With the prevailing application of new materials and the higher requirements for the quality and efficiency of production in the equipment manufacturing industry, traditional assembly methods can hardly meet the needs of large-scale production, especially in the field of high-precision assembly. Robot assembly guided by visual perception has become the key of the research in the field of engineering technology. It requires higher accuracy of robot visual perception and the control over force, position and so on. However, in 3C assembly, most products are made of transparent materials such as glass. Because of the transparency and specular reflection of the surface, 3D reconstruction of transparent objects is a very difficult problem in computer vision, in that the traditional visual perception methods could not be accurate enough. The present research proposes a bionic active sensing algorithm for 3D perception and reconstruction and realizes high-precision 3D by applying the registration algorithm. The purpose is to solve the problems existing in the traditional visual perception method, such as difficulties in achieving active sensing, low accuracy of point clouds registration, and complex computation. The results of the experiments show that the present method is efficient and accurate in 3D reconstruction. It reduces the planar reconstruction error to 0.064 mm and the surface reconstruction error to 0.177 mm. (C) 2020 Optical Society of America
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