Binocular Vision Based Drivable Region Fast Detection for Indoor Mobile Robot

Qu Shengyue, Meng Cai
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Abstract

A fast method based on binocular vision is proposed for mobile robot to detect drivable regions. First, the image is segmented into regions by searching contours. Second, part obstacle regions are determined by the vanishing line. Then, according to the different distribution of feature points extracted from the regions under the vanishing line, we use two different method to classify regions: various constraints-based region classification is used to classify regions including many feature points and homography-substraction-based region classification is used to classify regions including rare feature points. Finally, combining the two classification methods, we get the result of drivable region detection. The results of indoor and outdoor experiments show that the method can detect drivable regions quickly and robustly.
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基于双目视觉的室内移动机器人可驾驶区域快速检测
提出了一种基于双目视觉的移动机器人可行驶区域快速检测方法。首先,通过搜索等高线对图像进行区域分割;其次,利用消失线确定局部障碍区域;然后,根据消失线下提取的区域特征点分布的不同,采用两种不同的方法对区域进行分类:基于各种约束的区域分类方法对特征点多的区域进行分类,基于同形减法的区域分类方法对特征点少的区域进行分类。最后,结合两种分类方法,得到可驱动区域检测结果。室内和室外实验结果表明,该方法能够快速、鲁棒地检测出可驾驶区域。
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