Mitigating User Frustration through Adaptive Feedback based on Human-Automation Etiquette Strategies

Yang, Euijung

doi:10.31274/etd-180810-5470

Cited by 1 publication

(1 citation statement)

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“…Various authors found a direct influence on the acceptance of a technical system and trust on the decrease of frustration ( Giuliani et al, 2015 ; Yang, 2016 ; Abd et al, 2017 ). It was found that the sense of dominance was low when frustration was high in a task with high attentional demands ( Weidemann and Rußwinkel, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

The Role of Frustration in Human–Robot Interaction – What Is Needed for a Successful Collaboration?

Weidemann

Rußwinkel

2021

Front. Psychol.

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To realize a successful and collaborative interaction between human and robots remains a big challenge. Emotional reactions of the user provide crucial information for a successful interaction. These reactions carry key factors to prevent errors and fatal bidirectional misunderstanding. In cases where human–machine interaction does not proceed as expected, negative emotions, like frustration, can arise. Therefore, it is important to identify frustration in a human–machine interaction and to investigate its impact on other influencing factors such as dominance, sense of control and task performance. This paper presents a study that investigates a close cooperative work situation between human and robot, and explore the influence frustration has on the interaction. The task for the participants was to hand over colored balls to two different robot systems (an anthropomorphic robot and a robotic arm). The robot systems had to throw the balls into appropriate baskets. The coordination between human and robot was controlled by various gestures and words by means of trial and error. Participants were divided into two groups, a frustration- (FRUST) and a no frustration- (NOFRUST) group. Frustration was induced by the behavior of the robotic systems which made errors during the ball handover. Subjective and objective methods were used. The sample size of participants was N = 30 and the study was conducted in a between-subject design. Results show clear differences in perceived frustration in the two condition groups and different behavioral interactions were shown by the participants. Furthermore, frustration has a negative influence on interaction factors such as dominance and sense of control. The study provides important information concerning the influence of frustration on human–robot interaction (HRI) for the requirements of a successful, natural, and social HRI. The results (qualitative and quantitative) are discussed in favor of how a successful und effortless interaction between human and robot can be realized and what relevant factors, like appearance of the robot and influence of frustration on sense of control, have to be regarded.

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Section: Introductionmentioning

confidence: 99%