基于约束图像的机械臂视觉伺服在线模型预测控制

A. Hajiloo, Mohammad Keshmiri, W. Xie
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引用次数: 0

摘要

提出了一种基于鲁棒模型预测控制(RMPC)方法的六自由度机器人在线图像视觉伺服控制器。该控制器的设计考虑了机器人视觉伺服系统的输入和输出约束,如机器人的物理限制和可见性约束。所提出的IBVS控制器避免了图像雅可比矩阵的逆,从而解决了经典IBVS控制器难以解决的问题,如相机的初始位置与期望位置之间的大位移。为了验证该算法的有效性,给出了一种眼-手六自由度机械臂的实时实验结果
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On-Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator
This paper presents an on–line image based visual servoing (IBVS) controller for a 6 DOF robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing system’s input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real–time experimental results on a 6 Degrees–of–Freedom (DOF) robot manipulator with eye–in–hand configuration are presented
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