This letter introduces a novel approach for controlling aerial robots during physical interaction by integrating Admittance Control with Nonlinear Model Predictive Control (NMPC). Unlike existing methods, our technique incorporates the desired impedance dynamics directly into the NMPC prediction model, alongside the robot's dynamics. This allows for the explicit prediction of how the robot's impedance will respond to interaction forces within the prediction horizon. Consequently, our controller effectively tracks the desired impedance behavior during physical interaction while seamlessly transitioning to trajectory tracking in free motion, all while consistently respecting actuator constraints. The efficacy of this method is validated through real-time simulations and experiments involving physical interaction tasks with an aerial robot. Our findings demonstrate that, across most scenarios, our method significantly outperforms the state-of-the-art (which does not predict future impedance state), achieving a reduction in tracking error of up to 90%. Furthermore, the results indicate that our approach enables smoother and safer physical interaction, characterized by reduced oscillations and the absence of the unstable behavior observed with the state-of-the-art method in certain situations.

Predictive Admittance Control for Aerial Physical Interaction / Alharbat, A.; Gabellieri, C.; Mersha, A. Y.; Franchi, A.. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 10:11(2025), pp. 11235-11242. [10.1109/LRA.2025.3608653]

Predictive Admittance Control for Aerial Physical Interaction

Franchi A.
Ultimo
2025

Abstract

This letter introduces a novel approach for controlling aerial robots during physical interaction by integrating Admittance Control with Nonlinear Model Predictive Control (NMPC). Unlike existing methods, our technique incorporates the desired impedance dynamics directly into the NMPC prediction model, alongside the robot's dynamics. This allows for the explicit prediction of how the robot's impedance will respond to interaction forces within the prediction horizon. Consequently, our controller effectively tracks the desired impedance behavior during physical interaction while seamlessly transitioning to trajectory tracking in free motion, all while consistently respecting actuator constraints. The efficacy of this method is validated through real-time simulations and experiments involving physical interaction tasks with an aerial robot. Our findings demonstrate that, across most scenarios, our method significantly outperforms the state-of-the-art (which does not predict future impedance state), achieving a reduction in tracking error of up to 90%. Furthermore, the results indicate that our approach enables smoother and safer physical interaction, characterized by reduced oscillations and the absence of the unstable behavior observed with the state-of-the-art method in certain situations.
2025
aerial physical interaction; Aerial systems: mechanics and control; compliance and impedance control; optimization and optimal control; physical interaction control
01 Pubblicazione su rivista::01a Articolo in rivista
Predictive Admittance Control for Aerial Physical Interaction / Alharbat, A.; Gabellieri, C.; Mersha, A. Y.; Franchi, A.. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 10:11(2025), pp. 11235-11242. [10.1109/LRA.2025.3608653]
File allegati a questo prodotto
File Dimensione Formato  
Alharbat_Predictive-Admittance_2025.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 3.21 MB
Formato Adobe PDF
3.21 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1748866
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact