【摘要】 为实现基于视觉的6-DOF机器人智能焊接过程的自动导引,提出了一种无标定视觉伺服控制模型.该模型采用多个支持向量回归(SVR)机进行图像雅可比矩阵估计,建立了图像特征和机器人关节角的非线性映射关系,能够在无标定条件下进行焊接机器人视觉导引的伺服控制.文中给出了采用高斯核函数的图像雅可比矩阵估算表达式,并在计算机控制下对SVR-雅可比估计器进行自动训练后,分别对EIH"手眼"和ETH"眼看手"两种摄像机配置方式的焊接机器人进行视觉定位导引试验.试验结果表明,采用SVR-雅可比估计器的焊接机器人视觉导引能够较准确地定位在期望目标,与传统的Broyden-估计器相比有更好的动态响应质量.更多还原

【Abstract】 In order to implement the automatic visual guidance of 6-DOF robots in intelligent welding system,a new control model of uncalibrated visual servoing is proposed. In this model,multiple support vector regression( SVR)machines are used to estimate the Jacobian matrix of images,and the nonlinear mapping between the image feature and the robot joint angle is constructed. Thus,an uncalibrated visual servoing of welding robots can be carried out.The authors also put forward an image Jacobian matrix expression with Gaussian kernel and conduct visual guidance experiments of a welding robot with both eye-in-hand and eye-to-hand camera configurations by using the SVR-Jacobian estimator automatically trained under the control of computer. The results indicate that the visual guidance of welding robots using the SVR-Jacobian estimator converges at the desired goal and is superior to the conventional Broyden-estimator because it helps to acquire high dynamic response quality.更多还原