Closed loop control of a braided-structure continuum manipulator with hybrid actuation based on learning models

Design of continuum manipulators have always been restricted to simplified structures due to the modeling complexity involved. However with the success of machine learning based models, there are potentially more structures and actuation strategies that could be investigated. This paper presents a novel continuum manipulator with variable diameter and a general control strategy for closed loop task space control. The controller constitutes of an inverse kinematics based feedback component, a forward kinematics based feedforward component and a low level velocity controller. Our findings indicate how such an approach can deal with singularities and provide smooth and accurate motion.