| Summary: | 碩士 === 淡江大學 === 電機工程學系碩士班 === 99 === A stereo vision system with two cameras is implemented in this thesis. Based on the stereo vision system, a distance measurement of a target object is investigated and applied to the Sprint event of FIRA HuroCup. In the distance measurement of the target object, these topics of the camera calibration, specific target selection, feature point extraction, feature point matching, and distance measurement are discussed. A neural network is used to obtain more correct measurement data. The depth capture of stereo vision and the location judgment of feature points are used to let the robot can autonomously determine its current location. Furthermore, the strategy for the Spring event of FIRA HuroCup is completed. Some experimental results and comparison are presented to illustrate the implemented method can indeed obtain more accurate distance information.
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