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Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

机译：基于快速单应性分解的移动机器人自适应混合视觉伺服调节

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摘要

For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when objects imaging depth and cameras position extrinsic parameters are unknown. Firstly, the homographys particular properties caused by mobile robots 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view's single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and cameras position extrinsic parameters.
机译：对于基于单眼相机的移动机器人系统，提出了一种基于快速单应性分解方法的自适应混合视觉伺服调节算法，即使在物体成像深度和相机位置具有外部参数的情况下，也能将移动机器人驱动至所需的位置和方向。未知。首先，考虑了由移动机器人的2自由度运动引起的单应性的特殊属性，以诱导一种快速的单应性分解方法。其次，将单应性矩阵和提取的方向误差与所需视图的单个特征点结合在一起，以形成误差向量及其开环误差函数。最后，利用基于Lyapunov的技术来构建自适应调节控制律，然后进行实验验证。实验结果表明，所提出的快速单应分解方法不仅简单高效，而且具有很高的精确度。同时，尽管缺乏深度信息和摄像机位置外部参数，但设计的控制律仍可以很好地实现移动机器人的位置和方向调节。

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  • 来源
    《Journal of control science and engineering》 |2015年第2015期|739894.1-739894.10|共10页
  • 作者

    Chunfu Wu; Guodong Li; Qingshun Tang; Fengyu Zhou;

  • 作者单位

    School of Mechanical and Electrical Engineering, Longyan University, Longyan, Fujian 364012, China;

    School of Mechanical and Electrical Engineering, Longyan University, Longyan, Fujian 364012, China;

    School of Mechanical and Electrical Engineering, Longyan University, Longyan, Fujian 364012, China;

    School of Control Science and Engineering, Shandong University, Jinan, Shandong 250061, China;

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