Συντάχθηκε 07-10-2014 14:24
από Esthir Gelasaki
Email συντάκτη: egelasaki<στο>tuc.gr
Ενημερώθηκε:
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Ιδιότητα: υπάλληλος.
ΠΟΛΥΤΕΧΝΕΙΟ ΚΡΗΤΗΣ
Σχολή Ηλεκτρονικών Μηχανικών και Μηχανικών Υπολογιστών
Πρόγραμμα Προπτυχιακών Σπουδών
ΠΑΡΟΥΣΙΑΣΗ ΔΙΠΛΩΜΑΤΙΚΗΣ ΕΡΓΑΣΙΑΣ
ΙΩΑΝΝΗ ΛΙΒΕΡΙΟΥ-ΜΑΡΙΝΟΥ
με θέμα
Οπτική Αναγνώριση και Αξιοποίηση
Χρωμάτων και Διαγράμμισης γηπέδου
για το πρωτάθλημα Standard Platform του RoboCup
Visual Color and Field Line
Recognition and Exploitation
for the RoboCup Standard Platform League
Πέμπτη 9 Οκτωβρίου 2014, 10πμ
Αίθουσα Εργαστηρίου Intelligence, Κτίριο Επιστημών,
Πολυτεχνειούπολη
Εξεταστική Επιτροπή
Αναπληρωτής Καθηγητής Μιχαήλ Γ. Λαγουδάκης (επιβλέπων)
Επίκ. Καθ. Γεώργιος Χαλκιαδάκης (ΗΜΜΥ)
Καθ. Μιχάλης Ζερβάκης (ΗΜΜΥ)
Abstract
In order to complete complex tasks, both humans and robots are bound by one of the
most important senses, the visual sense, which helps them perceive the state of the
environment that surrounds them. Robotic soccer, known as RoboCup, represents a
complex, stochastic, real-time, multi-agent, competitive domain for autonomous robots.
In such domains, the ability to understand the environment is critical for the
accomplishment of the assigned task and is required for a range of activities, such as
locomotion, coordination, and decision making. This thesis focuses on two specific
aspects of robot visual perception, color and field line recognition, in order to
complement prior work on this problem by our RoboCup team “Kouretes”. In RoboCup,
the objects of interest are characterized by unique colors (orange ball, green field,
yellow goalposts, white lines) and their recognition relies on the correct identification of
image areas corresponding to the same color. However, the problem of color recognition
is highly affected by the environment illumination conditions, as well as the robot's
camera settings. In this thesis, we propose a new approach to color recognition, which
relies on modeling off-line the signatures of the target colors in the color space under
different illuminations using density estimation with Gaussian distributions and
dynamically identifying and using the correct models by exploiting a metric on the most
common color in the RoboCup environment (green). On the problem of field line
recognition, we focus on identifying a variety of field line landmarks (straight lines,
center circle, corners, T-lines), which are useful for localization. This is accomplished by
searching for white pixels in the camera images, selectively keeping those that can be
part of a line, and then identifying each type of line using curve fitting techniques. For
each recognized line landmark, we use geometry and projection techniques to estimate
its distance and bearing with respect to the robot. Our work contributes an off-line tool
for color recognition and a real-time module for field line recognition appropriate for onboard execution on the Aldebaran Nao humanoid robots. The proposed methods perform
reliably in most cases, failing only in extreme cases, which are typically infrequent
during RoboCup games.
