Seminar: Bayesian Modeling for Optimization and Control in Robotics

SpeakerRoberto Calandra
AffiliationTU Darmstadt
DateFriday, 16 Oct 2015
Time13:00 - 14:00
LocationRoberts G08 (Sir David Davies lecture theatre)
Event seriesDeepMind CSML Seminar Series

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.

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