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Interactive Learning from Unlabeled Instructions

Publications associées (70)

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Wearable Technologies for Embodied Human-Robot Interaction

Carine Rognon

Robotic teleoperation is fundamental to augment the resilience, precision, and force of robots with the cognition of the operator. However, current interfaces, such as joysticks and remote controllers, are often complicated to handle since they require cog ...

EPFL2019

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Robotics teleoperation enables human operators to control the movements of distally located robots. The development of new wearable interfaces as alternatives to hand-held controllers has created new modalities of control, which are more intuitive to use. ...

2019

A dynamical system approach to task-adaptation in physical human-robot interaction

Aude Billard, Mahdi Khoramshahi

The goal of this work is to enable robots to intelligently and compliantly adapt their motions to the intention of a human during physical Human-Robot Interaction in a multi-task setting. We employ a class of parameterized dynamical systems that allows for ...

SPRINGER2019

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

Brain-Computer Interface Racing at the Cybathlon 2016

Brain-computer interfaces measure the electricity produced by the brain and translate it into commands that are sent to a machine. However, it is often difficult to judge how quickly a user will be able to perform a task using a brain-computer interface wi ...

2019

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Human-Robot Interfaces (HRIs) can be hard to master for inexperienced users, making the teleoperation of mobile robots a difficult task. The development of Body-Machine Interfaces (BoMIs) represents a promising approach to making a user more proficient, by ...

2019

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Recent advances in the Brain-Machine Interface (BMI) and in the robotic fields allowed researchers to design a new generation of brain-actuated neuroprostheses to control a variety of assistive devices-ranging from powered wheelchairs to telepresence robot ...

IEEE2019

Workshops of the seventh international brain-computer interface meeting: not getting lost in translation

Kyuhwa Lee, Ricardo Andres Chavarriaga Lozano, Anton Nijholt

The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics ...

TAYLOR & FRANCIS LTD2019

The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users

José del Rocio Millán Ruiz, Serafeim Perdikis, Luca Tonin, Sareh Saeedi, Christoph Schneider

This work aims at corroborating the importance and efficacy of mutual learning in motor imagery (MI) brain–computer interface (BCI) by leveraging the insights obtained through our participation in the BCI race of the Cybathlon event. We hypothesized that, ...

2018

A Dynamical System Approach to Task-Adaptation in Physical Human-Robot Interaction

Aude Billard, Mahdi Khoramshahi

The goal of this work is to enable robots to intelligently and compliantly adapt their motions to the intention of a human during physical Human-Robot Interaction (pHRI) in a multi-task setting. We employ a class of parameterized dynamical systems that all ...

2018