Research On Target Recognition And Control Method Of Grasping With Binocular Household Robot

This research closely relies on the household robot platform in the intelligent robot Lab of South China University of Technology, analyzing the household robot particularly. This study gets access to some important research results and conclusions.First it builds binocular robot vision servo control system's framework, including camera calibration, target image acquisition and processing, getting the depth information of the target point, space coordinate transformation, kinematics modeling and analysis, and visual servo control system. Then we establish the kinematics model for our household robot based on the D-H method, and the inverse kinematics was carried out. We research the relationship of the dynamic robot hand-eye coordinate transformation.This study particularly analyses the characteristics of SIFT object recognition algorithm and its application in robot target recognition, we propose a method which combines Snake model and SIFT target recognition algorithm to solve the issue that we can't obtain enough target contour information from the traditional robot target recognition process, and it integrate the target information to the target capture process using robot arm end-effector. We use Visual Studio 2005 development platform to achieve the correlation algorithm.This paper researches the robot visual servo system, and analyses the related techniques of the traditional position-based visual servo system. According to the traditional method's deficiency in the target capture process with robot hand, and the relationship of the Jacobian matrix in robot differential kinematics, we propose the improved position-based visual servo system control method. The main idea of this control method is to control the robot hand to reach the target approximate location using inverse kinematics, then to calculate the Jacobian matrix of the robot hand on line, and finally to enable robot hand to reach the target precise position and grasp the target object. We Proved the effectiveness of this theory by experiment.