| Summary: | 碩士 === 國立交通大學 === 電機與控制工程系所 === 94 === To achieve the robot registration and localization using computer vision, artificial landmarks or specific shapes or specific colors in the image are usually used. However, there exist many robust algorithms in pattern recognition and image segmentation which do not require constraints on input data to achieve a good recognition performance. In other words, localization can be performed based on a general scene. In this thesis, we adopt Spatial Gaussian Mixture Model (GMM) in image segmentation to describe an image viewed by the robot in spatial domain without any artificial landmark. Secondly, we use a modified combination algorithm by Cyr and Kimia to combine similar data. It is found out that a monotonic relationship exists among the scene registered and its neighborhood in terms of distance. This phenomenon can be used to assist to localize the robot and this work demonstrate the feasibility by several experiments.
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