Publications by Florent Günter

Using reinforcement learning for optimizing the reproduction of tasks in robot programming by demonstration

As robots start pervading human environments, the need for new interfaces that would simplify human-robot interaction has become more pressing. Robot Programming by Demonstration (RbD) develops intuitive ways of programming robots, taking inspiration in st ...

EPFL2009

Dynamical System Modulation for Robot Learning via Kinesthetic Demonstrations

Micha Hersch, Aude Billard, Sylvain Calinon, Florent Günter

We present a system for robust robot skill acquisition from kinesthetic demonstrations. This system allows a robot to learn a simple goal-directed gesture, and correctly reproduce it despite changes in the initial conditions, and perturbations in the envir ...

2008

The Dof-Box Project: An Educational Kit for Configurable Robots

André Guignard, Aude Billard, Auke Ijspeert, Florent Günter, Davis Daidié, Olivier Barbey

This paper describes the Dof-Box, a modular, reconfigurable robot, used in Hands-on practicals of robotics taught to miroengineering students. We present the hardware and software of the robots and describe the pedagogical approach adopted in the practical ...

2007

Using Reinforcement Learning to Adapt an Imitation Task

Aude Billard, Florent Günter

The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots that can be accomplished by everyone. When a demonstrator teaches a task to a robot, he/she shows some ways of fulfilling the task, but ...

2007

On Learning, Representing and Generalizing a Task in a Humanoid Robot

Aude Billard, Sylvain Calinon, Florent Günter

We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a s ...

2007

Learning Dynamical System Modulation for Constrained Reaching Tasks

Micha Hersch, Aude Billard, Sylvain Calinon, Florent Günter

In this paper we combine kinesthetic demonstrations and dynamical systems to enable a humanoid robot to imitate constrained reaching gestures directed toward a target. Using a learning algorithm based on Gaussian Mixture Regression, the task constraints ar ...

2006

Discriminative and Adaptive Imitation in Uni-Manual and Bi-Manual Tasks

Aude Billard, Sylvain Calinon, Florent Günter

This paper addresses the problems of what to imitate and how to imitate in simple uni- and bi-manual manipulatory tasks. To solve the what to imitate issue, we use a probabilistic method, based on Hidden Markov Models, for extracting the relative importanc ...

Elsevier2006

On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts

Aude Billard, Sylvain Calinon, Florent Günter

This paper presents an architecture for solving generically the problem of extracting the relevant features of a given task in a programming by demonstration framework and the problem of generalizing the acquired knowledge to various contexts. We validate ...

2006

Design of a Biomimetic Upper Body for the Humanoid Robot Robota

André Guignard, Aude Billard, Florent Günter

This paper presents the current prototype of doll-shaped humanoid robot Robota. The use of the robot Robota as part of studies with disabled children sets a number of constraints on its design. In particular, it requires that the robot bears a human likene ...

2005

Goal-Directed Imitation in a Humanoid Robot

Aude Billard, Sylvain Calinon, Florent Günter

Our work aims at developing a robust discriminant controller for robot programming by demonstration. It addresses two core issues of imitation learning, namely "what to imitate" and "how to imitate". This paper presents a method by which a robot extracts t ...

2005