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AI"],"abstract":"<jats:p>Humans use semantic concepts such as spatial relations between objects to describe scenes and communicate tasks such as \u201cPut the tea to the right of the cup\u201d or \u201cMove the plate between the fork and the spoon.\u201d Just as children, assistive robots must be able to learn the sub-symbolic meaning of such concepts from human demonstrations and instructions. We address the problem of incrementally learning geometric models of spatial relations from few demonstrations collected online during interaction with a human. Such models enable a robot to manipulate objects in order to fulfill desired spatial relations specified by verbal instructions. At the start, we assume the robot has no geometric model of spatial relations. Given a task as above, the robot requests the user to demonstrate the task once in order to create a model from a single demonstration, leveraging cylindrical probability distribution as generative representation of spatial relations. We show how this model can be updated incrementally with each new demonstration without access to past examples in a sample-efficient way using incremental maximum likelihood estimation, and demonstrate the approach on a real humanoid robot.<\/jats:p>","DOI":"10.3389\/frobt.2023.1151303","type":"journal-article","created":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T02:39:12Z","timestamp":1684377552000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Interactive and incremental learning of spatial object relations from human demonstrations"],"prefix":"10.3389","volume":"10","author":[{"given":"Rainer","family":"Kartmann","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tamim","family":"Asfour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,5,18]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1177\/0278364911410459","article-title":"Learning the semantics of object\u2013action relations by observation","volume":"30","author":"Aksoy","year":"2011","journal-title":"Int. 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