Open-loop position control in collaborative, modular Variable-Stiffness-Link (VSL) robots. - Gandarias Palacios, Juan Manuel; Wang, Yongjing; Stilli, Agostino; García-Cerezo, Alfonso José; Gómez-de-Gabriel, Jesús Manuel; Wurdemann, Helge (IEEE, 2020)
Collaborative robots open up new avenues in the field of industrial robotics and physical Human-Robot Interaction (pHRI) as they are suitable to work in close approximation with humans. The integration and control of variable stiffness elements allow inherently safe interaction: Apart from notable work on Variable Stiffness Actuators, the concept of Variable-Stiffness-Link (VSL) manipulators promises safety improvements in cases of unintentional physical collision. However, position control of these type of robotic manipulators is challenging for critical task-oriented motions. In this letter, we propose a hybrid, learning based kinematic modelling approach to improve the performance of traditional open-loop position controllers for a modular, collaborative VSL robot. We show that our approach improves the performance of traditional open-loop position controllers for robots with VSL and compensates for position errors, in particular, for lower stiffness values inside the links: Using our upgraded and modular robot, two experiments have been carried out to evaluate the behaviour of the robot during task-oriented motions. Results show that traditional model-based kinematics are not able to accurately control the position of the end-effector: the position error increases with higher loads and lower pressures inside the VSLs. On the other hand, we demonstrate that, using our approach, the VSL robot can outperform the position control compared to a robotic manipulator with 3D printed rigid links.
Keywords: Aprendizaje automático (Inteligencia artificial); Robótica; Cinemática; Kinematics; Manipulators; Modeling, control, and learning for soft robots; Deep learning