State estimation for hand-based manipulation and grasping
ABSTRACT of the TALK
In robotics and other dynamics systems, sensory information is essential as it provides the basis for making appropriate decisions. However, sensorizing systems is not always straightforward, for a variety of reasons, such as cost or physical constraints, for example - a particular sensor might be very expensive, or existing sensors are not sufficiently accurate, or it might not be feasible to mount/install sensors in the desired location. An attractive solution to this problem is state estimation, which is sometimes known as indirect sensing, where (a) a mathematical model, and (b) available sensor measurements, are used to provide an estimate of an unmeasured signal/variable. This workshop will give an introduction to state estimation, followed by issues and challenges in this area. It will end with examples of successful applications of state estimation in robotic manipulation.
Chee Pin Tan received the B.Eng. degree (Hons.) and the Ph.D. degree from Leicester University, Leicester, U.K., in 1998 and 2002, respectively. He is now an Associate Professor at the School of Engineering, Monash University Malaysia. His research interests are in the theoretical development of robust state estimation and fault diagnosis schemes, and in applying them to areas such as soft robotics, mechanical ventilation, and smart cities. He has authored more than 100 internationally peer-reviewed research articles, including a book on fault reconstruction. He serves as a member of the IEEE Control Systems Society Conference Editorial Board, and also as Associate Editor of the Journal of Franklin Institute, and IET Collaborative Intelligent Manufacturing. In recognition of his research achievements, he has also been invited to give keynote talks at several international conferences - both in the academic and industrial communities.
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