Virtual Meeting

Speaker: Professor Daniele Fontanelli, Department of Industrial Engineering, University of Trento – Italy

Bio: Daniele Fontanelli (M’10, SM’19) received M.S. degree in Information Engineering in 2001, and a Ph.D. degree in Automation, Robotics, and Bioengineering in 2006, both from the University of Pisa, Pisa, Italy.  He was a Visiting Scientist with the Vision Lab of the University of California at Los Angeles, Los Angeles, US, from 2006 to 2007.  From 2007 to 2008, he has been an Associate Researcher with the Interdepartmental Research Center “E. Piaggio”, University of Pisa.  From 2008 to 2013 he was an Associate Researcher at the  Department of Information Engineering and Computer Science and from 2014 the Department of Industrial Engineering, both at the University of Trento, Trento, Italy, where he is now a Full Professor in the field of Measurement and Robotics.  He has authored and co-authored more than 200 scientific papers in peer-reviewed top journals and conference proceedings.  He is a member of the TC17 – Measurement in Robotics. He is currently a Senior Area Editor for the IEEE Transactions on Instrumentation and Measurement and an Associate Editor for the IET Science, Measurement & Technology Journal and the IEEE Robotics and Automation Letters. He has also served as an Associate Editor-in-Chief for the IEEE Transactions on Instrumentation and Measurement and as a technical program committee of numerous conferences in the area of measurements and robotics. He is the co-founder of Polytec Intralogistics Srl (aka Dolomiti Robotics – https://dolomitirobotics.it/). He is the PI of the EU project MAGICIAN – iMmersive leArninG for ImperfeCtion detectIon and repAir through human-robot interactioN – and he was the co-founder and the PI of the EIT-Digital international Master on Autonomous Systems from 2017 to 2023. His research interests include distributed and real-time estimation and control, localiazale.fontanelli@unitn.it

Abstract: Autonomous systems are nowadays having an undisputed pervasiveness in the modern society. Autonomous driving cars as well as applications of service robots (e.g. cleaning robots, companion robots, intelligent healthcare solutions, tour guided systems) are becoming more and more popular and a general acceptance is now developing around such systems in modern societies. Nonetheless, one of the major problems in building such applications relies on the capability of autonomous systems to understand their surroundings and then plan proper counteractions. The most popular solutions, which are gaining more and more attention, rely on artificial intelligence and deep learning as a means to perceive the structured and complex natural environment.  Nonetheless, besides the importance of such complex tools, the classical concepts of metrology, such as standard uncertainty, accuracy and precision, are still unavoidable for a clear and effective understanding of modern autonomous systems applications.

At the end of this webinar, the attendee will be able to answer such questions as: what are the tools and the methods of major relevance for autonomous systems applications? How do concepts such as uncertainty map in the autonomous systems realm?

Registration: https://events.vtools.ieee.org/event/register/411367