Digital Object Identifier: 10.1109/
TAMD.2014.2341351
"Vision gives primates a wealth of
information useful to manipulate the
environment, but at the same time it can
easily overwhelm their computational
resources. Active vision is a key solution
found by nature to solve this problem: a
limited fovea actively displaced in space
to collect only relevant information.
Here the authors highlight that in eco-
logical conditions this solution encounters four problems: 1) the agent needs to
learn where to look based on its goals;
2) manipulation causes learning feedback in areas of space possibly outside
the attention focus; 3) good visual
actions are needed to guide manipulation actions, but only these can generate
learning feedback; and 4) a limited fovea
causes aliasing problems. The authors
then propose a computational architec-
ture ("BITPIC") to overcome the four
problems. The system is tested with a
simple simulated camera-arm robot
solving a class of search-and-reach tasks.
The results show that the architecture
solves the problems, and hence the tasks,
very efficiently, and highlight how the
architecture principles can contribute to
a full exploitation of the advantages of
active vision in ecological conditions."
Call for Papers for Journal Special Issues
Special Issue on "Computational Intelligence Software"
Journal: IEEE Computational Intelligence Magazine
Guest Editors: Jesús Alcalá-Fdez, José M. Alonso, Oscar Cordón
Submission Deadline: August 15, 2015
Publication: May 2016
Further Information: Jesús Alcalá-Fdez (jalcala@decsai.ugr.es)
http://sci2s.ugr.es/ieeecimcisw2016/
Digital Object Identifier 10.1109/MCI.2015.2437571
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