Professor Sethu Vijayakumar FRSE
Professor of Robotics & Microsoft Research-RAEng Chair

Outreach + Media

U. Edinburgh

Professor Sethu Vijayakumar FRSE holds a Personal Chair in Robotics within the School of Informatics at the University of Edinburgh and is the Director of the Edinburgh Centre for Robotics.  Since 2007, he holds the Senior Research Fellowship of the Royal Academy of Engineering, co-funded by Microsoft Research and is also an Adjunct Faculty of the University of Southern California (USC), Los Angeles and a Visiting Research Scientist at the ATR Computational Neuroscience Labs, Kyoto-Japan. He has a Ph.D.(1998) in Computer Science and Engineering from the Tokyo Institute of Technology. Prof. Vijayakumar previously held the position of the Director of IPAB (2005-2015), Reader (2007-2010) and Lecturer (2003-2007) at the University of Edinburgh, a Research Assistant Professor ('01-'03) at USC and a Staff Scientist ('98-'00) at the RIKEN Brain Science Institute, Tokyo. His research interest spans a broad interdisciplinary curriculum involving basic research in the fields of robotics, statistical machine learning, motor control, planning and optimization in autonomous systems and computational neuroscience. His latest project (2016) involves a collaboration with NASA Johnson Space Centre on the Valkyrie humanoid robot being prepared for unmanned robotic pre-deployment missions to Mars. See here for a list of his publications [Google Scholar]. Sethu is a keen science communicator and in recent years, has been active in conceptualising, producing and presenting several public outreach events to engage with the general public and children on all things science and engineering. He is a Fellow of the Royal Society of Edinburgh and the winner of the 2015 Tam Dalyell Prize for Excellence in Engaging the Public with Science. He is the judge on the latest edition of BBC Robot Wars, a hugely popular technology show as well as involved with the launch of the BBC micro:bit coding initiative.

Postdoctoral Researchers: We have several senior Postdoctoral Fellowships (PDRAs: Grade 34, 3.5 yrs) starting immediately, aimed at candidates who have a PhD (or submitted), with an excellent research track record in the areas of motor control and multi-contact motion planning, humanoid and quadruped locomotion, shared autonomy interfaces and optimal control for variable impedance actuation. We also have an opening for a full time Engineer, with skills in hardware and software maintenance and hands on robotics expertise.  Get in touch if interested.
Studentships: Are you passionate about Robotics? Interested in a fully funded PhD with us on topics such as Machine Learning for Robotics, Humanoid and Anthropomorphic Robot planning, sensing  and control, Prosthetics and Human Motor Control? Would you like to work on exciting robotic platforms such as the UoE-NASA Valkyrie Humanoid? [News Coverage] [Prospective PhD Students apply here -- fully funded 4-year studentships]
June 2014: Our paper 'Robots Driven by Compliant Actuators: Optimal Control under Actuation Constraints' has been awarded the 2013 IEEE Transactions on Robotics Best Paper Award [News] [Paper] [IEEE site]
Edinburgh Centre for Robotics (2014): I direct our new Centre for Excellence in Robotics at Edinburgh, in collaboration with Heriot-Watt University, secured through a £11.5M investment from EPSRC [news] [EPSRC announcement] that includes the EPSRC Centre for Doctoral Training (CDT) in Robotics and Autonomous Systems to train over 65 PhD students in the area. [BBC News Coverage of ECR, March 2015]
Conferences: I was the publicity chair for the R:SS 2015 in Rome. I have served as the Program/Area Chairs for various editions of R:SS, NIPS and ICML.
Outreach: Please look at my Outreach and Media pages for public engagements, keynotes and media coverage.
2007: I have been awarded the Microsoft/Royal Academy of Engineering Senior Research Fellowship.
Check out our research home since June 2008: The Informatics Forum, in this video. Edinburgh beautiful sights!
Details of my research group, the Statistical Learning & Motor Control (SLMC) lab can be accessed here.

Selected Publications (for full list, see here)

  • Jun Nakanishi, Andreea Radulescu, David Braun and Sethu Vijayakumar, Spatio-temporal Stiffness Optimization with Switching Dynamics, Autonomous Robots, vol. 41(2), pp. 273-291 (2017). [pdf][DOI]

  • David Braun, Florian Petit, Felix Huber, Sami Haddadin, Patrick van der Smagt, Alin Albu-Schffer and Sethu Vijayakumar, Robots Driven by Compliant Actuators: Optimal Control under Actuation Constraints, IEEE Transactions on Robotics (IEEE T-RO), 29(5), pp. 1085-1101 (2013). [pdf] [2013 IEEE Transactions on Robotics Best Paper Award]

  • Konrad Rawlik, Marc Toussaint and Sethu Vijayakumar, On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference, Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf] [R:SS 2012 Best Paper Award Runner-up]

  • Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal, Incremental Online Learning in High Dimensions, Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005). [pdf] [LWPR software] [see next for usage guide]

  • Stefan Klanke, Sethu Vijayakumar and Stefan Schaal, A Library for Locally Weighted Projection Regression, Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). [pdf][DOI]

  • Stefan Schaal, Chris Atkeson and Sethu Vijayakumar, Real time robot learning with locally weighted statistical learning, Proc. International Conference on Robotics and Automation (ICRA2000), San Francisco, USA, vol.1, pp.288-293,(2000). [pdf] [ICRA 2000 Best Paper Award Finalist]

  • Djordje Mitrovic, Stefan Klanke and Sethu Vijayakumar,  Learning Impedance Control of Antagonistic Systems based on Stochastic Optimisation Principles, International Journal of Robotic Research (IJRR), Vol. 30, No. 5, pp. 556-573 (2011). [pdf][DOI]

  • Sethu Vijayakumar and Hidemitsu Ogawa, A Functional Analytic Approach to Incremental Learning in Optimally Generalizing Neural Networks, Proc. IEEE International Conference on Neural Networks (ICNN '95), Australia, vol. 2, pp.777-782 (1995).[DOI] [ICNN 1995 Best Student Paper Award]

  • Ian Saunders and Sethu Vijayakumar, The Role of Feed-Forward and Feedback Processes for Closed-Loop Prosthesis ControlJournal of Neuroengineering and Rehabilitation (JNER), 8:60 (2011). [pdf][DOI]

  • Dmitry Zarubin, Vladimir Ivan, Marc Toussaint, Taku Komura and Sethu Vijayakumar, Heirachical Motion Planning in Topological Representations,Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf] [video]

  • Andreaa Radulescu, Matthew Howard, David Braun and Sethu Vijayakumar, Exploiting Variable Physical Damping in Rapid Movement Tasks, Proc. 2012 IEEE ASME International Conference on Advanced Intelligent Mechatronics, Taiwan (2012). [pdf][video] [AIM 2012 Best Student Paper Award Finalist]

  • Timothy Hospedales and Sethu Vijayakumar, Bayesian Structure Inference for Multisensory Scene Understanding, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 30, no. 12, pp. 2140-2157 (2008). [pdf][DOI]

  • Sebastian Bitzer and Sethu Vijayakumar, Latent Spaces for Dynamic Movement Primitives, Proc. 9th IEEE RAS International Conference on Humanoid Robots (Humanoids 09), Paris, France (2009). [pdf]

  • Djordje Mitrovic, Stefan Klanke, Rieko Osu, Mitsuo Kawato and Sethu Vijayakumar, A Computational Model of Limb Impedance Control based on Principles of Internal Model Uncertainty, PLoS ONE, Vol. 5, No. 10 (2010). [pdf][DOI]

  • Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata, Jorg Conradt and Stefan Schaal, Statistical Learning for Humanoid Robots, Autonomous Robots , Vol. 12, No.1, pp. 55-69 (2002). [pdf]

  • Djordje Mitrovic, Stefan Klanke and Sethu Vijayakumar,  Adaptive Optimal Feedback Control with Learned Internal Dynamics Models, In: O. Sigaud and J. Peters (eds.): From Motor Learning to Interaction Learning in Robots, SCI 264, pp. 65-84, Springer-Verlag (2010). [pdf]

  • Graham McNeill and Sethu Vijayakumar, Part-based Probabilistic Point Matching Using Equivalence Constraints, Proc. Advances in Neural Information Processing Systems (NIPS '06), Vancouver (2006). [pdf]

  • Sethu Vijayakumar and Hidemitsu Ogawa, RKHS based Functional Analysis for Exact Incremental Learning
    Neurocomputing, Vol.29, No.1-3, pp.85-113, Elsevier Science(1999). [pdf]