Research on Optimized Control of Six - DOF Manipulator with Uncalibrated Visual Servo.

This paper realizes the uncalibrated visual servoless control of the Six-DOF manipulator, where the intrinsic and extrinsic parameters of the camera and the robot manipulator model are not known, nor real-time computes the inverse of image Jacobian. And the neural network was used to optimize the trajectory of manipulator end in Cartesian space. Firstly, a biaxial parallel layoutt are proposed to establish the relationship between the moving component along the coordinate axis and the change of single image feature when the end of the robot moves in the Cartesian space. The neural network was used to fit the relationship established above, then the optimization model was established, and the parameter of PID controller were optimized by neural network. Finally, the simulation and comparison experiments are investigated, and the results indicate the controller posed in this paper is effective and stable. [ABSTRACT FROM AUTHOR]