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Publications associées (238)

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Learning From Humans

Aude Billard, Sylvain Calinon

This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imita ...

Springer2016

Learning Controllers for Reactive and Proactive Behaviors in Human-Robot Collaboration

Sylvain Calinon

Designed to safely share the same workspace as humans and assist them in various tasks, the new collaborative robots are targeting manufacturing and service applications that once were considered unattainable. The large diversity of tasks to carry out, the ...

2016

Variable Duration Movement Encoding with Minimal Intervention Control

Sylvain Calinon

Programming by Demonstration (PbD) offers a user-friendly way of skill transfer from human to robot. Typically, demonstration data do not contain the control inputs required to reproduce the demonstrated skill. These control commands can be obtained from a ...

2016

A modular approach to learning manipulation strategies from human demonstration

Aude Billard, Miao Li, Ravin Luis De Souza

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is complex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly w ...

Springer Verlag2016

Synthesizing Robotic Handwriting Motion by Learning from Human Demonstrations

Aude Billard, Hang Yin, Ana Paiva

This paper contributes a novel framework that enables a robotic agent to efficiently learn and synthesize believable handwriting motion. We situate the framework as a foundation with the goal of allowing children to observe, correct and engage with the rob ...

2016

Learning Robot Manipulation Tasks with Task-Parameterized Semi-Tied Hidden Semi-Markov Model

Sylvain Calinon, Ajay Kumar Tanwani

In this paper, we investigate the semi-tied Gaussian mixture models for robust learning and adaptation of robot manipulation tasks. We make use of the spatial and temporal correlation in the data by tying the covariance matrices of the mixture model with c ...

2016

Thymio

Fanny Riedo

Technology is now an important part of our lives. We often see robots cited as the future of education, and reports of their imminent entrance in schools. New projects create buzz in the media and online, but when we look at the actual situation, very few ...

EPFL2015

Decentralized multi-robot coordination in crowded workspaces

Laleh Makarem

The coordination of multi-robot systems is becoming one of the most important areas of research in robotics, mostly because it is required by numerous complex applications. These applications range from intelligent transportation systems, search and rescue ...

EPFL2015

Learning Optimal Controllers in Human-robot Cooperative Transportation Tasks with Position and Force Constraints

Sylvain Calinon

Human-robot collaboration seeks to have humans and robots closely interacting in everyday situations. For some tasks, physical contact between the user and the robot may occur, originating significant challenges at safety, cognition, perception and control ...

2015

Learning the Stiffness of a Continuous Soft Manipulator from Multiple Demonstrations

Sylvain Calinon

Continuous soft robots are becoming more and more widespread in applications, due to their increased safety and flexibility in critical applications. The possibility of having soft robots that are able to change their stiffness in selected parts can help i ...

Springer2015