UCL ELLIS

Speaker	Roberto Calandra
Affiliation	TU Darmstadt
Date	Friday, 16 October 2015
Time	13:00-14:00
Location	Zoom
Link	Roberts G08 (Sir David Davies lecture theatre)
Event series	Jump Trading/ELLIS CSML Seminar Series
Abstract	Abstract: The use of robots in our everyday life is hindered by the complexity necessary to design and tune appropriate controllers to execute the desired tasks. In this talk, I will show how Bayesian modelling can help to substantially reduce such complexity by providing effective tools. In the first part of my talk, I will discuss the learning of dynamical models required for accurate control and planning of the robot's movement, with a special emphasis on discontinuities deriving from contacts with the environment. Following, I will discuss the use of Bayesian optimization to efficiently optimize the parameters of existing controllers. As demonstration, I will present results obtained on a dynamic bipedal walker. Short Bio: Roberto Calandra is a PhD Candidate in the Autonomous Intelligent Systems Lab at TU Darmstadt, Germany. Previously, he achieved a B.Sc. in Computer Science with an emphasis on control at the University of Palermo, Italy and a M.Sc. in Machine Learning and Data Mining at the Aalto University (formerly Helsinki University of Technology), Finland. His research interest lie at the convergence between robotics and machine learning.
Biography