SMARTTALK: A learning-based framework for natural human-robot interaction

Cameron Fabbri, Junaed Sattar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper presents a learning-based framework named SMARTTALK for natural-language human-robot interaction (HRI). The primary goal of this framework is to enable non-expert users to control and program a mobile robot using natural language commands. SMARTTALK is modality-agnostic, and is capable of integrating with both speech and non-speech (e.g., gesture-based) communication. Initially, robots using this mechanism are equipped with a limited vocabulary of primitive commands and functionality; however, through extended use and interaction, the robots are able to learn new commands and adapt to user's behaviors and habits. This makes the proposed framework highly desirable for long-term deployment in a variety of HRI tasks. We present the design of this framework and experimental data on a number of realistic scenarios to evaluate its performance. A qualitative experiment on a robotic platform is also presented.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016
EditorsJuan Guerrero
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages376-382
Number of pages7
ISBN (Electronic)9781509024919
DOIs
StatePublished - Dec 28 2016
Event13th Conference on Computer and Robot Vision, CRV 2016 - Victoria, Canada
Duration: Jun 1 2016Jun 3 2016

Publication series

NameProceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016

Other

Other13th Conference on Computer and Robot Vision, CRV 2016
CountryCanada
CityVictoria
Period6/1/166/3/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

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