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How rich motor skills empower robots at last: Insights and progress of the AMARSi project

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journal contribution
posted on 2015-03-13, 12:07 authored by Andrea SoltoggioAndrea Soltoggio, Jochen Steil
Flexible, robust, precise, adaptive, compliant and safe: these are some of the qualities robots must have to interact safely and productively with humans. Yet robots are still nowadays perceived as too rigid, clumsy and not sufficiently adaptive to work efficiently in interaction with people. The AMARSi Project endeavors to design and implement rich motor skills, unique flexibility, compliance and state-of-the-art learning in robots. Inspired by human-recorded motion and learning behavior, similarly versatile and constantly adaptive movements and skills endow robots with singularly human-like motor dynamics and learning. The AMARSi challenge is to integrate novel biological notions, advanced learning algorithms and cutting-edge compliant mechanics in the design of fully-fledged humanoid and quadruped robots with an unprecedented aptitude for integrating in our environments.

Funding

This work was supported by the European Community’s Seventh Framework Programme FP7/2007-2013, Challenge 2 Cognitive Systems, Interaction, Robotics (Grant No. 248311—AMARSi).

History

School

  • Science

Department

  • Computer Science

Published in

Kuenstlich Intelligenz

Volume

26

Issue

4

Pages

407 - 410

Citation

SOLTOGGIO, A. and STEIL, J., 2012. How rich motor skills empower robots at last: Insights and progress of the AMARSi project. Künstliche Intelligenz, 26 (4), pp. 407-410

Publisher

© Springer

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2012

Notes

The final publication is available at Springer via http://dx.doi.org/10.1007/s13218-012-0192-5.

eISSN

1610-1987

Language

  • en

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