Student Mechanism & Robot Design Competition
Friday August 29, 2014
On Bloomberg TV, Vijay Kumar of Engineering and Applied Science says “there is a business case to be made” for commercially viable delivery dron
Friday August 29, 2014
Rehabilitation With the Help of RobotsText by Heather A. Davis
Photos by Scott Spitzer
From automated assembly lines to personalized flying drones, robots are opening up new possibilities in the realms of both work and play.
Monday July 28, 2014
Media Contact:Evan Lerner | firstname.lastname@example.org | 215-573-6604July 28, 2014
The University of Pennsylvania’s
Presenter: Adam Spiers (Homepage)
Monday August 11, 2014 from 1:30pm to 2:30pm
* Alternate Location: Levine 307*
In this talk I will cover two quite different areas of research that are linked by the common theme of haptics.
Ad Spiers is a postdoctoral researcher in Yale University’s Grab lab. He is currently developing haptic navigation devices and investigating how upper limb amputees use their prosthetics in daily life. In his previous role (Bristol robotics laboratory, UK) Ad worked with NHS (National Health Service) surgeons to investigate benefits and methods of enabling haptic feedback in tele-operated surgery and training simulators. His PhD, obtained from Bristol University, was in the real-time synthesis of human-like reaching movements for robot manipulators.
In addition to academic research, Ad has been involved in various creative technology projects featuring robotics and haptics. This led to a (now long distance) invited residence at the Pervasive Media Studio creative technology hub in the UK. Previous work has included groups of animatronic origami creatures and a mind controlled beer pouring robot. His work has been exhibited in galleries and music festivals, reaching a wide and varied audience. His current haptics work continues his ongoing collaboration with visually impaired artists looking to create new and accessible forms of cultural experience.
Thursday July 10, 2014
Tampa Bay Times - Associated Press
"Those algorithms can translate off the field into technology like self-driving cars or delivery drones, said University of Pennsylvania engineering professor Dan Lee.
Presenter: Changhyun Choi (Homepage)
Friday July 18, 2014 from 1:00pm to 2:00pm
* Alternate Location: Levine 307*
As robotic systems move from
well-controlled settings to increasingly unstructured
environments, they are required to operate in highly
dynamic and cluttered scenarios. Finding an object,
estimating its pose, and tracking its pose over time
within such scenarios are challenging problems. Although
various approaches have been developed to tackle these
problems, the scope of objects addressed and the
robustness of solutions remain limited.
Changhyun Choi is a Ph.D. candidate in the School of Interactive Computing, College of Computing at the Georgia Institute of Technology (Georgia Tech) in Atlanta, Georgia, USA. He is also affiliated with the Institute for Robotics and Intelligent Machines (IRIM) at Georgia Tech. He was a research intern in the Imaging Group of Mitsubishi Electric Research Labs (MERL) in Cambridge, Massachusetts, USA, an intern researcher at the Imaging Media Research Center (IMRC) at Korea Institute of Science and Technology (KIST), and an undergraduate researcher at the Intelligent Systems Research Center at Sungkyunkwan University in Korea. He holds a B.S. in Information and Communication Engineering from Sungkyunkwan University. His broad research interests are in visual perception for robotics, with a focus on object recognition and pose estimation, visual tracking, and 3D registration.
Presenter: Sertac Karaman (Homepage)
Friday December 5, 2014 from 11:00am to 12:00pm
Consider a robotic vehicle that is traveling in a cluttered environment or attempting to fulfill tasks that require visiting several locations. What is the maximum speed that this vehicle can achieve and maintain for a long time? How does this speed depend on the agility, perception, actuation, or computation capabilities of the vehicle?
Sertac Karaman is the Charles Stark Draper Assistant Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology (since Fall 2012). He has obtained B.S. degrees in mechanical engineering and and in computer engineering from the Istanbul Technical University, Turkey, in 2007, an S.M. degree in mechanical engineering from MIT in 2009, and a Ph.D. degree in electrical engineering and computer science also from MIT in 2012. His research interests lie in the broad areas of robotics and control theory. In particular, he studies the applications of probability theory, stochastic processes, stochastic geometry, formal methods, and optimization for the design and analysis of high-performance cyber-physical systems. He is the recipient of an AIAA Graduate Award (2011), an NVIDIA fellowship (2011), as well as an NSF CAREER award (2014).
Presenter: Hong Zhang (Homepage)
Friday November 21, 2014 from 11:00am to 12:00pm
One area of significant progress in robotics research in recent years has been the use of visual sensing by mobile robots to map an environment and negotiate routes within the environment. This growth is mostly attributed to the rich textural information in visual sensory data compared with the traditional range data, as well as to the great strides made in the development of efficient and robust computer vision and image processing algorithms.
Dr. Hong Zhang received his Ph.D. from Purdue University in 1986 in Electrical Engineering. Subsequently he spent 18 months with the GRASP Lab at the University of Pennsylvania as post-doctoral fellow before joining the University of Alberta, Canada where he is currently a Professor in the Department of Computing Science and the Director of the Centre for Intelligent Mining Systems.
Dr. Zhang’s research interest spans robotics, computer vision, and image processing, and he has published close to 200 papers in top international journals and conferences in these areas. He is mostly known for his research in collective robotics - introducing biologically inspired solutions to decentralized control of a multirobot system - and in applied image processing for Alberta’s oil sands industry to measure key performance indicators, creating a unique expertise that never existed before. His current research focuses on visual robot navigation and its application to environment monitoring in Canadian outdoors.
Dr. Zhang has been active in professional activities. His journal editorial responsibilities include IEEE Transaction on Cybernetics, the journal of Robotics, and International Journal of Robotics and Biomimetics. Dr. Zhang chairs the technical committee on Robotics and Intelligent Sensing of the IEEE SMC Society, and is a member of the AdCom of the IEEE Robotics and Automation Society (2014-2016). Among the many conference organization involvements, he serves as the General Chair of 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), to be held in Vancouver, Canada. Dr. Zhang's achievements have been recognized through many awards including IEEE Millennium Medal in 2000, the 2006 Canadian Image Processing and Pattern Recognition Society (CIPPRS) Award for Research Excellence, and a 2008 ASTech Award in recognition of his contributions
to industrial research in Alberta. He is the holder of an NSERC Industrial Research Chair and a Fellow of IEEE.
Presenter: Kris Hauser (Homepage)
Friday November 14, 2014 from 11:00am to 12:00pm
planning -- the problem of computing physical actions to complete a
specified task -- has inspired some of the most theoretically rigorous
and beautiful results in robotics research. But as robots proliferate
in real-world applications like household service, driverless cars,
warehouse automation, minimally-invasive surgery, search-and-rescue, and
unmanned aerial vehicles, we are beginning to
see the classical theory fall behind. The clean assumptions of theory
are at odds with the dirty reality: robots must handle large amounts of
noisy sensor data, unc
Kris Hauser is an Associate Professor at the Pratt School of Engineering at Duke University with a joint appointment in the Electrical and Computer Engineering Department and the Mechanical Engineering and Materials Science Department. He received his PhD in Computer Science from Stanford University in 2008, bachelor's degrees in Computer Science and Mathematics from UC Berkeley in 2003, and worked as a postdoctoral fellow at UC Berkeley. He then joined the faculty at Indiana University from 2009-2014, where he started the Intelligent Motion Lab. He is a recipient of a Stanford Graduate Fellowship, Siebel Scholar Fellowship, and an NSF CAREER award.