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Sylvain Calinon

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Publications associées (85)

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Programming by Demonstration for Shared Control with an Application in Teleoperation

Sylvain Calinon

Shared control strategies can improve task-performance in teleoperation. In such systems automation guides or corrects a human operator. The amount of correction or guidance that is provided is denoted the level-of-automation. As the variety of teleoperati ...

2018

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Sylvain Calinon, Noémie Laure Gwendoline Jaquier, Emmanuel Pignat, Hakan Girgin

Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In this pa ...

IEEE2020

Logic Learning From Demonstrations for Multi-Step Manipulation Tasks in Dynamic Environments

Sylvain Calinon, Teng Xue, Amirreza Razmjoo Fard

Learning from Demonstration (LfD) stands as an efficient framework for imparting human-like skills to robots. Nevertheless, designing an LfD framework capable of seamlessly imitating, generalizing, and reacting to disturbances for long-horizon manipulation ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

A Minimum-Jerk Approach to Handle Singularities in Virtual Fixtures

Sylvain Calinon

Implementing virtual fixtures in guiding tasks constrains the movement of the robot's end effector to specific curves within its workspace. However, incorporating guiding frameworks may encounter discontinuities when optimizing the reference target positio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Handling of multiple constraints and motion alternatives in a robot programming by demonstration framework

Aude Billard, Sylvain Calinon, Florent D'Halluin

We consider the problem of learning robust models of robot motion through demonstration. An approach based on Hidden Markov Model (HMM) and Gaussian Mixture Regression (GMR) is proposed to extract redundancies across multiple demonstrations, and build a ti ...

2009

A Probabilistic Approach to Multi-Modal Adaptive Virtual Fixtures

Sylvain Calinon

Virtual Fixtures (VFs) provide haptic feedback for teleoperation, typically requiring distinct input modalities for different phases of a task. This often results in vision- and position-based fixtures. Vision-based fixtures, particularly, require the hand ...

Ieee-Inst Electrical Electronics Engineers Inc2024

A Tutorial on Task-Parameterized Movement Learning and Retrieval

Sylvain Calinon

Task-parameterized models of movements aims at automatically adapting movements to new situations encountered by a robot. The task parameters can for example take the form of positions of objects in the environment, or landmark points that the robot should ...

2016

Learning, Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction

Sylvain Calinon

This study proposes a novel imitation learning approach for the stochastic generation of human-like rhythmic wave gestures and their modulation for effective non-verbal communication through a probabilistic formulation using joint angle data from human dem ...

ACM2020

Teaching a Humanoid Robot to Recognize and Reproduce Social Cues

Aude Billard, Sylvain Calinon

In a Robot Programming by Demonstration framework, several demonstrations of a task are required to generalize and reproduce the task under different circumstances. To teach a task to the robot, explicit pointers are required to signal the start/end of a d ...

2006

Incremental Learning of Gestures by Imitation in a Humanoid Robot

Aude Billard, Sylvain Calinon

We present an approach to teach incrementally human gestures to a humanoid robot. The learning process consists of first projecting the movement data in a latent space and encoding the resulting signals in a Gaussian Mixture Model (GMM). We compare the per ...

2007

Special issue on robot learning for human-robot collaboration

Sylvain Calinon

The goal of this special issue is to document and highlight recent progress in robot learning for human–robot collaboration (HRC), covering a diversity of articles that reflect the state-of-the-art in the field. Following an open call for papers, we receiv ...

2018

D-LGP: Dynamic Logic-Geometric Program for Reactive Task and Motion Planning

Sylvain Calinon, Teng Xue, Amirreza Razmjoo Fard

Many real-world sequential manipulation tasks involve a combination of discrete symbolic search and continuous motion planning, collectively known as combined task and motion planning (TAMP). However, prevailing methods often struggle with the computationa ...

IEEE2024

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

Dexterous Undersea Interventions with Far Distance Onshore Supervision: the DexROV Project

Sylvain Calinon, Ajay Kumar Tanwani

The operation of a ROV requires significant off-shore dedicated manpower to handle and operate the robotic platform. In order to reduce the burden of operations, DexROV proposes to work out more cost effective and time efficient ROV operations, where manne ...

2016

Learning Dynamical System Modulation for Constrained Reaching Tasks

Aude Billard, Sylvain Calinon, Micha Hersch, 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

Learning Joint Space Reference Manifold for Reliable Physical Assistancey

Sylvain Calinon, Amirreza Razmjoo Fard

This paper presents a study on the use of the Talos humanoid robot for performing assistive sit-to-stand or stand-to-sit tasks. In such tasks, the human exerts a large amount of force (100-200 N) within a very short time (2-8 s), posing significant challen ...

IEEE2023

Teaching Physical Collaborative Tasks: Object-Lifting Case Study with a Humanoid

Aude Billard, Sylvain Calinon, Elena Gribovskaya

This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the hapti ...

IEEE2009

Improving the control of prosthetic hands with tactile sensing

Sylvain Calinon, Noémie Laure Gwendoline Jaquier

Despite recent advances in prostheses, intuitive and robust control of poly-articulated prosthetic hands remains an unsolved problem. The TACT-HAND project aims at providing hand amputees with improved dexterous capabilities by exploiting tactile sensing a ...

2018

Learning and reproduction of gestures by imitation: An approach based on Hidden Markov Model and Gaussian Mixture Regression

Aude Billard, Sylvain Calinon, Eric Sauser, Florent D'Halluin

We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrat ...

Institute of Electrical and Electronics Engineers2010