| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 94 === In this paper, using epipolar constraint and relaxed correlation we propose an improved algorithm of two images corresponding. Two images are captured from two cameras, which are put on an outdoor Autonomous Land Vehicle (ALV). Since environment of outdoor is complex, and light is not easy to control it is difficult and time-consuming to get correct corresponding points. In order to surmount this problem, we improve the corresponding algorithm with feature points. Then we use binocular stereovision system and artificial intelligence (AI) with fuzzy control policy to navigate the ALV at the road of outdoor. Before the navigation, the camera calibration is necessary. We consider the lens distortion and using eight known 3D points and image points projected from real world into cameras to obtain calibration parameters of the left and the right cameras. Then we can reconstruct the 3D information from the image points of two cameras by using the calibrated parameters.
In the stereo corresponding, first we should find out the feature point from the left and right images buffers. And then, a feature point in left image, we can draw the epipolar line in right image. The right feature points which adjacent to the epipolar line are most be the corresponding point with left feature point, that reduce searching time and computing time. Second, perform the correlation with the intensity of the neighboring pixels. Third, compare with the relaxed correlation result, and find out the optimal corresponding point candidates. After stereo corresponding and camera calibration, we can get the 3D information to exact the desired road region by road expanded algorithm.
After road searching, the direction of navigation is obtained by an digital compass. We employ an AI-based navigation with fuzzy control method to obtain the angle where ALV has to turn and make ALV avoid the obstacle safely and run toward the sub-goal or the goal in an appropriate path. The ALV system has been performed in the outdoor to demonstrate the effectiveness of the presented method.
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