Adaptive neural controller for visual servoing of robot manipulators with camera-in-hand configuration

作者：Kim Jungmin; Kumar Naveen^*; Panwar Vikas; Borm Jin Hwan; Choi Jangbom

来源：Journal of Mechanical Science and Technology, 2012, 26(8): 2313-2323.

DOI：10.1007/s12206-012-0610-5

• Feedforward neural network
• Kinematic control
• Lyapunov stability
• Visual servoing

In this paper, an adaptive neural controller is proposed for visual servoing of robot manipulators with camera-in-hand configuration. The controller is designed as a combination of a PI kinematic controller and feedforward neural network controller that computes the required torque signals to achieve the tracking. The visual information is provided using the camera mounted on the end-effector and the defined error between the actual image and desired image positions is fed to the PI controller that computes the joint velocity inputs needed to drive errors in the image plane to zero. Then the feedforward neural network controller is designed such that the robot%26apos;s joint velocities converges to the given velocity inputs. The stability of combined PI kinematic and feedforward neural network computed torque is proved by Lyapunov theory. It is shown that the neural network can cope with the unknown nonlinearities through the adaptive learning process and requires no preliminary off teaming. Simulation results are carried out for a three degrees of freedom microbot robot manipulator to evaluate the controller performance.

• 出版日期2012-8