Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 561020
Title Interactive teaching and experience extraction for learning about objects and robot activities
Author(s) Lim, Gi Hyun; Oliveira, Miguel; Mokhtari, Vahid; Kasaei, S.H.; Chauhan, Aneesh; Lopes, Luis Seabra; Tome, Ana Maria
Source In: The 23rd IEEE International Symposium on Robot and Human Interactive Communication. - IEEE - ISBN 9781479967636 - p. 153 - 160.
Event 23rd IEEE International Symposium on Robot and Human Interactive Communication, IEEE RO-MAN 2014, Edinburgh, 2014-08-25/2014-08-29
Publication type Contribution in proceedings
Publication year 2014

Intelligent service robots should be able to improve their knowledge from accumulated experiences through continuous interaction with the environment, and in particular with humans. A human user may guide the process of experience acquisition, teaching new concepts, or correcting insufficient or erroneous concepts through interaction. This paper reports on work towards interactive learning of objects and robot activities in an incremental and open-ended way. In particular, this paper addresses human-robot interaction and experience gathering. The robot's ontology is extended with concepts for representing human-robot interactions as well as the experiences of the robot. The human-robot interaction ontology includes not only instructor teaching activities but also robot activities to support appropriate feedback from the robot. Two simplified interfaces are implemented for the different types of instructions including the teach instruction, which triggers the robot to extract experiences. These experiences, both in the robot activity domain and in the perceptual domain, are extracted and stored in memory, and they are used as input for learning methods. The functionalities described above are completely integrated in a robot architecture, and are demonstrated in a PR2 robot.

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