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.
|Title of host publication||Towards Autonomous Robotic Systems: 18th Annual Conference, TAROS 2017, Guildford, UK, July 19–21, 2017|
|Subtitle of host publication||Proceedings|
|Editors||Yang Gao, Saber Fallah, Yaochu Jin, Constantina Lakakou|
|Place of Publication||Berlin|
|Publication status||E-pub ahead of print - 20 Jul 2017|
|Name||Lecture Notes in Artificial Intelligence|
Wortham, R. H., Theodorou, A., & Bryson, J. J. (2017). Robot transparency: Improving understanding of intelligent behaviour for designers and users. In Y. Gao, S. Fallah, Y. Jin, & C. Lakakou (Eds.), Towards Autonomous Robotic Systems: 18th Annual Conference, TAROS 2017, Guildford, UK, July 19–21, 2017 : Proceedings (pp. 274-289). (Lecture Notes in Artificial Intelligence; Vol. 10454). Berlin: Springer. https://doi.org/10.1007/978-3-319-64107-2 22