A Newton method with always feasible iterates for Nonlinear Model Predictive Control of walking in a multi-contact situation

Abstract : In this paper, we present a Nonlinear Model Predictive Control scheme, which is able to generate walking motions in multi-contact situations. Walking up and down stairs with an additional hand support is a typical example, which we address in simulation. Computing such a nonlinear control scheme is usually done with a Newton method, a potentially time-consuming procedure involving iterative linearizations. We propose here a Newton method which is specifically designed to provide at each iteration a feasible solution, always satisfying the (nonlinear) dynamic balance constraints. This results in a significant reduction in computation time, by minimizing the number of necessary iterations to reach a feasible solution.
Type de document :
Communication dans un congrès
IEEE-RAS 2016 - International Conference on Humanoid Robots (Humanoids), Nov 2016, Cancun, Mexico. IEEE, pp.932-937, <10.1109/HUMANOIDS.2016.7803384>
Liste complète des métadonnées


https://hal.inria.fr/hal-01418402
Contributeur : Alexander Sherikov <>
Soumis le : vendredi 16 décembre 2016 - 16:44:31
Dernière modification le : vendredi 3 février 2017 - 11:11:57
Document(s) archivé(s) le : lundi 20 mars 2017 - 17:30:42

Fichier

humanoids16_2.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Diana Serra, Camille Brasseur, Alexander Sherikov, Dimitar Dimitrov, Pierre-Brice Wieber. A Newton method with always feasible iterates for Nonlinear Model Predictive Control of walking in a multi-contact situation. IEEE-RAS 2016 - International Conference on Humanoid Robots (Humanoids), Nov 2016, Cancun, Mexico. IEEE, pp.932-937, <10.1109/HUMANOIDS.2016.7803384>. <hal-01418402>

Partager

Métriques

Consultations de
la notice

602

Téléchargements du document

83