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Obstacle detection system based on colour segmentation using monocular vision for an unmanned ground vehicle

机译:基于彩色分割的障碍物检测系统对无人视力的彩色分割

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摘要

An obstacle detection algorithm is introduced for aiding the navigation of unmanned ground vehicles (UGV). Coloured obstacles are placed randomly in an indoor environment. The coloured obstacles are detected, analysed and processed using a proposed monocular vision algorithm. A camera calibration is conducted to determine the relative position and orientation of the UGV with respect to the obstacles based on intrinsic and extrinsic matrices to form a perspective projection matrix. The field geometry is used to obtain a mapped environment in the world coordinates. Our obstacle detection algorithm is proposed to identify the existence of the obstacles in the field. Using bounding boxes around the detected obstacle allows the determination of the obstacles locations in a pixel coordinate frame. Thus, the depth perception is determined by using the pixel coordinates and the camera projection matrix. Real-time experiments are carried out to demonstrate the validity and efficiency of the proposed algorithm.
机译:障碍物检测算法被引入用于辅助无人地面车辆(UGV)的导航。彩色的障碍是在室内环境中随意摆放。有色障碍物检测,分析和使用提出了单目视觉算法进行处理。照相机校准以确定相对于基于内在因素和外在矩阵以形成立体投影矩阵障碍物的UGV的相对位置和定向。场几何特征来获得在世界坐标映射的环境。我们的障碍物检测算法,以确定在该领域的障碍存在。使用围绕检测到的障碍物包围盒允许在像素中的障碍物的位置的确定的坐标系。因此,深度知觉是通过使用像素坐标和摄像机投影矩阵确定。实时进行了实验验证了该算法的有效性和效率。

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