Adaptive Visual Servoing Shape Control of a Soft Robot Manipulator Using Bézier Curve Features
Fan Xu, Yuyou Zhang, Jing Sun, Hesheng Wang
Abstract
Soft continuum robot outperforms its rigid counterpart when executing in complicated environments thanks to its high dexterity of the redundant configuration. Shape control is regarded as a prerequisite to applications in unstructured environments. In this article, we develop an adaptive image-based visual servoing (IBVS) algorithm using an uncalibrated camera to realize visual shape control of the cable-driven soft manipulator. A Bézier curve is selected to be the feature providing shape information of the soft robot. An adaptive law is proposed to simultaneously solve the uncalibrated problem and to analytically model the motion of curve control points. The control algorithm is then designed with third-order Bézier curve being the image features, and theoretically proves its stability. The algorithm has been experimentally validated in the cable-driven soft continuum robot. The experiment results demonstrate rapid converging performance to C-type and S-type reference shapes.