Microscopic Visual Servoing for Microassembly Robot Depth Motion Based on Defocus Image Features

To measure micromanipulator depth motion,a gray variance-based focus measure operator is utilized to compute its defocus image features.The defocus feature curve is theoretically distributed with only one peak,which represents depth position of the microscopic focal plane.The extracted defocus features usually include lots of random noises.A nonlinear tracking differentiator is developed to suppress noises and smoothly track the features and their differential values without oscillation.Based on the differential defocus signals,a coarse-tofine self-optimizing vision controller is presented for the micromanipulator to precisely locate assembly plane along the depth way.Experimental results of microassembly depth motion demonstrate the validity of the proposed approach with a depth servoing error of 7.5 μm.