A fundamental element of most crucial robotics and autonomous systems applications is a reliance on path planning and tracking algorithms. However, it can be challenging to rapidly prototype, validate, and compare the many alternative approaches to this ubiquitous problem.
In this webinar, Dr. Umberto Montanaro, Senior lecturer with the School of Mechanical Engineering Sciences at the University of Surrey, will present his work on the development and validation of advanced path-tracking solutions using the Quanser QCar.
Umberto Montanaro received the “Laurea” (M.Sc.) degree in computer science engineering cum laude, the Ph.D. degree in control engineering and the Ph.D. degree in mechanical engineering from the University of Naples Federico II, Naples, Italy, in 2005, 2009, and 2016, respectively. From 2010 to 2013, he was a Research Fellow with the Italian National Research Council (Istituto Motori).
He is currently a Senior Lecturer in Autonomous Systems and Control Engineering with the School of Mechanical Engineering Sciences, University of Surrey, Guildford, U.K. The scientific results he has obtained up to now have been the subject of more than 70 scientific articles published in peer-reviewed international scientific journals and conferences.
His research interests range from control theory to control application and include adaptive control, enhanced model reference adaptive control (EMRAC), control of discontinuous systems, control of mechatronics systems, automotive systems, control of networked systems, connected autonomous vehicles, and vehicle platooning.