| Summary: | 碩士 === 國立中央大學 === 電機工程研究所 === 98 === The main purpose of this thesis is to use pattern recognition methods to control the autonomous mobile robot and then achieve the purpose of navigation. The thesis installed a video camera in the autonomous mobile robot and used it to search for patterns on the ground. The autonomous mobile robot will go ahead to approach the pattern, identify it and then perform the action for which the pattern represented. When this pattern action completed, the next pattern is sought and the action will continue, so the circle continues to achieve the navigation control of the autonomous mobile robot.
As for the pattern detection, color detection techniques are used to search for patterns and identify the block, and it will separate the image of pattern from the original complex background. As for the capturing pattern section, contour tracing techniques are used to extract the pattern that can be used to determine the features. This technique also filtered out residual noise from the background in the detached way. After the access pattern is used to determine characteristics, two-dimensional linear discrimination analysis of method is employed to obtain the characteristic parameters of pattern. By using the characteristic parameters to recognize the pattern, the results will be identified to control an autonomous mobile robot.
The estimation of the relative distance and the location between autonomous mobile robot and the pattern section, this thesis designs a back-propagation neural network to execute on inverse perspective mapping. Using the back-propagation neural network function approximation can give enough input and output to approximate the camera within the nonlinear images projection function in the situation of not knowing the camera internal parameters of the case. According to the relative distance between the autonomous mobile robot and the pattern, the autonomous mobile robot will evaluate how to move, approach the pattern and correct the action automatically.
The thesis uses the image recognition technology and the back-propagation neural network, to achieve the navigation purposes of intelligently controlling autonomous mobile robot.
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