| Machine vision is an active and challenging research field, its research areaand applications area spread widely. Moving objects tracking is an activeproblem in machine vision and has a wide variety of applications. In this paper,the problem on moving objects searching based color information and trajectorytracking based on machine vision is primary, the calibrating method and the wayof tracking the moving objects are introduced in detail. Further more, anadaptive visual servo controller is developed.In stereovision, the primary problem to solve is the relations between the3D points and the 2D image points. So the camera calibrating is the premise andthe basic problem to practice the machine vision. At the third part of thedissertation, the preliminary vision system is built up, which is based on linearcamera calibration.In many fields, tracking the moving objects quickly and accuracy isimportant. According to the analysis of moving scene, introduce how to choosethe color space, how to process the image, and how to segment a set of movingcolor image. Then make the soccer robot vision system as an example, a newobject tracing method, named dynamic window trace, is designed andimplemented in our soccer robot vision system. Experiment results clearly showthat this method is efficient enough to meet the time criteria. At the end of thispaper, the vision program for soccer robot is designed and achieved throughcomprehensive consideration and analyze.The controller is formulated using a hybrid composition of image-spacepixel information and reconstructed Euclidean information that is obtained viaprojective homography relationships between the actual images, a referenceimage, and the desired image. To achieve the objective, a Lyapunov-basedadaptive control strategy is employed to actively compensate for the lack ofunknown depth measurements and unknown object model parameters.Simulation results were provided to demonstrate the performance of thecontroller for the fixed camera problem. |
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