Vision Guiding Controller Design for Articulated Manipulator Based on Barrier Lyapunov Function

This work proposed a vision-guided articulated manipulator controller design using the Barrier Lyapunov function. In a closed-loop system, vision guiding uses camera feedback to control the motion of an articulated manipulator. For vision guidance to operate the articulated manipulator, an object must be in the camera's field of view. Image-based and position-based visual servoing are used to improve the vision-guiding controller. Using this method, an offline trajectory is produced to perform position- and image-based visual servoing operations on the articulated manipulator. Two different control strategies are presented: the vision guiding controller with the limit orientation using the Barrier Lyapunov function and the vision guiding controller with a quadratic Lyapunov function. Simulation results from two vision-guiding controllers, as well as proof of asymptotic stability, are used to validate the efficacy of the proposed controller.