| CIRA'97 TUTORIALS (Wednesday, July 9, 1997) (Fees) | |
|---|---|
| Below is a list and description of the four tutorial courses (each one 4 hrs long): | |
| 1.1 |
An Introduction to Evolutionary Computation (8:00 AM - 12:00 PM): |
| Evolutionary computation is receiving increased interest for solving difficult problems in industry, medicine, and defense. Many of these problems are strongly related to robotics. The tutorial will provide an introduction to evolutionary algorithms, including genetic algorithms, evolution strategies, and evolutionary programming and indicate how these methods can be used in practice. Other related topics such as genetic programming and artificial life will also be discussed, as will advanced topics including self-adaptation and constrained optimization. | |
| Presenter: Dr. David B. Fogel, Natural Selection, Inc. | |
| David B. Fogel received the Ph.D. from UCSD in 1992. He is chief scientist of Natural Selection, Inc. in La Jolla. Dr. Fogel has over 100 publications in the area of evolutionary computation and is the founding editor-in-chief of the IEEE Transactions on Evolutionary Computation. | |
| 1.2 |
Design of Computational Intelligence Models for Robotics (8:00 AM - 12:00 PM): |
| Design of computational intelligence models are discussed with the perspective of fuzzy neural integration. Fuzzy rules represent our approximate knowledge of a system behavior that can be extracted from input-output analyses. In this context, fuzzy cluster analyses are known as the unsupervised and the neural methods as the supervised learning techniques. Next approximate reasoning methods may be categorized into (i) myopic reasoning methods which include (a) Mamdani approximation and (b) formal classical logic approximation, and (ii) full formal reasoning which requires Type II knowledge representation and inference. We present an integrated reasoning method that combines two myopic methods. The full reasoning method is reviewed for future research. Robotics and industrial process planning examples are discussed with the integrated methodology approach in the tutorial. | |
| Presenter: Prof. I.B. Turksen, Department of Mechanical & Industrial Engineering, University of Toronto | |
| I.B. Turksen is a Professor of Mechanical and Industrial Engineering at the University of Toronto. He is the Associate Editor of IEEE Transactions on Fuzzy Systems and sits on the Editorial Boards of FSS, IJAR, DSS, IS, ES&A, ACI, ITM, TOR, ECS&T. He is the Co-Editor of NATO-ASI on "Soft Computing and Computational Intelligence" and Editor of NATO-ASI on "Computer Integrated Manufacturing". | |
| 2.1 |
Real and Virtual Robotic Systems: Sensing, Simulation, and Interfaces (13:30 PM - 17:30 PM): |
| This half-day tutorial will focus on two important aspects of intelligent robotics and human-machine cooperative systems. These are: (1) integrated robotic systems: architecture and sensing, and (2) simulation, animation, visualization and interactive control for human-machine systems. The tutorial will include discussion of the role of visualization environments for simulation, animation, and interactive control of integrated robotic systems. Virtual reality concepts and systems will have a great impact on the development of a new generation of human-robot cooperating systems. Key ideas presented in the tutorial include: (i) use of multiple sensors, both for real and virtual systems, (ii) transparency between the real and virtual mode operation, and (iii) integrating sensing and planning in simulation. The presentation will include the following case studies where above concepts are successfully employed: a locomotion controller for a tracked mobile manipulator for nuclear reactor applications, a of binocular robotic head for active perception and telepresence, and multi-robot teams for inspection and maintenance applications. | |
| Presenters: Prof. Mohan M. Trivedi and Dr. Chuxin Chen, Computer Vision and Robotics Research Laboratory, University of California at San Diego | |
| Mohan M. Trivedi is a Professor of Electrical and Computer Engineering and the Director of the Interdisciplinary Program in Advanced Manufacturing at the at the University of California in San Diego. He has published extensively and has edited over a dozen volumes including books, special issues, video presentations, and conference proceedings. He is a Fellow of the International Society for Optical Engineering (SPIE). DR. Trivedi serves as the Editor-in-Chief of the Machine Vision and Applications journal. | |
| Chuxin Chen received the B.S. and M.S. degrees in electrical engineering from Louisiana State University in 1983 and 1986, respectively, and the Ph.D. in electrical engineering from the University of Tennessee, Knoxville, in 1991. Dr. Chen has been involved in a wide range of university and industry-based research projects. | |
| 2.2 |
Autonomous Learning Algorithms for Autonomous Robots (13:30 PM - 17:30 PM): |
| Autonomous robots need autonomous learning algorithms. Learning algorithms are autonomous when they can learn on their own (e.g. design and train computational structures such as neural networks) without depending on any human intervention or external assistance. The objective of this tutorial is to present some new ideas regarding brain-like learning that can lead to the development of truly autonomous robots. The tutorial will broadly introduce several new types of learning methods developed over the last few years by several researchers closely associated with the field of operations research. The participants will learn how these methods decompose and simplify the learning problem and make it tractable. | |
| Presenter: Dr. Asim Roy, Computer Information Systems Group, Arizona State University | |
| Asim Roy received his M. S. from Case Western Reserve University and his Ph.D. from University of Texas, Austin, both in operations research. He has been a visiting scholar at Stanford University and has served on organizing committees of many scientific conferences. He is an Associate Editor of IEEE Transactions on Neural Networks. | |
| TUTORIAL REGISTRATION FEES* | |
|---|---|
| Early Bird Conference Registration through June 27, 1997 | |
| IEEE MEMBERS | $100 |
| NON-MEMBERS | $150 |
| FULL-TIME STUDENTS** | $70 |
| AFTER June 27, 1997 | |
| IEEE MEMBERS | $150 |
| NON-MEMBERS | $250 |
| FULL-TIME STUDENTS** | $100 |
| * Tutorial registration includes one morning and one afternoon tutorial. Tutorial registration fee includes refreshments, and a copy fo the tutorial presentation. | |
| ** Students must submit evidence of full-time enrollment on University letterhead. | |