Measurements Applications for Autonomous Systems
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 the 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 understand the structured and complex natural environment. Nonetheless, besides the importance of such complex tools, classical concept of metrology, such as uncertainty and precision, are still unavoidable to a clear and effective application of modern autonomous systems applications.
In this tutorial, some measurement concepts will be revised in light of the autonomous systems domain. In particular, we will cover the main concepts of the statistical approach to measurements that will then be applied to:
- Uncertainty analysis and synthesis for autonomous systems localisation
- Precision-based feedback for social robotics
Daniele Fontanelli received the M.S. degree in Information Engineering in 2001, and the Ph.D. degree in Automation, Robotics and Bioengineering in 2006, both from the University of Pisa, Italy. He was a Visiting Scientist with the Vision Lab of the University of California at 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 joined as an Associate Researcher 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 an Associate Professor. He has authored and co-authored more than 140 scientific papers in peer-reviewed top journals and conference proceedings. He is currently an Associate Editor for the IEEE Transactions on Instrumentation and Measurement, for the IET Science, Measurement and Technology Journal. From 2018 he is also an Associate Technical Program Committee Member for the IEEE/RSJ International Conference on Intelligent Robots and Systems. His research interests include autonomous systems and human localization algorithms, synchrophasor estimation, clock synchronization algorithms, real-time estimation and control, resource aware control, wheeled mobile robots and service robotics.
Audience: Young Professionals, Professionals in I&M, Researchers, Students
Publication Year: 2020