Model-free approaches for modeling and control of robotic systems

Approches à base de données pour la modélisation et la commande de systèmes robotiques

Achille Melingui (1)

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

In work presented above, we have presented control strategies for the autonomous navigation of mobile robots. We have also presented learning architectures for the modeling and control of continuum manipulators and a learning architecture that maintains multiple inverse kinematic solutions for high dof rigid manipulators. Finally, we have proposed new control laws for the control of flexible joint manipulators. Our prospective study is a continuation of these works and aims at improving the existing ones. Our research team recently interested in Machine Learning algorithms (artificial neural networks and machine vectors support), artificial intelligence (Fuzzy logic, artificial potential field), and backstepping control. Our main short term objective is to reinforce our research team of the UY1, which currently has only two confirmed researchers.

Mots clés: Robotics; Machine Learning algorithms; Artificial Intelligence; Backstepping control

Mots clés: Robotique; Intelligence artificielle

Domaines: Automatique / Robotique; Apprentissage [cs.LG]

Achille Melingui. Model-free approaches for modeling and control of robotic systems. Automatic. Université de Lille, 2021. ⟨tel-04429476⟩