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Learning-based force servoing control of a robot with vision in an unknown environment

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1 Author(s)
Xiao Nanfeng ; School of Computer Science and Engineering, South China University of Technology, Guangzhou 510641, P. R. China

A learning-based control approach is presented for force servoing of a robot with vision in an unknown environment. Firstly, mapping relationships between image features of the servoing object and the joint angles of the robot are derived and learned by a neural network. Secondly, a learning controller based on the neural network is designed for the robot to trace the object. Thirdly, a discrete time impedance control law is obtained for the force servoing of the robot, the on-line learning algorithms for three neural networks are developed to adjust the impedance parameters of the robot in the unknown environment. Lastly, wiping experiments are carried out by using a 6 DOF industrial robot with a CCD camera and a force/torque sensor in its end effector, and the experimental results confirm the effecti veness of the approach.

Published in:

Journal of Systems Engineering and Electronics  (Volume:15 ,  Issue: 2 )