The ability to perceive
and understand our dynamic real world is critical for the next
generation of multi-sensory robotic systems. One of the most important
tasks is the one of search. Biological mechanisms for search are seen
as adaptive process that searches for objects of interest managing the
limited available processing. In actual fact, cognitive robots also
require attention mechanisms to determine which parts of the sensory
array they need to process, in a way similar to what biological systems
do. In other words, attention consists in selecting the most relevant
information from multi-sensory inputs to perform efficiently the search
of a target.
A first mechanism consists of a bottom-up approach that is
the scenario and happens at a very early processing stage. This
mechanism also includes some prior symbolic contextual knowledge about
the target un-der consideration. This knowledge determines to a large
extent the area that the robot will have to examine first, and it is
usually expressed in natural language in the form of resources such as
lexica and ontologies and could be directly accessible by the robot to
narrow down the visual search space.
Then, when the robot decides to examine a specific selected area, the robot should have the model of the target with information about its shape, size, color, or texture. This model should describe the target enough to allow the robot to efficiently find a small number of candidates, in order to proceed inspecting each one for segmentation. This second process is voluntary and is called top-down attention.
The project aims to integrate bottom up with top down attention and develop the resulting mechanism in hardware. It is an interdisciplinary project involving linguistics and knowledge engineering (these amount to tools necessary for the robot to deduce that it has to search the floor if it is given the command: “search for the shoes”), computer vision and image processing (these amount to tools necessary for the robot to use color, texture, shape and size for finding the target), distributed control and VLSI design.