We present a novel MPC method for humanoid gait generation that is guaranteed to produce stable CoM trajectories. This is obtained by using a dynamic extension of the LIP as motion model, with the ZMP velocity as a control variable, and embedding an explicit stability constraint in the formulation. Such constraint turns out to be linear in the control variables, leading to a standard QP problem with equality and inequality constraints. The intrinsically stable MPC framework is developed into a full-fledged gait generation scheme by including automatic footstep placement. Simulations show that the proposed method is very effective and performs robustly in the presence of changes in the prediction horizon. © 2016 IEEE.
Intrinsically Stable MPC for Humanoid Gait Generation / Scianca, Nicola; Cognetti, Marco; DE SIMONE, Daniele; Lanari, Leonardo; Oriolo, Giuseppe. - STAMPA. - (2016), pp. 601-606. (Intervento presentato al convegno 16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016 tenutosi a Cancun; Mexico nel 15-17 November 2016) [10.1109/HUMANOIDS.2016.7803336].
Intrinsically Stable MPC for Humanoid Gait Generation
SCIANCA, NICOLA
;COGNETTI, MARCO;DE SIMONE, DANIELE;LANARI, Leonardo;ORIOLO, Giuseppe
2016
Abstract
We present a novel MPC method for humanoid gait generation that is guaranteed to produce stable CoM trajectories. This is obtained by using a dynamic extension of the LIP as motion model, with the ZMP velocity as a control variable, and embedding an explicit stability constraint in the formulation. Such constraint turns out to be linear in the control variables, leading to a standard QP problem with equality and inequality constraints. The intrinsically stable MPC framework is developed into a full-fledged gait generation scheme by including automatic footstep placement. Simulations show that the proposed method is very effective and performs robustly in the presence of changes in the prediction horizon. © 2016 IEEE.File | Dimensione | Formato | |
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