Active Modeling and Compensation Control of Yoshimura Manipulator Using Koopman Operator

Abstract

The integration of origami structures into soft robotics has enriched the adaptability and functionality of the soft robots. Our research group has developed a cable-driven origami robot attached to an arc frame, which enables its deployment in an MR bore and manipulation of medical tools. However, the control of such origami robots still faces challenges such as nonlinear dynamics, unstructured environment, and external payload. This paper introduces an active modeling compensation control method using Koopman operator (K-AMCC) for the Yoshimura origami manipulator, enabling its accurate trajectory tracking with payloads under different orientations. This active modeling method exploits Koopman operator theory and Kalman filter to estimate the model error and synergies the linear quadratic regulator to compensate the modeling errors. The rectangular and circular trajectory tracking experiments under varying payloads and orientations were carried out. The results demonstrate the K-AMCC method’s ability to improve trajectory accuracy significantly, which lays a solid foundation for further medical applications such as needle manipulation and laser ablation in an MR environment.