The workpiece frames relative to each robot base frame should be known in advance for the proper operation of twin-robot nondestructive testing system. However, when two robots are separated from the workpieces, the t...The workpiece frames relative to each robot base frame should be known in advance for the proper operation of twin-robot nondestructive testing system. However, when two robots are separated from the workpieces, the twin robots cannot reach the same point to complete the process of workpiece frame positioning. Thus, a new method is proposed to solve the problem of coincidence between workpiece frames. Transformation between two robot base frames is initiated by measuring the coordinate values of three non-collinear calibration points. The relationship between the workpiece frame and that of the slave robot base frame is then determined according to the known transformation of two robot base frames, as well as the relationship between the workpiece frame and that of the master robot base frame. Only one robot is required to actually measure the coordinate values of the calibration points on the workpiece. This requirement is beneficial when one of the robots cannot reach and measure the calibration points. The coordinate values of the calibration points are derived by driving the robot hand to the points and recording the values of top center point（TCP） coordinates. The translation and rotation matrices relate either the two robot base frames or the workpiece and master robot. The coordinated are solved using the measured values of the calibration points according to the Cartesian transformation principle. An optimal method is developed based on exponential mapping of Lie algebra to ensure that the rotation matrix is orthogonal. Experimental results show that this method involves fewer steps, offers significant advantages in terms of operation and time-saving. A method used to synchronize workpiece frames in twin-robot system automatically is presented.展开更多
This paper proposes an uncalibrated workpiece positioning method for peg-in-hole assembly of a device using an industrial robot.Depth images are used to identify and locate the workpieces when a peg-in-hole assembly t...This paper proposes an uncalibrated workpiece positioning method for peg-in-hole assembly of a device using an industrial robot.Depth images are used to identify and locate the workpieces when a peg-in-hole assembly task is carried out by an industrial robot in a flexible production system.First,the depth image is thresholded according to the depth data of the workpiece surface so as to filter out the background interference.Second,a series of image processing and the feature recognition algorithms are executed to extract the outer contour features and locate the center point position.This image information,fed by the vision system,will drive the robot to achieve the positioning,approximately.Finally,the Hough circle detection algorithm is used to extract the features and the relevant parameters of the circular hole where the assembly would be done,on the color image,for accurate positioning.The experimental result shows that the positioning accuracy of this method is between 0.6-1.2 mm,in the used experimental system.The entire positioning process need not require complicated calibration,and the method is highly flexible.It is suitable for the automatic assembly tasks with multi-specification or in small batches,in a flexible production system.展开更多
基金Supported by International S&T Cooperation Program of China(Grant No.2012DFA70260)High-end CNC Machine and Basic Manufacturing Equipment of Chinese Key National Science and Technology(Grant No.2011ZX04014-081)
文摘The workpiece frames relative to each robot base frame should be known in advance for the proper operation of twin-robot nondestructive testing system. However, when two robots are separated from the workpieces, the twin robots cannot reach the same point to complete the process of workpiece frame positioning. Thus, a new method is proposed to solve the problem of coincidence between workpiece frames. Transformation between two robot base frames is initiated by measuring the coordinate values of three non-collinear calibration points. The relationship between the workpiece frame and that of the slave robot base frame is then determined according to the known transformation of two robot base frames, as well as the relationship between the workpiece frame and that of the master robot base frame. Only one robot is required to actually measure the coordinate values of the calibration points on the workpiece. This requirement is beneficial when one of the robots cannot reach and measure the calibration points. The coordinate values of the calibration points are derived by driving the robot hand to the points and recording the values of top center point（TCP） coordinates. The translation and rotation matrices relate either the two robot base frames or the workpiece and master robot. The coordinated are solved using the measured values of the calibration points according to the Cartesian transformation principle. An optimal method is developed based on exponential mapping of Lie algebra to ensure that the rotation matrix is orthogonal. Experimental results show that this method involves fewer steps, offers significant advantages in terms of operation and time-saving. A method used to synchronize workpiece frames in twin-robot system automatically is presented.
文摘This paper proposes an uncalibrated workpiece positioning method for peg-in-hole assembly of a device using an industrial robot.Depth images are used to identify and locate the workpieces when a peg-in-hole assembly task is carried out by an industrial robot in a flexible production system.First,the depth image is thresholded according to the depth data of the workpiece surface so as to filter out the background interference.Second,a series of image processing and the feature recognition algorithms are executed to extract the outer contour features and locate the center point position.This image information,fed by the vision system,will drive the robot to achieve the positioning,approximately.Finally,the Hough circle detection algorithm is used to extract the features and the relevant parameters of the circular hole where the assembly would be done,on the color image,for accurate positioning.The experimental result shows that the positioning accuracy of this method is between 0.6-1.2 mm,in the used experimental system.The entire positioning process need not require complicated calibration,and the method is highly flexible.It is suitable for the automatic assembly tasks with multi-specification or in small batches,in a flexible production system.
