Research On Visual Auto-control Biological Microoperation System

In bioscience research and experiments, the microoperation robot make the microoperation simplify, automatic, improve operation efficiency and success rate. Robot visual servoing is the fusion of results from many elemental areas including real-time image processing,robot kinematics,controlling theory,computer technology and real-time computation, and is a main subject in the research field of robot visual servoing system. Image processing and calibration are the key parts of a robot visual servo system.One major classification of robot visual servoing system distinguishes position-based control from image-based control according to whether the error signal is defined in 3D coordinates or directly in terms of image features. In position-based control, features are extracted from image and used in conjunction with a known geometrical model of the target and camera model to estimate the pose of the target with respect to the camera. The primary disadvantage of position-based control is that it is often highly calibration dependent. The impact of calibration dependency often depends on the situation. In image-based servoing, control values are computed on the basis of image features directly. The image-based approach may reduce computational delay, eliminate the necessity for image interpretation and eliminate errors due to sensor modeling and camera calibration.In this thesis, an image-based digital cell microoperation robot system is studied. This system bypass 3D space reconstructiona and directly make use of image properties to control robotic motion, and especially avoided the diffculty of visual reconstruction that is brought about by the nonlinear imaging process and image matching in the position-based visual servoing control method. The system architecture and the basic function of digital cell microinjection robot system is analyzed, and the functional control system module and implementation is defined. An improved laser trigonometry measurement method combined with an error matrix used for increasing system precision is emploied to calibrate digital cell microoperatin system, and an image acquisition module is developed by the customization of Matrox acquisition board's function library in VC++6.0 environment. The image acquisition module can access from image acquisition equipment the video streaming that could be used to control microtool's precision movement, on the basis of which the images captured could be studied for the purpose of image processing. Therefore, the implementation of cell injecting can be carried out.