Closed Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control

Variable Stiffness Actuation (VSA) has become one of the focal points in robotics research recently. Due to the intrinsic nonlinearity of robot dynamics and the requirement to fulfill constraints imposed on input and state variables, control of VSA systems is a nontrivial task. In this work we present a closed-loop control framework for VSA robots leveraging recent increases in computational resources and advances in optimization algorithms. We genererate reference trajectories using open-loop optimal control and subsequently track trajectories via nonlinear model predictive control in a closed-loop manner. The video demonstrated a real-world experiments which were conducted using a two-link planar manipulator for a ball throwing task.

For more information, please see:
A. Zhakatayev, M. Rubagotti, H.A. Varol, “Closed-Loop Control of Variable Stiffness Actuated Robots via Nonlinear Model Predictive Control”, IEEE Access, vol. 3, pp. 235-248, 2015