This paper presents a fast approach for vision-based self-localization in RoboCup. The
vision system extracts the features required for localization without processing the whole …

Robotics researchers have been focusing on develo** autonomous and human-like
intelligent robots that are able to plan, navigate, manipulate objects, and interact with …

In RoboCup soccer, ball localization is an important and challenging task, especially since
the last change of the rule which allows 50% of the ball's surface to be of any color or pattern …

This paper presents a fast approach for edge-based self-localization in RoboCup. The vision
system extracts edges between the field and field lines, borders, and goals following a grid …

This paper presents a real-time approach for object recognition in robotic soccer. The vision
system does not need any calibration and adapts to changing lighting conditions during run …

This paper presents a predictive controller for intercepting mobile targets. A global vision
system is used to identify fast moving objects and uses a color threshold technique to …

Colour labeling is critical to the real-time performance of colour-based vision systems and is
used for low-level vision by most RoboCup 2002 physically based teams. Unfortunately …

Static color classification as a first processing step of an object recognition system is still the
de facto standard in the RoboCup Standard Platform League (SPL). Despite its efficiency …

Object recognition and localization methods in RoboCup work on color segmented camera
images. Unfortunately, color labeling can be applied to object recognition tasks only in very …

Robot recognition is a very important point for further improvements in game-play in
RoboCup middle size league. In this paper we present a neural recognition method we …