Progressive automation is a method that allows the operator to demonstrate a task a few times until the robot gradually learns to execute it autonomously. In this paper we combine a novel structure of Dynamic Movement Primitives with variable stiffness control, to allow synchronization with the demonstrated motion during the operator's intervention. This structure enables the DMP to speed up or slow down depending on the human demonstration. In addition, we present a variable stiffness controller to change the role of the robot between follower and leader based on the tracking error of the robot from the proposed DMP and on the guidance forces. The proposed variable stiffness controller is proved to be passive using energy tanks. The effectiveness of the proposed method is demonstrated experimentally.

In this article, a passive physical human–robot interaction (pHRI) controller is proposed to enhance pHRI performance in terms of precision, cognitive load, and user effort, in cases partial knowledge of the task is available. Partial knowledge refers to a subspace of $SE(3)$ determined by the desired task, generally mixing both position and orientation variables, and is mathematically approximated by parametric expressions. The proposed scheme, which utilizes the notion of virtual constraints and the prescribed performance control methodology, is proved to be passive with respect to the interaction force, while guaranteeing constraint satisfaction in all cases. The control scheme is experimentally validated and compared with a dissipative control scheme utilizing a KUKA LWR4+ robot in a master–slave task; experiments also include an application to a robotic assembly case.

In Robotic-Assisted Minimally Invasive Surgery a long and thin instrument attached to the robotic arm enters the human body through a tiny incision. To ensure that no injury occurs when the surgeon is manipulating the instrument, the incision point must be a remote center of motion (RCM) for the instrument. For this purpose, a novel target admittance model is designed in the joint space for hands-on procedures that can be applied in all commercially available general-purpose manipulators with six or more degrees of freedom. It is proved that the joint reference trajectories generated by the proposed target admittance model under the exertion of a human force are stable and satisfy the RCM constraint. The measurements of the human force and the robot's forward kinematic model are only required. Its use spans all hands-on surgical procedures. The proposed model can be easily extended to achieve additional objectives. Simulation results validate the theoretical findings and experimental results utilizing a KUKA LWR4+ demonstrate that trocar displacements are less than 1mm.