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The IDDM allows the intention to be inferred from observed movements using Bayes\u2019 theorem. The IDDM simultaneously finds a latent state representation of noisy and high-dimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human\u2013robot interaction scenarios, i.e. target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.<\/jats:p>","DOI":"10.1177\/0278364913478447","type":"journal-article","created":{"date-parts":[[2013,4,18]],"date-time":"2013-04-18T21:07:50Z","timestamp":1366319270000},"page":"841-858","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":128,"title":["Probabilistic movement modeling for intention inference in human\u2013robot interaction"],"prefix":"10.1177","volume":"32","author":[{"given":"Zhikun","family":"Wang","sequence":"first","affiliation":[{"name":"Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"},{"name":"Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Katharina","family":"M\u00fclling","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"},{"name":"Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Marc Peter","family":"Deisenroth","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"Heni","family":"Ben Amor","sequence":"additional","affiliation":[{"name":"Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]},{"given":"David","family":"Vogt","sequence":"additional","affiliation":[{"name":"Technical University Bergakademie Freiberg, Freiberg, Germany"}]},{"given":"Bernhard","family":"Sch\u00f6lkopf","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"}]},{"given":"Jan","family":"Peters","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Intelligent Systems, T\u00fcbingen, Germany"},{"name":"Technische Universit\u00e4t Darmstadt, Darmstadt, Germany"}]}],"member":"179","published-online":{"date-parts":[[2013,4,18]]},"reference":[{"key":"bibr1-0278364913478447","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015430"},{"key":"bibr2-0278364913478447","volume-title":"A Robot Ping-Pong Player: Experiment in Real-time Intelligent Control","author":"Anderson R","year":"1988"},{"key":"bibr3-0278364913478447","doi-asserted-by":"publisher","DOI":"10.1023\/A:1020281327116"},{"key":"bibr4-0278364913478447","doi-asserted-by":"publisher","DOI":"10.1016\/j.cognition.2009.07.005"},{"key":"bibr5-0278364913478447","unstructured":"Baker C, Tenenbaum J, Saxe R (2006) Bayesian models of human action understanding. 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