Forward Kinematic Modeling of Conical-Shaped ...
Type de document :
Compte-rendu et recension critique d'ouvrage
Titre :
Forward Kinematic Modeling of Conical-Shaped Continuum Manipulators
Auteur(s) :
Bouyom Boutchouang, A. [Auteur]
Melingui, Achille [Auteur]
Mvogo Ahanda, J. [Auteur]
Lakhal, Othman [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Biya Motto, Frederic [Auteur]
Université de Yaoundé I [UY1]
Merzouki, Rochdi [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Melingui, Achille [Auteur]
Mvogo Ahanda, J. [Auteur]
Lakhal, Othman [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Biya Motto, Frederic [Auteur]
Université de Yaoundé I [UY1]
Merzouki, Rochdi [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la revue :
Robotica
Pagination :
1760-1778
Éditeur :
Cambridge University Press
Date de publication :
2021-10
ISSN :
0263-5747
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Résumé en anglais : [en]
SUMMARY Forward kinematics is essential in robot control. Its resolution remains a challenge for continuum manipulators because of their inherent flexibility. Learning-based approaches allow obtaining accurate models. ...
Lire la suite >SUMMARY Forward kinematics is essential in robot control. Its resolution remains a challenge for continuum manipulators because of their inherent flexibility. Learning-based approaches allow obtaining accurate models. However, they suffer from the explosion of the learning database that wears down the manipulator during data collection. This paper proposes an approach that combines the model and learning-based approaches. The learning database is derived from analytical equations to prevent the robot from operating for long periods. The database obtained is handled using Deep Neural Networks (DNNs). The Compact Bionic Handling robot serves as an experimental platform. The comparison with existing approaches gives satisfaction.Lire moins >
Lire la suite >SUMMARY Forward kinematics is essential in robot control. Its resolution remains a challenge for continuum manipulators because of their inherent flexibility. Learning-based approaches allow obtaining accurate models. However, they suffer from the explosion of the learning database that wears down the manipulator during data collection. This paper proposes an approach that combines the model and learning-based approaches. The learning database is derived from analytical equations to prevent the robot from operating for long periods. The database obtained is handled using Deep Neural Networks (DNNs). The Compact Bionic Handling robot serves as an experimental platform. The comparison with existing approaches gives satisfaction.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
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