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Robot Navigation Control Based on Monocular Images: An Image Processing Algorithm for Obstacle Avoidance Decisions

机译:基于单眼图像的机器人导航控制:避障决策的图像处理算法

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This paper covers the use of monocular vision to control autonomous navigation for a robot in a dynamically changing environment. The solution focused on using colour segmentation against a selected floor plane to distinctly separate obstacles from traversable space: this is then supplemented with canny edge detection to separate similarly coloured boundaries to the floor plane. The resulting binary map (where white identifies an obstacle-free area and black identifies an obstacle) could then be processed by fuzzy logic or neural networks to control the robot's next movements. Findings show that the algorithm performed strongly on solid coloured carpets, wooden, and concrete floors but had difficulty in separating colours in multicoloured floor types such as patterned carpets.
机译:本文介绍了在动态变化的环境中使用单眼视觉控制机器人的自主导航。该解决方案着重于对选定的地板平面使用颜色分割,以将障碍物与可穿越的空间区分开来:然后,对它进行精巧的边缘检测,以将相似颜色的边界与地板平面分离。然后,可以通过模糊逻辑或神经网络对生成的二进制映射图(白色表示无障碍区域,黑色表示障碍物)进行处理,以控制机器人的下一个动作。研究结果表明,该算法在纯色地毯,木质地板和混凝土地板上表现出色,但是在分离彩色地板类型(例如图案化地毯)时很难区分颜色。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第10期|240476.1-240476.14|共14页
  • 作者

    William Benn; Stanislao Lauria;

  • 作者单位

    Department of Information Systems and Computing, Brunel University, Uxbridge UB8 3PH, UK;

    Department of Information Systems and Computing, Brunel University, Uxbridge UB8 3PH, UK;

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  • 正文语种 eng
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