Title :

Condensed semi-implicit dynamics for trajectory optimization in soft robotics

Author(s) :

Ménager, Etienne [Auteur]
Deformable Robots Simulation Team [DEFROST ]
Bilger, Alexandre [Auteur]
Service Expérimentation et Développement [SED [Lille]]
Jallet, Wilson [Auteur]
Équipe Mouvement des Systèmes Anthropomorphes [LAAS-GEPETTO]
Models of visual object recognition and scene understanding [WILLOW]
Carpentier, Justin [Auteur]
Models of visual object recognition and scene understanding [WILLOW]
Département d'informatique - ENS-PSL [DI-ENS]
Duriez, Christian [Auteur]
Université de Lille
Deformable Robots Simulation Team [DEFROST ]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Conference title :

IEEE International Conference on Soft Robotics (RoboSoft)

Conference organizers(s) :

IEEE

City :

San Diego (CA)

Country :

Etats-Unis d'Amérique

Start date of the conference :

2024-04-14

Publication date :

2024-04

English keyword(s) :

Optimization and Optimal Control
Modeling Control and Learning for Soft Robots
Soft Robot Applications

HAL domain(s) :

Informatique [cs]/Robotique [cs.RO]

English abstract : [en]

Over the past decades, trajectory optimization (TO) has become an effective solution for solving complex motion generation problems in robotics, ranging from autonomous driving to humanoids. Yet, TO methods remain limited ...
Show more >Over the past decades, trajectory optimization (TO) has become an effective solution for solving complex motion generation problems in robotics, ranging from autonomous driving to humanoids. Yet, TO methods remain limited to robots with tens of degrees of freedom (DoFs), limiting their usage in soft robotics, where kinematic models may require hundreds of DoFs in general. In this work, we introduce a generic method to perform trajectory optimization based on continuum mechanics to describe the behavior of soft robots. The core idea is to condense the dynamics of the soft robot in the constraint space in order to obtain a reduced dynamics formulation, which can then be plugged into numerical TO methods. In particular, we show that these condensed dynamics can be easily coupled with differential dynamic programming methods for solving TO problems involving soft robots. This method is evaluated on three different soft robots with different geometries and actuation.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Infrastructure technologique pour la recherche d'excellence en robotique
Apprentissage et contrôle de modèles sensori-moteurs en robotique
PaRis Artificial Intelligence Research InstitutE

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL