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Adaptive image-based visual servoing of wheeled mobile robots with fixed camera configuration

机译:具有固定摄像头配置的轮式移动机器人的基于图像的自适应视觉伺服

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In this paper, we will study the uncalibrated vision-based positioning problem of wheeled mobile robots by using a ceiling-mounted camera. A new image-based visual servoing scheme will be proposed, which can cope with the unknown intrinsic and extrinsic parameters of the camera and the uncertain distance parameter of the feature point from geometric center of the mobile robot. The presented approach is developed via extending the depth-independent interaction matrix framework for robot manipulators to mobile robots such that the nonlinear dependence on unknown parameters can be removed from the image-Jacobian matrix and then, we can linearly parameterize uncertain parameters in the closed-loop system. In this way, an estimation scheme for the online updating of uncertain parameters can be developed very efficiently. To show that image errors can be guaranteed to be asymptotically convergent, stability analysis will be carried out by using Lyapunov theory. To validate the performance of the presented approach, simulation and experimental results will also be provided.
机译:在本文中,我们将使用吊装式摄像机研究轮式移动机器人的未经校准的基于视觉的定位问题。将提出一种新的基于图像的视觉伺服方案,该方案可以应对未知的相机内在和外在参数以及特征点到移动机器人几何中心的不确定距离参数。通过将机器人操纵器的深度无关交互矩阵框架扩展到移动机器人,从而可以从图像-Jacobian矩阵中消除对未知参数的非线性依赖性,然后我们可以在闭环中对不确定参数进行线性参数化,从而开发出了该方法循环系统。这样,可以非常有效地开发用于不确定参数的在线更新的估计方案。为了证明可以保证图像误差渐近收敛,将使用Lyapunov理论进行稳定性分析。为了验证所提出方法的性能,还将提供仿真和实验结果。

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