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Interactive reinforcement learning through speech guidance in a domestic scenario
conference contributionposted on 2015-01-01, 00:00 authored by F Cruz Naranjo, J Twiefel, S Magg, C Weber, S Wermter
Recently robots are being used more frequently as assistants in domestic scenarios. In this context we train an apprentice robot to perform a cleaning task using interactive reinforcement learning since it has been shown to be an efficient learning approach benefiting from human expertise for performing domestic tasks. The robotic agent obtains interactive feedback via a speech recognition system which is tested to work with five different microphones concerning their polar patterns and distance to the teacher to recognize sentences in different instruction classes. Moreover, the reinforcement learning approach uses situated affordances to allow the robot to complete the cleaning task in every episode anticipating when chosen actions are possible to be performed. Situated affordances and interaction allow to improve the convergence speed of reinforcement learning, and the results also show that the system is robust against wrong instructions that result from errors of the speech recognition system.
EventInternational Neural Network Society. Conference (2015 : Killarney, Ireland)
SeriesInternational Neural Network Society Conference
Pagination1 - 8
PublisherInstitute of Electrical and Electronics Engineers
Place of publicationPiscataway, N.J.
Publication classificationE1.1 Full written paper - refereed
Copyright notice2015, IEEE
Title of proceedingsIJCNN 2015 : Proceedings of the 2015 International Joint Conference on Neural Networks
CategoriesNo categories selected