Keynote speaker

Robots that Learn:
Harnessing Advances in Machine Learning for Smart Actuation

Professor Sethu Vijayakumar FRSE

Professor Sethu Vijayakumar FRSE

Professor of Robotics and Director, Institute of Perception, Action and Behaviour (IPAB)
Royal Academy of Engineering - Microsoft Research Chair in Robotics
School of Informatics, University of Edinburgh, UK
http://homepages.inf.ed.ac.uk/svijayak

Abstract

What is your science fiction fantasy: A personal robot butler doing your household chores autonomously or going to the surgeon to buy a new bionic part to augment your body’s capabilities? Today, robots are increasingly making the journey from industry floors to our homes and workplaces – examples include self-driving vehicles (on road and underwater), prosthetic devices, surgical assistants and service robots for drilling, mining and cleaning. Professor Sethu Vijayakumar will explore the scientific challenges in the exciting domain of ‘interactive, autonomous robotics’ and show some of the cutting edge research in topology based representation and planning, variable impedance actuation as well as real time optimal control that is aimed at making robots as versatile, safe, reactive and adaptive as us humans. He will illustrate the spills and thrills of working with some of the world’s most sophisticated anthropomorphic robots through interactive demonstrations and videos. The science fiction of truly embodied artificial intelligence has never been this close to science fact in robotics and I will argue that it is the tremendous progress in data driven machine learning that is fuelling it.

Brief biography of the Speaker

Sethu Vijayakumar is the Professor of Robotics in the School of Informatics at the University of Edinburgh, UK and Director of the Institute for Perception, Action and Behavior (IPAB) as well as the co-Director of the Edinburgh Centre for Robotics. Since August 2007, he holds the prestigious Senior Research Fellowship of the Royal Academy of Engineering, co-funded by Microsoft Research. He also holds additional appointments as an Adjunct Faculty of the University of Southern California (USC), Los Angeles and a Visiting Research Scientist at the RIKEN Brain Science Institute, Japan. Prof. Vijayakumar, who has a PhD from the Tokyo Institute of Technology, has pioneered the use of large scale machine learning techniques in the real time control of large degree of freedom anthropomorphic robotic systems including the SARCOS and the HONDA ASIMO humanoid robots, KUKA-DLR robot arm and iLIMB prosthetic hand. His research interest spans a broad interdisciplinary curriculum ranging from statistical machine learning, adaptive control, and actuator design to human motor control and computational neuroscience. He is the author of over 150 highly cited publications in these fields and the winner of the IEEE Vincent Bendix award, the Japanese Monbusho fellowship, 2013 IEEE Transaction on Robotics Best Paper Award and several other awards from leading conferences. He has been the scientific coordinator and lead PI for a number of national, EU and international research projects, attracting over £25M in research funding over the past 8 years besides serving on numerous EU, DFG and NSF grant review panels and program committees of leading machine learning and robotics conferences. He is a Fellow of the Royal Society of Edinburgh and a keen science communicator with a significant annual outreach agenda.

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