TU Darmstadt / ULB / TUbiblio

Online Learning of an Open-Ended Skill Library for Collaborative Tasks

Koert, Dorothea ; Trick, Susanne ; Ewerton, Marco ; Lutter, Michael ; Peters, Jan (2022)
Online Learning of an Open-Ended Skill Library for Collaborative Tasks.
International Conference on Humanoid Robots (Humanoids). Beijing, China (06.-09.11.2018)
doi: 10.1109/HUMANOIDS.2018.8625031
Konferenzveröffentlichung, Bibliographie

Dies ist die neueste Version dieses Eintrags.

Kurzbeschreibung (Abstract)

Intelligent robotic assistants can potentially improve the quality of life for elderly people and help them maintain their independence. However, the number of different and personalized tasks render pre-programming of such assistive robots prohibitively difficult. Instead, to cope with a continuous and open-ended stream of cooperative tasks, new collaborative skills need to be continuously learned and updated from demonstrations. To this end, we introduce an online learning method for a skill library of collaborative tasks that employs an incremental mixture model of probabilistic interaction primitives. This model chooses a corresponding robot response to a human movement where the human intention is extracted from previously demonstrated movements. Unlike existing batch methods of movement primitives for human-robot interaction, our approach builds a library of skills online, in an open-ended fashion and updates existing skills using new demonstrations. The resulting approach was evaluated both on a simple benchmark task and in an assistive human-robot collaboration scenario with a 7DoF robot arm.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2022
Autor(en): Koert, Dorothea ; Trick, Susanne ; Ewerton, Marco ; Lutter, Michael ; Peters, Jan
Art des Eintrags: Bibliographie
Titel: Online Learning of an Open-Ended Skill Library for Collaborative Tasks
Sprache: Englisch
Publikationsjahr: 2022
Ort: Darmstadt
Verlag: IEEE
Buchtitel: 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)
Kollation: 8 Seiten
Veranstaltungstitel: International Conference on Humanoid Robots (Humanoids)
Veranstaltungsort: Beijing, China
Veranstaltungsdatum: 06.-09.11.2018
DOI: 10.1109/HUMANOIDS.2018.8625031
Zugehörige Links:
Kurzbeschreibung (Abstract):

Intelligent robotic assistants can potentially improve the quality of life for elderly people and help them maintain their independence. However, the number of different and personalized tasks render pre-programming of such assistive robots prohibitively difficult. Instead, to cope with a continuous and open-ended stream of cooperative tasks, new collaborative skills need to be continuously learned and updated from demonstrations. To this end, we introduce an online learning method for a skill library of collaborative tasks that employs an incremental mixture model of probabilistic interaction primitives. This model chooses a corresponding robot response to a human movement where the human intention is extracted from previously demonstrated movements. Unlike existing batch methods of movement primitives for human-robot interaction, our approach builds a library of skills online, in an open-ended fashion and updates existing skills using new demonstrations. The resulting approach was evaluated both on a simple benchmark task and in an assistive human-robot collaboration scenario with a 7DoF robot arm.

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Intelligente Autonome Systeme
TU-Projekte: EC/H2020|640554|SKILLS4ROBOTS
Hinterlegungsdatum: 02 Aug 2024 12:45
Letzte Änderung: 02 Aug 2024 12:45
PPN:
Export:
Suche nach Titel in: TUfind oder in Google

Verfügbare Versionen dieses Eintrags

Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen