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首页> 外文期刊>International Journal of Adaptive Control and Signal Processing >Passivity-based adaptive 3D visual servoing without depth and image velocity measurements for uncertain robot manipulators
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Passivity-based adaptive 3D visual servoing without depth and image velocity measurements for uncertain robot manipulators

机译:基于不确定度的基于被动性的自适应3D视觉伺服,无需深度和像速测量

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摘要

In this work, we consider the 3D visual tracking problem for a robot manipulator with uncertainties in the kinematic and dynamic models. The visual feedback is provided by a fixed and uncalibrated camera located above the robot workspace. The Cartesian motion of the robot end effector can be separated into a 1D motion parallel to the optical axis of the camera and a 2D motion constrained on a plane orthogonal to this axis. Thus, the control design can be simplified, and the overall visual servoing system can be partitioned in two almost-independent subsystems. Adaptive visual servoing schemes, based on a kinematic approach, are developed for image-based look-and-move systems allowing for both depth and planar tracking of a reference trajectory, without using image velocity and depth measurements. In order to include the uncertain robot kinematics and dynamics in the presented solution, we develop a cascade control strategy based on an indirect/direct adaptive method. The stability and convergence properties are analyzed in terms of Lyapunov-like functions and the passivity-based formalism. Numerical simulations including hardware-in-the-loop results, obtained with a robot manipulator and a web camera, are presented to illustrate the performance and feasibility of the proposed control scheme. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:在这项工作中,我们考虑了在运动学和动力学模型中具有不确定性的机器人操纵器的3D视觉跟踪问题。视觉反馈由位于机器人工作区上方的固定且未经校准的摄像机提供。机器人末端执行器的笛卡尔运动可以分为与摄像机光轴平行的一维运动和与该轴正交的平面上的二维运动。因此,可以简化控制设计,并且可以将整个视觉伺服系统划分为两个几乎独立的子系统。基于运动学方法的自适应视觉伺服方案是为基于图像的外观和运动系统开发的,该系统允许在不使用图像速度和深度测量的情况下对参考轨迹进行深度和平面跟踪。为了在提出的解决方案中包括不确定的机器人运动学和动力学,我们开发了一种基于间接/直接自适应方法的级联控制策略。根据类Lyapunov函数和基于被动性的形式主义来分析稳定性和收敛性。提出了使用机器人操纵器和网络摄像头进行的包括半闭环硬件结果的数值仿真,以说明所提出的控制方案的性能和可行性。版权所有(C)2016 John Wiley&Sons,Ltd.

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