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KI - Künstliche Intelligenz
Erschienen in: KI - Künstliche Intelligenz 4/2012

01.11.2012 | Projekt

How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project

verfasst von: Andrea Soltoggio, Jochen J. Steil

Erschienen in: KI - Künstliche Intelligenz | Ausgabe 4/2012

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Abstract

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.
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Metadaten
Titel
How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project
verfasst von
Andrea Soltoggio
Jochen J. Steil
Publikationsdatum
01.11.2012
Verlag
Springer-Verlag
Erschienen in
KI - Künstliche Intelligenz / Ausgabe 4/2012
Print ISSN: 0933-1875
Elektronische ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-012-0192-5

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Dissertationen und Habilitationen

Adaptive Dissimilarity Measures, Dimension Reduction and Visualization (University of Groningen)