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Contact force regulation in physical human-machine interaction based on model predictive control

Published online by Cambridge University Press:  17 August 2023

Daniel Pacheco Quiñones Open the ORCID record for Daniel Pacheco Quiñones [Opens in a new window] ,
Maria Paterna Open the ORCID record for Maria Paterna [Opens in a new window] ,
Carlo De Benedictis Open the ORCID record for Carlo De Benedictis [Opens in a new window] ,
Daniela Maffiodo Open the ORCID record for Daniela Maffiodo [Opens in a new window] ,
Walter Franco Open the ORCID record for Walter Franco [Opens in a new window]  and
Carlo Ferraresi Open the ORCID record for Carlo Ferraresi [Opens in a new window]
Daniel Pacheco Quiñones
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
Maria Paterna
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
Carlo De Benedictis*
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
Daniela Maffiodo
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
Walter Franco
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
Carlo Ferraresi
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
*
Corresponding author: Carlo De Benedictis; Email: carlo.debenedictis@polito.it
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Abstract

With increasing attention to physical human-machine interaction (pHMI), new control methods involving contact force regulation in collaborative and coexistence scenarios have spread in recent years. Thanks to its internal robustness, high dynamic performance, and capabilities to avoid constraint violations, a Model Predictive Control (MPC) action can pose a viable solution to manage the uncertainties involved in those applications. This paper uses an MPC-driven control method that aims to apply a well-defined and tunable force impulse on a human subject. After describing a general control design suitable to achieve this goal, a practical implementation of such a logic, based on an MPC controller, is shown. In particular, the physical interaction considered is the one occurring between the body of a patient and an external perturbation device in a dynamic posturography trial. The device prototype is presented in both its hardware architecture and software design. The MPC-based main control parameters are thus tuned inside hardware-in-the-loop and human-in-the-loop environments to get optimal behaviors. Finally, the device performance is analyzed to assess the MPC algorithm’s accuracy, repeatability, flexibility, and robustness concerning the several uncertainties due to the specific pHMI environment considered.

Keywords

force controlhuman-machine interactionman-machine systemsModel Predictive Controlcontact force

Information

Type
Research Article
Information
Robotica , Volume 41 , Issue 11 , November 2023 , pp. 3409 - 3425
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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