Object Recognition and Localization Algorithm base on NAO Robot

Abstract

Object recognition and localization technology based on robot vision plays an important role in robot motion, obstacle avoidance, object grabbing and multi robot cooperation. The object recognition and localization algorithm provided by NAO robot official documents is not robust to different light conditions. It often causes misjudged or low accuracy. This paper uses the method of adaptive luminance RGB, combined with median filter, Hough circle detection, according to the color difference image segmentation technology, greatly reduce the misjudged and improve the accuracy. Then we use the transformation between image coordinate system and three-dimensional space coordinate system to get more precise object location. By analyzing the error of experimental data, a linear error compensation algorithm is added for different area errors, which further improves the positioning accuracy. The average error is reduced to 0.37 centimeters.