Title: A Monocular Vision System for Playing Soccer in Low Color Information Environments,
Abstract: Humanoid soccer robots perceive their environment exclusively through
cameras. This paper presents a monocular vision system that was originally
developed for use in the RoboCup Humanoid League, but is expected to be
transferable to other soccer leagues. Recent changes in the Humanoid League
rules resulted in a soccer environment with less color coding than in previous
years, which makes perception of the game situation more challenging. The
proposed vision system addresses these challenges by using brightness and
texture for the detection of the required field features and objects. Our
system is robust to changes in lighting conditions, and is designed for
real-time use on a humanoid soccer robot. This paper describes the main
components of the detection algorithms in use, and presents experimental
results from the soccer field, using ROS and the igus Humanoid Open Platform as
a testbed. The proposed vision system was used successfully at RoboCup 2015.