— Collaborative robots (cobots) open up new avenues
in the fields of industrial robotics and physical Human-Robot
Interaction (pHRI) as they are suitable to work in close approximation and in collaboration 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 collisions. However, position control of these type of
robotic manipulators is challenging for critical task-oriented
motions (e.g., pick and place). Hence, the study of open-loop
position control for VSL robots is crucial to achieve high
levels of safety, accuracy and hardware cost-efficiency in pHRI
applications. In this paper, 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 taskoriented 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
