A hybrid vision system for soccer robots using radial search lines

The recognition of colored objects is very important for robot vision in RoboCup Middle Size League competition. This paper describes an efficient hybrid vision system developed for the robotic soccer team of the University of Aveiro, CAMBADA (Cooperative Autonomous Mobile roBots with Advanced Distributed Architecture). The hybrid vision system integrates an omnidirectional and a perspective camera. The omnidirectional sub-system is used by our localization algorithm for finding the ball, detecting the presence of obstacles and white lines. The perspective vision is used to find the ball and obstacles in front of the robot at larger distances, which are difficult to detect using the omnidirectional vision system. In this paper, we present a set of algorithms for efficiently extracting the color information of the acquired images and, in a second phase, for extracting the information of all objects of interest. We developed an efficient color extraction algorithm based on lookup tables and we use a radial model for object detection, both in the omnidirectional and perspective sub-system. The CAMBADA middle-size robotic soccer team won the 2007 Portuguese Robotics Festival and ranked 5th in the 2007 RoboCup World Championship. These results show the effectiveness of our algorithms. Moreover, our experiments show that the system is fast and accurate having a constant processing time independently of the environment around the robot, which is a desirable property of Real-Time systems.