The feasibility region of a Model Predictive Control (MPC) algorithm is the subset of the state space in which the constrained optimization problem to be solved is feasible. In our recent Intrinsically Stable MPC (IS-MPC) method for humanoid gait generation, feasibility means being able to satisfy the dynamic balance condition, the kinematic constraints on footsteps as well as an explicit stability condition. Here, we exploit the feasibility concept to build a step timing adapter that, at each control cycle, modifies the duration of the current step whenever a feasibility loss is imminent due, e.g., to an external perturbation. The proposed approach allows the IS-MPC algorithm to maintain its linearity and adds a negligible computational burden to the overall scheme. Simulations and experimental results where the robot is pushed while walking showcase the performance of the proposed approach.

Feasibility-Driven Step Timing Adaptation for Robust MPC-Based Gait Generation in Humanoids / Smaldone, Filippo Maria; Scianca, Nicola; Lanari, Leonardo; Oriolo, Giuseppe. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 6:2(2021), pp. 1582-1589. [10.1109/LRA.2021.3059627]

Feasibility-Driven Step Timing Adaptation for Robust MPC-Based Gait Generation in Humanoids

Smaldone, Filippo Maria
;
Scianca, Nicola
;
Lanari, Leonardo
;
Oriolo, Giuseppe
2021

Abstract

The feasibility region of a Model Predictive Control (MPC) algorithm is the subset of the state space in which the constrained optimization problem to be solved is feasible. In our recent Intrinsically Stable MPC (IS-MPC) method for humanoid gait generation, feasibility means being able to satisfy the dynamic balance condition, the kinematic constraints on footsteps as well as an explicit stability condition. Here, we exploit the feasibility concept to build a step timing adapter that, at each control cycle, modifies the duration of the current step whenever a feasibility loss is imminent due, e.g., to an external perturbation. The proposed approach allows the IS-MPC algorithm to maintain its linearity and adds a negligible computational burden to the overall scheme. Simulations and experimental results where the robot is pushed while walking showcase the performance of the proposed approach.
2021
Humanoids; Biped Locomotion; Model Predictive Control
01 Pubblicazione su rivista::01a Articolo in rivista
Feasibility-Driven Step Timing Adaptation for Robust MPC-Based Gait Generation in Humanoids / Smaldone, Filippo Maria; Scianca, Nicola; Lanari, Leonardo; Oriolo, Giuseppe. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 6:2(2021), pp. 1582-1589. [10.1109/LRA.2021.3059627]
File allegati a questo prodotto
File Dimensione Formato  
Smaldone_Feasibility-Driven_2021.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.57 MB
Formato Adobe PDF
1.57 MB Adobe PDF   Contatta l'autore
Smaldone_postprint_Feasibility-Driven_2021.pdf

accesso aperto

Note: DOI: 10.1109/LRA.2021.3059627
Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.16 MB
Formato Adobe PDF
1.16 MB Adobe PDF

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/11573/1504222
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact