| Summary: | 碩士 === 國立交通大學 === 電機與控制工程系所 === 97 === This thesis proposes an image-based visual servo system, which can estimate and update Image Jacobian Matrix to control a robot arm without camera calibration. There are two parts in the visual servo system. The first one is image feature extraction. We apply the Mean-Shift algorithm in order to improve the performance of feature tracking. Mean-Shift algorithm, which takes the color distribution as a model, is based on the similarity measure function to decide a tracking candidate. This algorithm works well in a real-time and complicated environment. The second part is the control of a manipulator to track visual objects. An easy-to-implement algorithm is proposed to find the relationship between the camera and the manipulator. It can be carried out easily as compared with other methods.
We use the camera and the manipulator emulator to simulate the system effectively. In the implementation, we use only one computer to develop all the software, including the communication to the manipulator and the processing of two cameras' images to solve the local and the global Image Jacobian matrices. Ball-hitting experiments such as the juggling task are presented to analyze the real-time performance of the proposed algorithms.
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