Visible to the public Effects of Task-Dependent Robot Errors on Trust in Human-Robot Interaction: A Pilot Study

TitleEffects of Task-Dependent Robot Errors on Trust in Human-Robot Interaction: A Pilot Study
Publication TypeConference Paper
Year of Publication2019
AuthorsHaider, C., Chebotarev, Y., Tsiourti, C., Vincze, M.
Conference Name2019 IEEE SmartWorld, Ubiquitous Intelligence Computing, Advanced Trusted Computing, Scalable Computing Communications, Cloud Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Date PublishedAug. 2019
PublisherIEEE
ISBN Number978-1-7281-4034-6
Keywordselderly care, experimental design, Human Behavior, human factors, human robot interaction, human user, human-robot interaction, mobile robots, Monitoring, pubcrawl, reliability, resilience, Resiliency, robot failures, Robot sensing systems, Robot Trust, robust trust, self-reported trust ratings, Service robots, Task Analysis, task-dependent robot errors, Time factors, time-critical task, Trust
Abstract

The growing diffusion of robotics in our daily life demands a deeper understanding of the mechanisms of trust in human-robot interaction. The performance of a robot is one of the most important factors influencing the trust of a human user. However, it is still unclear whether the circumstances in which a robot fails to affect the user's trust. We investigate how the perception of robot failures may influence the willingness of people to cooperate with the robot by following its instructions in a time-critical task. We conducted an experiment in which participants interacted with a robot that had previously failed in a related or an unrelated task. We hypothesized that users' observed and self-reported trust ratings would be higher in the condition where the robot has previously failed in an unrelated task. A proof-of-concept study with nine participants timidly confirms our hypothesis. At the same time, our results reveal some flaws in the design experimental, and encourage a future large scale study.

URLhttps://ieeexplore.ieee.org/document/9060178
DOI10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00072
Citation Keyhaider_effects_2019