Connectionists: Special Issue on “Emerging Spatial Competences: From Machine Perception to Sensorimotor Intelligence”
Agostino Gibaldi
agostino.gibaldi at unige.it
Wed Jan 22 11:58:50 EST 2014
Dear Researcher,
due to multiple requestes, we kindly inform you that the deadline for
the Special Issue on “Emerging Spatial Competences: From Machine
Perception to Sensorimotor Intelligence”
<http://www.journals.elsevier.com/robotics-and-autonomous-systems/call-for-papers/emerging-spatial-competences-machine-perception/>
for the RAS - Robotics and Autonomous Systems, has been extended to
February 15, 2014.
The Special Issue (see below for a more detailed description) aims to
investigate how the mutual influence between the perception of the
environment and the interaction with it can be extended to support
co-evolution mechanisms of perceptual and motor processes.
* Robotics and Autonomous Systems Journal*
*
*
**
*Special Issue on “Emerging Spatial Competences: From Machine Perception
to Sensorimotor Intelligence”*
CALL FOR PAPERS
*_Aims and Objectives_***
Following the recent evolution of robotics and AI in different fields of
application, the increasing complexity of the *actions* that an
artificial**agent needs to perform, is directly dependent on the
complexity of the *sensory information *that it can acquire and
*interpret*, /i.e./ *perceive*.
From this point of view, an efficient and internal representation of
the sensory information is at the base of a robot to develop a
*human-like capability* of interaction with the surrounding environment.
Particularly, in the space at a *reachable distance*, not only visual
and auditory, but also tactile and proprioceptive information rise to be
relevant to gain a comprehensive spatial cognition. This information,
coming from different senses, can be in principle integrated and used to
experience an awareness of the environment both to actively interact
with it, and to calibrate the interaction itself. Besides, the early
sensory and sensorimotor mechanisms, that at a first glance may appear
simple processes, are grounded on highly structured and complex
algorithms that are far from being understood and modeled. By exploiting
an early synergy between *sensing modules*and *motor control*, the loop
between action and perception comes to be not just closed at system
level, but shortened at an inner one. This would allow not only the
emergence of *spatial competences* but also their *continuous
adaptation*to changes in the environment or in the body, which could
modify its interactions with the world.
The aim of this special issue is to survey a state of the art of
methodologies, concepts, algorithms and techniques that would serve as
bricks on which to build and develop artificial agents with such a
spatial competence; perceptual and cognitive understanding of space
should emerge from sensorimotor exercise.
The *action-perception loop* has never been so close!
*_Paper Submission_***
We invite original contributions that provide novel solutions to address
the relevant topics including but not limited to:
§Theoretical or practical aspects of machine sensing (for computer
vision, robot audition, artificial touch, etc.)
§Multisensory data fusion, processing, learning and integration
§Computational neural modeling
§Embodied robotics: perception, cognition, and behaviors
§Machine learning for sensorimotor control and intelligence
§Neural networks: models, theories, learning algorithms and applications
§Engineering application of sensorimotor intelligence to pattern
recognition, computer vision, speech recognition, human-robot interactions.
As a follow-up of the IJCNN 2013 special session, we invite in
particular the special session participants to submit profoundly
extended versions of their conference submission to go through a new
peer review process, together with contributions not published in the
conference proceedings. **
Papers should be typeset according to the format instructions for the
Robotics and Autonomous Systems Journal, available on the Elsevier web
site
(http://www.elsevier.com/journals/robotics-and-autonomous-systems/0921-8890/guide-for-authors).
*_Important Dates_*
§*February 15, 2014***January 31, 2014: Paper submission deadline
§March 31, 2014: Notification of paper acceptance
§April 30, 2014: Camera ready paper submission
§Late Spring 2014: Expected publication date
*_Guest editors_***
*Agostino Gibaldi*, agostino.gibaldi at unige.it
Department of Informatics, Bioengineering, Robotics and System Engineering
University of Genoa, Italy
Advanced ResearchCenteron Electronic Systems (ARCES)
University of Bologna, Italy
/Agostino Gibaldi received his degree in Biomedical Engineering from the
University of Genoa, Italy, in 2007, and his Ph.D. in 2011. Since the
master thesis he is with the Physical Structure of Perception and
Computation (PSPC) Group where he is actually a post doc. Recently, he
joined the Computer Vision Group of the //Advanced Research Center on
Electronic Systems (ARCES), working on data analysis computer aided
diagnosis for CT perfusion related to tumour lesions. //His research
interests are related to cortical models of V1, MT and MST areas, in
relation with the estimation of disparity, the control of vergence eye
movements, and the optic flow analysis for navigation, for their
real-time implementation on robot platforms so to obtain active
behaviours and adaptation to the environment. Aside, he also worked on
neural networks and learning, eye tracking algorithms, camera
calibration, 3D data modelling for virtual reality, CT perfusion and
image registration./
//
*Silvio P. Sabatini* <http://www.pspc.unige.it/>, silvio.sabatini at unige.it
Department of Informatics, Bioengineering, Robotics and System Engineering
University of Genoa, Italy
http://www.pspc.unige.it/~silvio/home/
<http://www.pspc.unige.it/%7Esilvio/home/>
/Silvio P. Sabatini received the Laurea Degree in Electronics
Engineering and the Ph.D. in Computer Science from the //University//of
//Genoa//in 1992 and 1996. He is currently Associate Professor of
Bioengineering at the Department of Informatics, Bioengineering,
Robotics and System Engineering of the //University//of //Genoa//. In
1995 he promoted the creation of the “Physical Structure of Perception
and Computation” (PSPC) Lab to develop models that capture the
“physicalist” nature of the information processing occurring in the
visual cortex, to understand the signal processing strategies adopted by
the brain, and to build novel algorithms and architectures for
artificial perception machines. His research interests relate to visual
coding and multidimensional signal representation, early-cognitive
models for visually-guided behavior, and robot vision. He is author of
more than 100 papers in peer-reviewed journals, book chapters and
international conference proceedings./
//
*Sylvain Argentieri* <http://people.isir.upmc.fr/argentieri>,
sylvain.argentieri at upmc.fr
Institute for Intelligent Systems and Robotics (ISIR)
Université Pierre et Marie Curie, Paris, France
http://www.isir.upmc.fr/index.php?op=view_profil&id=113&old=N&lang=fr
<http://www.isir.upmc.fr/index.php?op=view_profil&id=113&old=N%E2%8C%A9=fr>
/Sylvain Argentieri received his Master's degrees in Robotics from the
Pierre et Marie Curie University, Paris, and in Electronics from Ecole
Normale Supérieure, Cachan, France, in 2003. He then received his Ph.D.
in Computer Science from the //Paul////Sabatier////University//,
//Toulouse//, //France//, in 2006. After two years as an Assistant
Professor at LAAS-CNRS (Laboratory for Analysis and Architecture of
Systems) in the same University, he is now Associate Professor at the
"Active Multimodal Perception" group in the Institute for Intelligent
Systems and Robotics of the //Pierre//et
//Marie////Curie////University//since 2008. He also obtained in 2002 the
highest teaching diploma in //France//(Agrégation externe) in
Electronical Science. His research interests relate to artificial
audition in a robotics context, from array processing methods to
binaural approaches, for sound source localization, speaker recognition,
human-robot interaction, etc. He is also interested in active approaches
to multimodal perception and sensorimotor integration./
//
*Zhengping Ji*, jizhengp at gmail.com <mailto:jizhengp at gmail.com>
Advanced Image Research Laboratory (AIRL)
Samsung, Pasadena, CA, U.S.A
http://cnls.lanl.gov/External/people/Zhengping_Ji.php
/Zhengping Ji received his B.S. degree in Electrical Engineering from
Sichuan University//, //China, in 2003 and the Ph.D. in Computer Science
from Michigan State University, USA, in 2008. From 2009 to 2010, he held
a postdoctoral fellow position at the Center for the Neural Basis of
Cognition, //Carnegie////Mellon////University//, working on the DARPA
RealNose Project. After that, he spent two years in Los Alamos National
Laboratory, where he was a Research Associate conducting researches on
computational modelling of the brain’s visual pathways. He is now a
Senior Research Scientist at Advanced Image Research Laboratory of
Samsung Electronics. His current research interests lie in computer
vision, computational neuroscience and machine learning. Specifically,
he seeks to develop a series of deep learning models to generate
cortex-like hierarchical sparse representation for a variety of tasks in
vision, including generic object recognition, object detection and
segmentation, image denoising and compression, and vision-based
autonomous navigation. He is a Vice Chair of Task Force on Bio-Inspired
Self-Organizing Collective Systems at IEEE Computational Intelligence
Society, and a committee member of the Brain-Mind Institute, USA./
//
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