Abstract
The design of a high-precision robot assembly system is a great challenge. In this article, a robotic assembly system is developed to assemble two components with six degree-of-freedoms in three-dimensional space. It consists of two manipulators, a structured light camera which is mounted on the end-effector aside component A to measure the pose of component B. Firstly, the features of irregular components are extracted based on U-NET network training with few labeled images. Secondly, an algorithm is proposed to calculate the pose of component B based on the image features and the corresponding three-dimensional coordinates on its ellipse surface. Thirdly, the six errors including two position errors and one orientation error in image space, and one position error and two orientation errors in Cartesian space are computed to control the motions of component A to align with component B. The hybrid visual servoing method is used in the control system. The experimental results verify the effectiveness of the designed system.
Highlights
With the development of technology, the demand for highprecision assembly in industrial manufacturing and space exploration is increasing.[1,2,3] Industrial assembly devices are generally divided into two categories
Meng et al.[7] realized precise robot assembly for large-scale spacecraft components based on computer-aided design models of aircraft components and key geometric features located by ranging sensors and binocular vision
The elliptical ring area containing the groove of the desired image is extracted by trained U-NET network
Summary
With the development of technology, the demand for highprecision assembly in industrial manufacturing and space exploration is increasing.[1,2,3] Industrial assembly devices are generally divided into two categories. The computer can control the entire assembly process including image capture with the camera, image processing, feature extraction, pose estimation, and alignment and insertion of the two components. The desired image capture stage is mainly to obtain the desired image and the displacement of the manipulator between the alignment and insertion positions via one assembly manually controlled. Manipulator 1 is translated along the x-axis in its end-effector frame until the camera can capture the image of component B. The elliptical ring area containing the groove of the desired image is extracted by trained U-NET network. A hybrid visual servoing control system is designed, in which the features from image space and Cartesian space are combined to realize the alignment between component B and camera. The features from image space are used to control translations along the x-axis and y-axis and rotation around the z-axis
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