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Dr. Sethu Vijayakumar

Director of the Institute of Perception, Action and Behavior,
School of Informatics, University of Edinburgh, UK


Machine Learning for Robotics and Sensorimotor Control

Date: Jan 21st

Time: 10 a.m.


Humans and other biological systems are very adept at performing fast, complicated control tasks in spite of large sensorimotor delays while being fairly robust to noise and perturbations. There are various components involved in achieving such levels of robustness, accuracy and safety in anthropomorphic robotic systems. Broadly, speaking challenges lie in the domain of robust sensing, flexible planning, appropriate representation and learning dynamics under various contexts. Statistical Machine Learning provides ideal tools to deal with these challenges, especially in tackling issues like partial observability, noise, redundancy resolution, high dimensionality and the ability to perform and adapt in real time.

This talk is about

(a) novel techniques developed for real time acquisition of non-linear dynamics in a data driven manner

(b) techniques for automatic low-dimensional (latent space) representation of complex movement policies and trajectories

(c) planning methods capable of dealing with redundancy (e.g. variable impedance) and adaptation in the Optimal Feedback Control framework.

Some of the techniques developed, in turn, provide novel insights into modeling human motor control behavior. 

Videos of learning in high dimensional movement systems like anthropomorphic limbs (KUKA robot arm, SARCOS dexterous arm, iLIMB etc.) and humanoid robots (HONDA ASIMO, DB) will serve to validate the effectiveness of these machine learning techniques in real world applications. 

Director of the Institute of Perception, Action and Behavior,
School of Informatics, University of Edinburgh, UK


Prof. Sethu Vijayakumar 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 Nao mini-humanoids. Since August 2007, he holds the prestigious Microsoft Research- Royal Academy of Engineering Senior Research Fellowship in Learning Robotics.  Prof. Vijayakumar, who has a PhD in Computer Science and Engineering from the Tokyo Institute of Technology, also holds additional appointments as an Adjunct Faculty of the University of Southern California (USC), Los Angeles and as a Visiting Research Scientist at the RIKEN Brain Science Institute, Japan and the ATR Computational Neuroscience Labs, Kyoto. His research interest spans a broad interdisciplinary curriculum involving basic research in the fields of statistical machine learning, robotics, human motor control, Bayesian inference techniques and computational neuroscience. He is the author of over 100 peer reviewed publications in these fields, the winner of the IEEE Vincent Bendix award, the Japanese Monbusho fellowship besides serving on numerous EU and NSF grant review panels and program committees of leading machine learning and robotics conferences.


Prof.Sethu Vijayakumar's Personal Webpage



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