We introduce a robust gait generation framework for humanoid robots based on our Intrinsically Stable Model Predictive Control (IS-MPC) scheme, which features a stability constraint to guarantee internal stability. With respect to the original version, the new framework adds multiple components addressing the robustness problem from different angles: an observer-based disturbance compensation mechanism; a ZMP constraint restriction that provides robustness with respect to bounded disturbances; and a step timing adaptation module to prevent the loss of feasibility. Simulation and experimental results are presented.

Robust MPC-Based Gait Generation in Humanoids / Smaldone, Filippo M.; Scianca, Nicola; Lanari, Leonardo; Oriolo, Giuseppe. - (2020). (Intervento presentato al convegno I-RIM 2020 (2nd Italian Conference on Robotics and Intelligent Machines) tenutosi a Virtual).

Robust MPC-Based Gait Generation in Humanoids

Filippo M. Smaldone;Nicola Scianca;Leonardo Lanari;Giuseppe Oriolo
2020

Abstract

We introduce a robust gait generation framework for humanoid robots based on our Intrinsically Stable Model Predictive Control (IS-MPC) scheme, which features a stability constraint to guarantee internal stability. With respect to the original version, the new framework adds multiple components addressing the robustness problem from different angles: an observer-based disturbance compensation mechanism; a ZMP constraint restriction that provides robustness with respect to bounded disturbances; and a step timing adaptation module to prevent the loss of feasibility. Simulation and experimental results are presented.
2020
I-RIM 2020 (2nd Italian Conference on Robotics and Intelligent Machines)
Humanoids; gait generation; robust locomotion
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Robust MPC-Based Gait Generation in Humanoids / Smaldone, Filippo M.; Scianca, Nicola; Lanari, Leonardo; Oriolo, Giuseppe. - (2020). (Intervento presentato al convegno I-RIM 2020 (2nd Italian Conference on Robotics and Intelligent Machines) tenutosi a Virtual).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1482486
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