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In order to detect navigation line for agricultural vehicles in natural vegetation-embraced environment, a method was presented based on robotic vision. Firstly, an improved region growing algorithm was introduced to segment path. Then the two edges of path were extracted and an array of points through the center was computed. Lastly, the guidance line for vehicles to follow was obtained by Hough...
Lane detection is one of fundamental but critical problems for lane following system of intelligent vehicles. However, a robust and cost effective approach is still a deserve exploit issue. A novel and effective approach using a five steps scheme is presents. First, Canny detector is used to obtain edge map from the road image acquired from monocular camera mount on vehicle; Second, a matching process...
Visual information processing is one of the key technologies for robot visual navigation, whose speed directly determines the quality of the visual navigation. Taking advantage of the parallel image processing capability of cellular neural networks (CNN), we propose a fast algorithm using CNN for mobile visual information processing. In the algorithm, convex restoration, gray threshold, dilation and...
In this article we present a novel navigation approach for an autonomous robot in an unknown maze based on calibration-free visual information. On one hand, we segment images to obtain the approximate traversable region and on the other hand the lines and corners in images are also extracted to help a robot understanding the topological structure. In the experiment, our navigation approach running...
Self-localization is key to mobile robot navigation. Among many techniques for self-localization, landmark-based approaches can avoid complex and often memory demanding descriptions of robot surroundings. In this paper, doorplate is selected as visual landmark. For color images captured by robot, adaptive thresholding segmentation based on component color histograms and rival penalized competitive...
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