{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T12:15:03Z","timestamp":1740140103788,"version":"3.37.3"},"reference-count":32,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","funder":[{"name":"German Federal Ministry of Education and Research","award":["16SV7984 (KOBO34)","ERC StG 640554"],"award-info":[{"award-number":["16SV7984 (KOBO34)","ERC StG 640554"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Human. Robot."],"published-print":{"date-parts":[[2020,2]]},"abstract":"<jats:p> Intelligent assistive robots can potentially contribute to maintaining an elderly person\u2019s independence by supporting everyday life activities. However, the number of different and personalized activities to be supported renders pre-programming of all respective robot behaviors prohibitively difficult. Instead, to cope with a continuous and potentially open-ended stream of cooperative tasks, new collaborative robot behaviors need to be continuously learned and updated from demonstrations. To this end, we introduce an online learning method to incrementally build a cooperative skill library of probabilistic interaction primitives. The resulting model chooses a corresponding robot response to a human movement where the human intention is extracted from previously demonstrated movements. While existing batch learning methods for movement primitives usually learn such skill libraries only once for a pre-defined number of different skills, our approach enables extending the skill library in an open-ended and online fashion from new incoming demonstrations. The proposed approach is evaluated on a low-dimensional benchmark task and in a collaborative scenario with a 7DoF robot, where we also investigate the generalization of learned skills between different subjects. <\/jats:p>","DOI":"10.1142\/s0219843620500012","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T16:04:43Z","timestamp":1575302683000},"page":"2050001","source":"Crossref","is-referenced-by-count":4,"title":["Incremental Learning of an Open-Ended Collaborative Skill Library"],"prefix":"10.1142","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3571-6848","authenticated-orcid":false,"given":"Dorothea","family":"Koert","sequence":"first","affiliation":[{"name":"Intelligent Autonomous Systems Group, Department of Computer Science, Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Susanne","family":"Trick","sequence":"additional","affiliation":[{"name":"Psychology of Information Processing Group, Department of Psychology, Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Marco","family":"Ewerton","sequence":"additional","affiliation":[{"name":"Intelligent Autonomous Systems Group, Department of Computer Science, Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Michael","family":"Lutter","sequence":"additional","affiliation":[{"name":"Intelligent Autonomous Systems Group, Department of Computer Science, Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Jan","family":"Peters","sequence":"additional","affiliation":[{"name":"Intelligent Autonomous Systems Group, Department of Computer Science, Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"},{"name":"Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"}]}],"member":"219","published-online":{"date-parts":[[2020,1,10]]},"reference":[{"key":"S0219843620500012BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/S1364-6613(99)01327-3"},{"volume-title":"Human Motor Control","year":"2009","author":"Rosenbaum D. 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