[robotics-worldwide] [meetings] CFP: ICRA 2017 Workshop on Learning and control for autonomous manipulation systems: the role of dimensionality reduction

Pietro Falco pietro.falco at tum.de
Tue Mar 21 06:57:35 PDT 2017

[Apologies for multiple copies of this announcement]

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

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

Workshop webpage:



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 <mailto: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 < 10 MB)
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


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 <mailto: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.


Important Dates:

Abstract submission: 7 April, 2017

Proposal for Demo Submission: 7 April,

Notification of acceptance: 21 April, 2017

Workshop: 2 June, 2017


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


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



Dr. Fanny Ficuciello


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 <mailto:fanny.ficuciello at unina.it>


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 <mailto:sylvain.calinon at idiap.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 <mailto:pietro.falco at tum.de>


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