Publications de Thibaut Antoine Kulak

Active Learning of Bayesian Probabilistic Movement Primitives

Jean-Marc Odobez, Sylvain Calinon, Hakan Girgin, Thibaut Antoine Kulak

Learning from Demonstration permits non-expert users to easily and intuitively reprogram robots. Among approaches embracing this paradigm, probabilistic movement primitives (ProMPs) are a well-established and widely used method to learn trajectory distribu ...

IEEE2021

Combining Social and Intrinsically-Motivated Learning for Multi-Task Robot Skill Acquisition

Sylvain Calinon, Thibaut Antoine Kulak

IEEE2023

Learning strategies and representations for intuitive robot learning from demonstration

Thibaut Antoine Kulak

Robots are becoming more and more present around us, both in industries and in our homes. One key capability of robots is their adaptability to various situations that might appear in the real world. Robot skill learning is therefore a crucial aspect of ro ...

EPFL2021

Fourier movement primitives: an approach for learning rhythmic robot skills from demonstrations

Sylvain Calinon, Thibaut Antoine Kulak

Whether in factory or household scenarios, rhythmic movements play a crucial role in many daily-life tasks. In this paper we propose a Fourier movement primitive (FMP) representation to learn such type of skills from human demonstrations. Our approach take ...

2020