Picture of  Patrick van der Smagt

Patrick van der Smagt

current: Head of AI Research, data lab, VW Group

Previous: Director of BRML labs
fortiss, An-Institut der Technischen Universität München
Professor for Biomimetic Robotics and Machine Learning, TUM

Chairman of Assistenzrobotik e.V.

In heading a research lab focussing on machine learning and its application in robotics, biomimetics and sensory data processing, my goal is to develop the techniques to model and use (human) movement.

The slides of my Keynote on end-to-end learning at the 2015 IROS conference are available here.

Visit my blog.


Best Paper Award, Int Conf on Neural Information Processing (ICONIP 2014)
King-Sun Fu Best 2013 Transactions on Robotics Paper Award (2014)
Harvard Medical School/MGH Martin Research Prize (2013)
Erwin Schrödinger Award, Helmholtz Gesellschaft (2012)
SfN BCI Award Finalist (2012)
TUM Leonardo da Vinci Award (2008)
IEEE Best Paper Awards
Beckmann Institute Fellowship (1995)
NACEE Fellowship

in the press

various sources, e.g. NY Times, May 16, 2012: on a brain-controlled robotics experiment
Bayerische Rundfunk, May, 2012: "Wenn Rechner immer intelligenter werden", Radio Wissen
n-tv, June 10, 2010: EMG-controlled robotics
pinc, May 18, 2009, "biorobotics"
Het Financieele Dagblad, May, 2009
Discovery Channel, April 2009: "Future Homes"
3Sat, April 22, 2007: "Z wie Zukunft"
RTLII, March, 2007: "Welt der Wunder"
Pro7, Nov. 5, 2006: "Wunderwelt Wissen"
Abendzeitung, Oct. 28, 2006: Bestnoten für Forscher und Unternehmen
ZDF: Heute Journal, Sep. 15, 2006: Interview
ORF: "Newton" Science report, April 30, 2006: report on advanced prostheses
Süddeutsche Zeitung, Mar. 03, 2006: "Künstliche Hand am Computer entwickelt"
Süddeutsche Zeitung, Jan. 26, 2006: "Direkter Draht zum Hirn"

We were and are funded by various sources, including:
DFG project "SPP autonomous learning" (2012-2015)
NEUROBOTICS (EC project, 2005-2009)
NINAPRO (Swiss project, 2010-2013)
SENSOPAC (EC project, 2006-2010)
STIFF (EC project, 2009-2011)
THE (EC project, 2010-2014)
VIACTORS (EC project, 2009-2012)

on publishing

In June 2012 I resigned as editor of Neural Networks (Elsevier). Having worked with Neural Networks for almost 20 years, I have come to realise that the publication model propagated by behind-paywall publishers no longer combines with my own views of publication DOs and DONTs.  In particular, I have decided to move away from classical publication methods towards open access publishing, now that such alternatives are maturing.

After so many years of research and publishing, it is clear that only a peer-to-peer (double-open) review system with open access to the publications can be fair and unbiased.

I am currently still editor of Biological Cybernetics, as the open access model is being supported by Springer. However, also that large publishing house will have to rethink their approach to scientific publication before long.

Reviewing is good.  But open publication is an alternative.  My blog is an attempt to solve, for my own benefit, this publication issue.

Title: Cerebellar Control of Robot Arms
Written by: Smagt P van der
in: Connection Science 1998
Volume: 10 Number:
on pages: 301--320
Editor: Noel Sharkey
how published:
DOI: 10.1080/095400998116468

pdf doi bibtex


Abstract: Decades of research into the structure and function of the cerebellum have led to a clear understanding of many of its cells, as well as how learning takes place. Furthermore, there are many theories on what signals the cerebellum operates on, and how it works in concert with other parts of the nervous system. Nevertheless, the application of computational cerebellar models to the control of robot dynamics remains in its infant state. To date, a few applications have been realized, yet limited to the control of traditional robot structures which, strictly speaking, do not require adaptive control for the tasks that are performed since their dynamic structures are relatively simple. The currently emerging family of light-weight robots~\cite{Hir96} poses a new challenge to robot control: due to their complex dynamics traditional methods, depending on a full analysis of the dynamics of the system, are no longer applicable since the joints influence each other dynamics during movement. Can artificial cerebellar models compete here? In this overview paper we present a succinct introduction of the cerebellum, and discuss where it could be applied to tackle problems in robotics. Without conclusively answering the above question, an overview of several applications of cerebellar models to robot control is given.