Vision Based Environment Recognition and Movement Control for Autonomous Wheeled Mobile Robots

This paper presents an experimental study on environment recognition and movement control for multiagent robotic soccer using wheeled mobile robots. A color image segmentation method based on YUV color information of each pixel of the color image is applied to the object recognition. The color image segmentation is performed using the tables that transform each value in a pixel to membership in several color classes, where the lower and higher threshold values of Y, U, and V are determined and described for the sample color markers. The position of objects on the field is efficiently and accurately calculated using a monocular camera. A common image processing method is used to detect landmarks such as corners/edges in the environment. A movement control algorithm is implemented based on the distance and orientation to the target. Experimental results of real-time movement control are also presented.