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Learning strategies and representations for intuitive robot learning from demonstration

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Skills Learning in Robots by Interaction with Users and Environment

Sylvain Calinon

The fast technological evolution and dissemination of multimodal sensors and compliant actuators bring a new human-centric perspective to robotics. The variety of human-robot interactions that stem from these new capabilities unveil compelling challenges f ...

2014

Idiap2014

Interactive Learning from Unlabeled Instructions

Inaki Asier Iturrate Gil

Interactive learning deals with the problem of learning and solving tasks using human instructions. It is common in human-robot interaction, tutoring systems, and in human-computer interfaces such as brain-computer ones. In most cases, learning these tasks ...

2014

Shared control of a robot using EEG-based feedback signals

Inaki Asier Iturrate Gil

In the last years there has been an increasing interest on using human feedback during robot operation to incorporate non-expert human expertise while learning complex tasks. Most work has considered reinforcement learning frameworks were human feedback, p ...

2013

Transfer Learning of Visual Concepts across Robots: a Discriminative Approach

Barbara Caputo, Tatiana Tommasi

While there is a general consensus that autonomous robots should be able to learn continuously over time, the learning process is traditionally envisioned for each specific robot situated in a given environment. This does not consider the fact that robots ...

Idiap2012

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Technology is playing an increasing role in our society. Therefore it becomes important to educate the general public, and young generations in particular, about the most common technologies. In this context, robots are excellent education tools, for many ...

Springer2012

Brain-coupled Interaction for Semi-autonomous Navigation of an Assistive Robot

José del Rocio Millán Ruiz, Roland Siegwart, Ricardo Andres Chavarriaga Lozano, Xavier Perrin

This paper presents a novel semi-autonomous navigation strategy designed for low throughput interfaces. A mobile robot (e.g. intelligent wheelchair) proposes the most probable action, as analyzed from the environment, to a human user who can either accept ...

Elsevier2010

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

Teaching a Humanoid: A User Study on Learning by Demonstration with HOAP-3

Aude Billard, Sylvain Calinon

This article reports on the results of a user study investigating the satisfaction of naïve users conducting two learning by demonstration tasks with the HOAP-3 robot. The main goal of this study was to gain insights on how to ensure a successful as well a ...

2009

How robot morphology and training order affect the learning of multiple behaviors

Joshua Evan Auerbach

Automatically synthesizing behaviors for robots with articulated bodies poses a number of challenges beyond those encountered when generating behaviors for simpler agents. One such challenge is how to optimize a controller that can orchestrate dynamic moti ...

IEEE2009