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Adaptive Control Techniques for Dynamic Visual Repositioning of Hand-Eye Robotic Systems

机译:手眼机器人系统动态视觉重新定位的自适应控制技术

摘要

Using active monocular vision for 3-D visual control tasks is difficult since the translational and the rotational degrees of freedom are strongly coupled. This paper addresses several issues in 3D visual control and presents adaptive control schemes for the the problem of robotic visual servoing (eye-in-hand configuration) around a static rigid target. The objective is to move the image projections of several feature poinb of the static rigid target to some desired image positions The inverse perspective transformation is assumed partially unknown. The adaptive controllers compensate for the servoing errors, the partially unknown camera parameters, and the computational delays which are introduced by the time-consuming vision algorithms. We present a stability analysis along with a study of the conditions that the feature points must satisfy in order for the problem to be solvable. Finally, several experimental results are presented to verify the validity and the efficacy of the proposed algorithms.
机译:由于平移和旋转自由度紧密耦合,因此很难将主动单眼视觉用于3-D视觉控制任务。本文讨论了3D视觉控制中的几个问题,并针对围绕静态刚性目标的机器人视觉伺服(手眼配置)问题提出了自适应控制方案。目的是将静态刚性目标的几个特征点的图像投影移动到某些所需的图像位置。假定部分未知,逆透视变换。自适应控制器补偿了伺服误差,部分未知的相机参数以及耗时的视觉算法带来的计算延迟。我们提出了稳定性分析,并对特征点必须满足才能解决问题的条件进行了研究。最后,提出了几个实验结果,以验证所提出算法的有效性和有效性。

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