Swiss Federal Institute of Technology (ETH), Zurich
Switzerland
Wednesday, June 11, 2008
8:00 – 9:00am
Grand III
Individual mobility is closely linked to the welfare of any society. Not surprisingly, the number of automobiles has been inexorably increasing and is likely to double in the next twenty years. Clearly, this development creates many benefits and economic opportunities, but also many problems, such as air pollution, traffic fatalities, increased energy consumption and carbon dioxide emission. In this talk the relevance of these problems will be prioritized and some of the most likely technological solutions will be presented. The key point is that in most - if not all - of these approaches automatic control systems will be an enabling factor, without which no true breakthroughs are possible.
After these rather general remarks, the following three examples will be presented to show what typical problem setups are to be faced and what methods are to be used to tackle these problems:
The talk closes with some remarks concerning some possible consequences for the control community. It postulates that there is a demand for more powerful modeling methods and tools, for learning control systems, and for a better integration of feedback and feedforward control loops into communication and computation networks. The most important challenge, however, is finding a way to implement all of these new devices and still not increase the system costs.
Lino Guzzella has been a full professor at ETH Zurich, Switzerland since 1999. After receiving his mechanical engineering diploma in 1981 and his doctoral degree in 1986, both from ETH, he has held several positions in industry and academia.
With his research group he focuses on novel approaches in system dynamics and in the control of energy conversion systems. Control-oriented systems modeling, dynamic optimization, and feedback control design methods are his main areas of research. He places a particular emphasis on the minimization of fuel consumption and pollutant emission of automotive propulsion systems. In teaching, he has been successfully promoting project- and team-based learning approaches.
Among the awards he received are the IEEE Control Systems Magazine Outstanding Paper Award, the SAE Arch T. Colwell Merit Award and the Ralph R. Teetor Educational Award, the IMechE Thomas Hawksley Medal and Crompton Lancaster Medal, and the Energy Globe Award.
Lino Guzzella has published more than 100 research articles as well as two textbooks (Modeling and Control of IC Engine Systems, Springer Verlag, 2004, and Vehicle Propulsion Systems, 2nd Ed., Springer Verlag, 2007). He is a consultant to several tier-one automotive companies and holds several patents on automotive control systems.
Queensland Brain Institute, University of Queensland
and
ARC Centre of Excellence in Vision Science
Thursday, June 12, 2008
8:00 – 9:00am
Grand III
Investigation of the principles of visually guided flight in insects is offering novel, computationally elegant solutions to challenges in machine vision and robot navigation.
Insects, in general, and honeybees, in particular, perform remarkably well at seeing and perceiving the world and navigating effectively in it, despite possessing a brain that weighs less than a milligram and carries fewer than 0.01% as many neurons as ours does. Although most insects lack stereo vision, they use a number of ingenious strategies for perceiving their world in three dimensions and navigating successfully in it.
The talk will describe a series of experiments which reveal that flying insects perceive the world in three dimensions and navigate safely in it by using cues derived from image motion, rather than complex stereo mechanisms. For example, distances to objects are gauged in terms of the apparent speeds of motion of the objects' images, rather than by using complex stereo mechanisms. Objects are distinguished from backgrounds by sensing the apparent relative motion at the boundary. Narrow gaps are negotiated safely by balancing the apparent speeds of the images in the two eyes. The speed of flight is regulated by holding constant the average image velocity as seen by both eyes. This ensures that flight speed is automatically lowered in cluttered environments, and that thrust is appropriately adjusted to compensate for headwinds and tail winds. Visual cues are also used to compensate for crosswinds. Bees landing on a horizontal surface hold constant the image velocity of the surface as they approach it, thus automatically ensuring that flight speed is close to zero at touchdown. Bees approaching a vertical surface hold the rate of expansion of the image of the surface constant during the approach, again ensuring smooth docking. Foraging bees gauge distance flown by integrating optic flow: they possess a visually-driven "odometer" that is robust to variations in wind, body weight, energy expenditure, and the properties of the visual environment.
We have been using some of the insect-based strategies described above to design, implement and test biologically-inspired algorithms for the guidance of autonomous terrestrial and aerial vehicles. Maneuvers such as visually stabilized hover, corridor and gorge navigation, attitude stabilization and terrain following will also be discussed in the talk.
Insects accomplish all of their navigational tasks without relying on detailed terrain maps, or external aids such as GPS. Thus, the principles uncovered by these studies could be of relevance to autonomous navigation in building interiors, in underwater environments, and in space exploration, and may be of interest in designing the next generation of autonomous vehicles, and in formulating future DARPA Grand Challenges.
Dr. Mandyam Srinivasan is with the University of Queensland’s Queensland Brain Institute, and the ARC Centre of Excellence in Vision Science. After receiving his Ph.D. at Yale University in Engineering and Applied Science in 1976, he joined the Australian National University’s Institute of Advanced Studies where he held a joint appointment as a Research Fellow in the Research Schools of Physical Sciences and Biological Sciences. During this time he worked on the electrophysiological analysis of visual information processing in insects, and on the development of mathematical models of movement detection and optimal image encoding. During 1982-85 he was a Visiting Assistant Professor at the University of Zurich, where he worked on the behavioral analysis of visual processing in honeybees. Srinivasan returned to the Australian National University in 1985, where he was promoted to full professor in 1993.
Dr. Srinivasan’s research focuses on understanding the principles of vision and navigation in small animals with relatively simple nervous systems, and on the application of these principles to the design of novel, biologically-inspired algorithms for machine vision, robotics and autonomous vehicles.
Dr. Srinivasan has published over two hundred journal papers and reviews, including several in high-impact journals such as Nature, Science and PNAS. Since 2000 he has delivered numerous keynote/plenary/named lectures at international conferences. He was awarded a D.Sc. in Neuroethology by the Australian National University in 1993, an Honorary Doctorate by the University of Zurich in 2001, the Australian Centenary Medal in 2003, the Australia Prime Minister’s Science Prize in 2006, and the U.K. Rank Prize in Optoelectronics in 2008. Srinivasan was elected to the Fellowship of the Australian Academy of Science in 1995, to the Fellowship of the Royal Society of London in 2001, and to the Academy of Science for the Developing World in 2005. He was awarded a five-year Federation Fellowship by the Australian Research Council in 2002, and a five-year Queensland Premier’s Fellowship in 2007. Srinivasan has served/ is serving on the Editorial Boards of Vision Research, the Public Library of Science (PLOS), the Journal of Comparative Physiology (A), the Journal of Insect Physiology, the Australian Journal of Intelligent Information Processing Systems, and the IEEE Transactions on Pattern Analysis and Machine Intelligence. Srinivasan’s research has received substantial support from the Australian Research Council, the Queensland State Government, the Australian Defense Science and Technology Organization (DSTO), the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. Office of Naval Research (ONR), the U.S. Air Force (AFOSR), the U.S. National Aeronautics and Space Administration (NASA), and the US Army (ARO).
University of Illinois at Urbana-Champaign
Friday, June 13, 2008
8:00 – 9:00am
Grand III
In this talk we will give an overview of our recent work on formulating and studying robustified versions of some concepts from nonlinear system theory. The original concepts are standard ones, such as the observability and minimum-phase properties. We call our versions robustified because rather than focusing on some ideal behavior (such as the output being identically zero) they capture possibly large deviations from this behavior and the resulting response of the system. These concepts are based on the framework of input-to-state stability, which is a robustified version of global asymptotic stabilization under zero inputs.
Our motivation for studying these concepts comes from several analysis and synthesis problems of current interest. These include stability of switched systems and control with limited information. Some advances on these problems which directly utilize the above concepts will be described in the talk.
Daniel Liberzon was a student in the Department of Mechanics and Mathematics at Moscow State University from 1989 to 1993 and received the Ph.D. degree in mathematics from Brandeis University in 1998 (under the supervision of Prof. Roger W. Brockett of Harvard University). Following a postdoctoral position in the Department of Electrical Engineering at Yale University from 1998 to 2000, he joined the University of Illinois at Urbana-Champaign, where he is now an associate professor in the Electrical and Computer Engineering Department and a research associate professor in the Coordinated Science Laboratory. Dr. Liberzon's research interests include nonlinear control theory, analysis and synthesis of switched systems, control with limited information, and uncertain and stochastic systems. He is the author of the book "Switching in Systems and Control". Dr. Liberzon currently serves as Associate Editor for the IEEE Transactions on Automatic Control. He is a recipient of the IFAC Young Author Prize (2002), the NSF CAREER Award (2002), and the Donald P. Eckman Award from the American Automatic Control Council (2007).