I Like the Way You Move: A mixed-methods approach for studying the effects of robot motion on collaborative human robot interaction

Jonas E. Pedersen, Kristoffer Wulff Christensen, Damith Heath, Elizabeth Jochum

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

Human robot collaboration is an increasingly relevant area within Human Robot Interaction. As robots move into dynamic environments and engage in collaborative tasks with people, there is a need to further understand how perceptual and communication cues facilitate and support Human Robot Collaboration. Building on prior Human Robot Interaction studies, we developed a mixed-methods approach for studying the effects of expressive movements of an industrial robot arm engaged in a collaborative drawing task. The purpose was to evaluate the effects of different movement qualities on participant experience while collaborating with a robot. We present our approach and the results of the experiments. Although we did not identify any significant difference in interactions where the robot moved expressively, our study highlights the importance of in-the-wild experiments and strategies for combining qualitative and quantitative methodologies.
Original languageEnglish
Title of host publicationInternational Conference on Social Robotics
Number of pages12
PublisherSpringer
Publication date2020
Pages73-84
ISBN (Print)978-3-030-62055-4
ISBN (Electronic)978-3-030-62056-1
DOIs
Publication statusPublished - 2020
EventInternational Conference on Social Robotics 2020 - Golden, United States
Duration: 14 Nov 202018 Nov 2020

Conference

ConferenceInternational Conference on Social Robotics 2020
Country/TerritoryUnited States
CityGolden
Period14/11/202018/11/2020
SeriesLecture Notes in Computer Science
Volume12483
ISSN0302-9743

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