Publication

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Related publications (32)

Learning and optimization of anticipatory feedback controllers for robot manipulation

Programming intelligent robots requires robust controllers that can achieve desired tasks while adapting to the changes in the task and the environment. In this thesis, we address the challenges in designing such adaptive and anticipatory feedback controll ...

EPFL2023

Introducing Productive Engagement for Social Robots Supporting Learning

Jauwairia Nasir

We have all been one such student or seen such students who can maintain the 'good student' image while playing a video game under the table or those loyal backbenchers, seemingly always distracted, who then ace their exams. These intricacies of human beha ...

EPFL2022

Social/dialogical roles of social robots in supporting children's learning of language and literacy-A review and analysis of innovative roles

Barbara Bruno

One of the many purposes for which social robots are designed is education, and there have been many attempts to systematize their potential in this field. What these attempts have in common is the recognition that learning can be supported in a variety of ...

FRONTIERS MEDIA SA2022

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

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

Children Teach Handwriting to a Social Robot with Different Learning Competencies

Pierre Dillenbourg, Shruti Chandra, Ana Paiva

As robots are entering into educational fields to enhance children's learning, it becomes relevant to explore different methods of learning in the area of child-robot interaction. In this article, we present an autonomous educational system incorporating a ...

SPRINGER2020

CoWriting Kazakh: Learning a New Script with a Robot

Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal

In the Republic of Kazakhstan, the transition from Cyrillic to Latin alphabet raises challenges to training an entire population in writing the new script. This paper presents a CoWriting Kazakh system, an extension of the existing CoWriter system, aiming ...

Association for Computing Machinery2020

Bayesian Gaussian mixture model for robotic policy imitation

Sylvain Calinon, Emmanuel Pignat

A common approach to learn robotic skills is to imitate a demonstrated policy. Due to the compounding of small errors and perturbations, this approach may let the robot leave the states in which the demonstrations were provided. This requires the considera ...

2019

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Nadia Barbara Figueroa Fernandez

Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

EPFL2019

Learning How to Write with a Social Robot

Shruti Chandra

Learning handwriting is one of the main occupations for children in primary education. It is a complex skill that has been associated with children’s learning and development. Poor handwriting skills affect children negatively concerning their academic per ...

EPFL2019

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