Robot transparency: Improving understanding of intelligent behaviour for designers and users

Robert H. Wortham, Andreas Theodorou, Joanna J Bryson

Research output: Chapter or section in a book/report/conference proceedingChapter or section

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Autonomous robots can be difficult to design and understand. Designers have difficulty decoding the behaviour of their own robots simply by observing them. Naive users of robots similarly have difficulty deciphering robot behaviour simply through observation. In this paper we review relevant robot systems architecture, design, and transparency literature, and report on a programme of research to investigate practical approaches to improve robot transparency. We report on the investigation of real-time graphical and vocalised outputs as a means for both designers and end users to gain a better mental model of the internal state and decision making processes taking place within a robot. This approach, combined with a graphical approach to behaviour design, offers improved transparency for robot designers. We also report on studies of users’ understanding, where significant improvement has been achieved using both graphical and vocalisation transparency approaches.
Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems: 18th Annual Conference, TAROS 2017, Guildford, UK, July 19–21, 2017
Subtitle of host publicationProceedings
EditorsYang Gao, Saber Fallah, Yaochu Jin, Constantina Lakakou
Place of PublicationBerlin
ISBN (Electronic)978-3-319-64107-2
ISBN (Print)978-3-319-64106-5
Publication statusE-pub ahead of print - 20 Jul 2017

Publication series

NameLecture Notes in Artificial Intelligence
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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