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Interactive reinforcement learning through speech guidance in a domestic scenario

conference contribution
posted on 01.01.2015, 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.

History

Event

International Neural Network Society. Conference (2015 : Killarney, Ireland)

Series

International Neural Network Society Conference

Pagination

1 - 8

Publisher

Institute of Electrical and Electronics Engineers

Location

Killarney, Ireland

Place of publication

Piscataway, N.J.

Start date

12/07/2015

End date

17/07/2015

ISBN-13

9781479919604

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2015, IEEE

Editor/Contributor(s)

[Unknown]

Title of proceedings

IJCNN 2015 : Proceedings of the 2015 International Joint Conference on Neural Networks