| Learning-based force servoing control of a robot with vision in an unknown environment |
| |
| 引用本文： | 肖南峰. Learning-based force servoing control of a robot with vision in an unknown environment[J]. 系统工程与电子技术(英文版), 2004, 15(2) |
| |
| 作者姓名： | 肖南峰 |
| |
| 作者单位： | Xiao Nanfeng School of Computer Science and Engineering，South China University of Technology，Guangzhou 510641，P. R. China |
| |
| 基金项目： | This project was supported by the research foundation of China Education Ministry for the scholars from abroad (2002247). |
| |
| 摘 要： | 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.
|
Learning-based force servoing control of a robot with vision in an unknown environment |
| |
| Xiao Nanfeng School of Computer Science and Engineering,South China University of Technology,Guangzhou ,P. R. China. Learning-based force servoing control of a robot with vision in an unknown environment[J]. Journal of Systems Engineering and Electronics, 2004, 15(2) |
| |
| Authors: | Xiao Nanfeng School of Computer Science Engineering South China University of Technology Guangzhou P. R. China |
| |
| Affiliation: | School of Computer Science and Engineering, South China University of Technology, Guangzhou 510641, P. R. China |
| |
| Abstract: | 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. |
| |
| Keywords: | robotics force servoing vision control learning algorithm neural network. |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
