We present a Model Predictive Control (MPC) algorithm for 3D walking and running in humanoids. The scheme makes use of the Variable Height Inverted Pendulum (VH-IP) as prediction model, and generates a Center of Mass (CoM) trajectory and footstep positions online. The MPC works with the nonlinear dynamics by decomposing the problem into a vertical and a horizontal component. The vertical is solved first making the horizontal dynamics linear time-varying and therefore solvable in real-time. A stability constraint is incorporated to ensure internal stability. The algorithm is validated with dynamic simulations in DART.
MPC-based gait generation for humanoids: From walking to running / Smaldone, Filippo M.; Scianca, Nicola; Lanari, Leonardo; Oriolo, Giuseppe. - (2021), pp. 129-130. (Intervento presentato al convegno 2021 I-RIM Conference tenutosi a Roma) [10.5281/zenodo.5900605].
MPC-based gait generation for humanoids: From walking to running
Filippo M. Smaldone
;Nicola Scianca;Leonardo Lanari;Giuseppe Oriolo
2021
Abstract
We present a Model Predictive Control (MPC) algorithm for 3D walking and running in humanoids. The scheme makes use of the Variable Height Inverted Pendulum (VH-IP) as prediction model, and generates a Center of Mass (CoM) trajectory and footstep positions online. The MPC works with the nonlinear dynamics by decomposing the problem into a vertical and a horizontal component. The vertical is solved first making the horizontal dynamics linear time-varying and therefore solvable in real-time. A stability constraint is incorporated to ensure internal stability. The algorithm is validated with dynamic simulations in DART.| File | Dimensione | Formato | |
|---|---|---|---|
|
Smaldone_MPC-Based_2021.pdf
accesso aperto
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Creative commons
Dimensione
434.79 kB
Formato
Adobe PDF
|
434.79 kB | Adobe PDF |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
