Apologies for multiple posting.
Call for contributions:
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IROS 2012 Workshop
Optimality Principles and Adaptation in Humanoid Robotic Control
http://macsi.isir.upmc.fr/index.php?perma=iros2012workshop
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IROS 2012 Workshop, October 7
Location: Vilamoura, Algarve, Portugal
July 10, 2012: Extended abstracts submission deadline
July 30, 2012: Notification of acceptance
Organizers:
Serena Ivaldi, Olivier Sigaud (ISIR-UPMC, France)
Bastien Berret, Francesco Nori (IIT, Italy)
Contact: h2h_iros12@isir.upmc.fr
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The availability of new mechatronic platforms such as humanoid robots has
driven robotics control research to new paradigms where optimal control of
movements and adaptation to perturbations or unforeseen situations are
becoming the key challenges. In these new lines of research, inspiration
from human motor control and learning capability is playing a central role.
But the corresponding frameworks come with very large computational costs so
a lot of effort is required in designing practical methods that can address
meaningful control and learning problems up to the whole body control of
humanoids.
OBJECTIVES
The goal of this workshop is to get an accurate picture of the current state
of the art and discuss the hot questions of the application of optimal
control and adaptation models of human motor control to robotics:
- The inverse optimal control being ill-posed, how can we determine the
cost function underlying human movements?
- Do we truly behave optimally in some sense?
- Shall we address whole body control with standard optimal control
approaches, or are there some higher level organization principles to be
considered?
- What are the next challenges to be addressed?
TOPICS
- Optimal control methods and their derivatives
- Reinforcement learning methods for robotics
- Practical implementations of the above methods in robots
- Humans to humanoids transfer
- Models of human movements based on optimality : successes and
limitations
INTENDED AUDIENCE
The workshop will bring together roboticists, optimal control and machine
learning experts interested in the use of these methods in robots, as well
as computational neurosciences researchers interested in modeling these
processes in animals and humans, so as to generate a fruitful discussion
between both communities.
CONFIRMED SPEAKERS
• Jan Babic (Josef Stefan Institute, Ljubjana, Slovenia)
• Etienne Burdet (Imperial College, London, UK)
• Martin Butz (University of Tübingen, Germany)
• Jean-Paul Laumond (LAAS-CNRS, Toulouse, France)
• Katja Mombaur (Ruprecht-Karls-Universität Heidelberg, Germany)
• Pietro Morasso (Istituto Italiano di Tecnologia, Genova, Italy)
• Jan Peters (Technische Universitaet Darmstadt, Germany)
• Stephen Scott (Queen's University, Kingston, Canada)
• Sethu Vijayakumar (University of Edinburgh, UK)
• Evangelos Theodorou (University of Southern California, USA)
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CALL FOR CONTRIBUTIONS
The workshop will also feature a session for posters and short
presentations.
Prospective participants are required to submit an extended abstracts (4
pages maximum), optionally accompanied by a video. Submissions must be in
pdf, following the IEEE conference style (two-column). All contributed
workshop presentations are subject to a peer review process.
Authors wishing to give a talk should mention it when sending their
abstract: upon available time, selected contributions may have the
opportunity to be presented in the oral session.
Other selected contributions will be presented as posters during dedicated
sessions.
Important dates:
July 10, 2012: Extended abstracts submission deadline
July 30, 2012: Notification of acceptance
August 31, 2012: Final paper due
Submission:
Please send your contribution via e-mail directly to the Workshop organizers
( h2h_iros12@isir.upmc.fr ) with the tag IROS2012.
For more information see:
http://macsi.isir.upmc.fr/index.php?perma=iros2012workshop
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Serena Ivaldi, PhD
Institut des Systèmes Intelligents et de Robotique
Université Pierre et Marie Curie
Pyramide - T55/65 CC 173
4 Place Jussieu - 75005 Paris
www.isir.upmc.fr
Tel: +33 (0) 1 44 27 96 23
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