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A Novel Obstacle Detection Method Based on Monocular Camera and Laser Radar

机译:一种基于单眼相机和激光雷达的新型障碍物检测方法

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Obstacle detection is an important task in the field of environmental perception for Intelligent Ground Robots. This paper presents a new obstacle detection method which uses visual saliency detection to detect multiple obstacles in the scene. By analyzing the saliency map and the marker-based watershed algorithm, we combine their characteristics creatively to obtain accurate contours of obstacles, and propose a fast method to detect obstacles based on monocular camera and laser radar. The laser radar points representing obstacles are clustered, and projected onto the saliency map as markers of watershed algorithm. The experimental results indicate the effectiveness, robustness and performance of realtime of our method.
机译:障碍物检测是智能地机器人环境感知领域的重要任务。本文介绍了一种新的障碍检测方法,它使用视觉显着性检测来检测场景中的多个障碍物。通过分析显着图和基于标记的流域算法,我们将其具有创造性的特征来获得精确的障碍轮廓,并提出了一种快速检测基于单眼相机和激光雷达的障碍的方法。代表障碍物的激光雷达点被聚集,并投影到显着图作为流域算法的标记。实验结果表明我们方法实时的有效性,鲁棒性和性能。

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