[robotics-worldwide] [journals][CfP] Special Issue on "Computational Models of Affordance for Robotics" in Frontiers in Neurorobotics

Erwan Renaudo erwan.renaudo at uibk.ac.at
Fri Jul 5 04:30:41 PDT 2019

*Apologies for cross-posting*


Special Issue on "Computational Models of Affordance for Robotics"  in 
Frontiers in Neurorobotics


Gibson's theory of affordance, in its adherence to bottom-up direct 
perception, is
antithetical to the top-down inferential models often proposed by modern 
research purporting to tackle it. Such research assumes internal 
representation to
be sacrosanct, but given current developments, to what extent can this 
now be reexamined? The recently proposed sensorimotor contingency theory 
the theoretical argument that internal representation is unnecessary, 
and its
proof-of-concept application in robotics as well as the subsequent 
explosion in
deep learning methodology sheds new light on the possibility of 
equipping robots
with the capacity for directly perceiving their environments by 
exploiting correlated
changes in their sensory inputs triggered by executing specific motor 
programs. This
reexamination of direct perception is only one of several issues 
warranting scrutiny
in current robotic affordance research.

The aim of this special issue is to highlight the relevance of Gibson's 
notion of
affordance for developmental and cognitive robotics. The issue is focused on
contributions from the current panorama of robotics with an emphasis on 
from the ecological, cognitive, developmental and sensorimotor accounts.

We welcome submissions of all types (original research articles, 
reviews, short
communications, and opinions) related to affordances and robotics, 
including but
not limited to the following topics:

- Affordance learning
- Multimodal affordance learning
- Affordance perception and vision for affordances
- Perceptual learning and development
- Babbling and exploration
- Language and affordances
- Learning from observation and mirroring
- Self-organization of knowledge
- Deep learning of affordances
- Bayesian learning of affordances
- Concept learning
- Symbol emergence
- Symbol grounding
- Sensorimotor contingency theory
- Behavior affording behavior
- Actions and functions in object perception
- Brain-body-environment systems
- Agent-environment systems
- Selective attention
- Self-supervised learning
- Sensing physical properties
- Ecologically intuitive physics

This special issue is being released in conjunction with the 2nd 
Workshop on "Computational Models of Affordance in Robotics" 
(https://urldefense.proofpoint.com/v2/url?u=https-3A__r1d1.github.io_iwcmar_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=te31E4jL9hUy6azZS4fK0clsdv8RTAu1cZm0ENEcF3A&s=ENuFZZr1kIsNRLD7x7zCc1HrUtACBhKlQTTk4kTRorE&e= )
that was held at the 2019 International Conference on Robotics and 
Automation (ICRA) in Montréal, Canada.

Submission of full manuscript:  **October 13, 2019**

Full manuscripts should comply with Frontiers author's guidelines:


Mehdi Khamassi, Centre National de la Recherche Scientifique
mehdi.khamassi at upmc.fr

Philipp Zech, University of Innsbruck
Erwan Renaudo, University of Innsbruck
Raja Chatila, Pierre and Marie Curie University

Intelligent and Interactive Systems Lab <https://urldefense.proofpoint.com/v2/url?u=https-3A__iis.uibk.ac.at_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=te31E4jL9hUy6azZS4fK0clsdv8RTAu1cZm0ENEcF3A&s=bnpgT4gmO2OKCHF7l_PZE2Y-21Wq_n8Sri_GUqyu4lI&e= >
University of Innsbruck, Austria

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