### Abstract

My work focuses on human-centered robotics applications in which the robots can acquire new skills from only few demonstrations and interactions. It requires the development of models that can exploit the structure and geometry of the acquired data in an efficient way, the development of optimal control techniques that can exploit the learned task variations and coordination patterns, and the development of intuitive interfaces to acquire meaningful demonstrations. The developed approaches can be applied to a wide range of manipulation skills, with robots that are either close to us (assistive and industrial robots), parts of us (prosthetics and exoskeletons), or far away from us (teleoperation). This document presents an overview of the recent research developments in the Robot Learning & Interaction group at the Idiap Research Institute, with pointers to our most recent publications presenting the proposed approaches in further details. For each of the proposed research directions, I also discuss ongoing and further work that needs to be investigated to advance the proposed research lines.

### Bibtex reference

@techreport{Calinon22misc,
author="Calinon, S.",
title="Research statement",
institution="Idiap Research Institute",
year="2022"
}


### Video

Invited talk at the ICRA 2021 Workshop on Unlocking the potential of human-robot collaboration for industrial applications.