Robotic Adaptive Impedance Control Based On Visual Guidance

摘要

Abstract Uncalibrated visual servoing based on SVR-Jacobian estimator is proposed in unknown environment. Multiple support vector regression (SVR) machines are used to estimate the Jacobian matrix of images, and the nonlinear mapping between the image features of the curved line and the robot joint angle is constructed, uncalibrated robot impedance control can be carried out. Image Jacobian matrix expression with Gaussian kernel is put forward, the effectiveness of the presented approach is verified by using a 6 DOF robot with a CCD camera and a force/torque sensor installed in its end effector