Connectionists: ICRA 2017 Workshop: "Learning and control for autonomous manipulation systems: the role of dimensionality reduction"

Thu Apr 6 12:41:31 EDT 2017

[Apologies for multiple copies of this announcement]

ICRA 2017 Workshop on Learning and control for autonomous manipulation  
systems: the role of dimensionality reduction
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Dear colleagues,
we invite you to submit your contributions to the ICRA 2017 Full Day  
Workshop "Learning and control for autonomous manipulation systems:  
the role of dimensionality reduction".
The Workshop will be held at ICRA 2017 on June 2, 2017 from h. 8:30 to 17:00.

Workshop webpage: http://www.icra2017-ws-lecom.unina.it/

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Call for Papers
---------------

We invite you to submit short papers (2-4 pages) or full papers (6  
pages), using the standard ICRA template.
Please send your contribution in pdf format to lecom.icra2017 at gmail.com.
The submissions will be reviewed based on relevance and quality.
Multimedia material is optional and can be sent as a zip file (if  
<10MB) or with a google drive/dropbox/youtube link.
Accepted contributions will be included in the workshop program with a  
spotlight presentation followed by an interactive session.

The workshop contributions will appear as online proceedings.
Contributors to the workshop will be invited to submit extended
versions of the manuscripts to a special issue (publisher to be  
announced during the Workshop).
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Call for Demos
--------------

We invite you to show a demo of your recent work. In order to  
participate, please send a 1-page description of the demo in a pdf  
format to lecom.icra2017(at)gmail.com.
Optionally, a video can be included in a zip file (if < 10MB) or  
shared with a suitable application. Please include in your proposal  
basic requirements such as screens, plugs, and desks.

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Important Dates:
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Abstract submission: 14 April, 2017

Proposal for Demo Submission: 14 April,

Notification of acceptance: 24 April, 2017

Workshop: 2 June, 2017

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Topic and Objectives
--------------------

New generation of robots, to serve and substitute humans in various
kinds of application, should have comparable abilities to deftly
move, autonomously learn and make decisions. Analytical approaches to
manipulation require precise model of the objects, accurate
description of the task, and evaluation of object affordance, which
all make the process time consuming. To learn and execute new tasks
just as humans do, i.e. through trial-and-error and compliant
adaptation to the environment, human-like physical interaction is
crucial. Therefore, advanced mechanical designs such as tendon-driven
actuation, underactuated compliant mechanisms and
hyper-redundant/continuum robots might exhibit enhanced capabilities
of adapting to changing environments. As a matter of fact, high
degrees of freedom (DoF) and compliance increase the complexity of
modelling and control of these devices. To this purpose, the adoption
of coordinated motion patterns leads to a problem of reduced
dimension. As a consequence, model-based control strategies of
manipulation activities can be learned from human experience and,
relying on dimensionality reduction, can be integrated with
model-free reinforcement learning algorithms which have the potential
to learn from actions.

The purpose of the workshop is to portray the level of autonomy that
anthropomorphic robotic systems have reached today and to chart
possible paths towards improved manipulation capabilities by means of
self-adaptability to the environment. The workshop intends to
spotlight how autonomy depends on the ability to adapt to the
environment by learning from experience, and how, for this purpose,
physical interaction is critical and consequently smart design makes
the difference. This workshop aims at discussing the integration of
learning, control and design aspects that should not be separated in
the complex problem of robotic manipulation. Indeed, these aspects
can interact and take advantage of one another being inspired by the
functioning, reasoning and physical resemblance of human beings. Of
course, in this contest the perception is involved in the process and
the integration of visual and tactile sensing is a crucial issue
during the interaction with the environment.

Some of the questions we will try to answer are:

-How human experience can help to develop new paradigm for  
anthropomorphic devices control
-How a synergistic approach can help to simplify modeling of high  
degrees of freedom systems
-How dimensionality reduction will help the learning process
-How vision and tactile information can be integrated in the learning  
process and in control strategies

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Topics of interest include but not limited to the following
-----------------------------------------------------------

-Dimensionality reduction in anthropomorphic design: mechanical and  
motor-synergies
-Model of reduced dimensions learned from humans for control  
simplification of high degrees of freedom devices
-Synergy-based learning and control strategies -Learning visual  
representations for perception-action systems
-Learning grasping and manipulation from tactile information
-Vision and force integration for autonomous control of manipulation systems
-Dynamic movement primitives
-Imitation learning and Reinforcement learning

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Organizers
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Dr. Fanny Ficuciello
PRISMA Lab
Department of Electrical Engineering and Information Technology
University of Naples Federico II via Claudio 21, 80125, Naples, Italy
phone: +39 081 7683916
fanny.ficuciello at unina.it
http://wpage.unina.it/fanny.ficuciello

Dr. Sylvain Calinon
Idiap Research Institute
Centre du Parc
Rue Marconi 19, PO Box 592, CH-1920 Martigny, Switzerland
phone: +41 27 721 77 61
sylvain.calinon at idiap.ch
http://calinon.ch/

Dr. Pietro Falco
Marie Curie Fellow
Technische Universität München
Department of Dynamic Human-Robot-Interaction for Automation Systems
Karlstraße 45, 5. OG. 80333 München,
phone: +49(89) 289-26885
pietro.falco at tum.de
https://www.hri.ei.tum.de/en/team/pietro-falco/

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PhD. Eng. Fanny Ficuciello
Dipartimento di Ingegneria Elettrica e
Tecnologie dell'Informazione
Università di Napoli Federico II
Via Claudio 21, 80125 Napoli, ITALY
Tel: +39 0817683186
e-mail: fanny.ficuciello at unina.it
Skype: fficuciello
URL: http://wpage.unina.it/fanny.ficuciello/
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