Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

Chivarov, Nayden; Chikurtev, Denis; Chivarov, Stefan; Pleva, Matúš; Ondáš, Stanislav; Juhar, Jozef; Yovchev, Kaloyan

doi:10.31577/cai_2019_5_1210

Cited by 12 publications

(2 citation statements)

References 33 publications

(34 reference statements)

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“…The shortage of trained professionals and desire to age-in-place can be solved by social assistive robotics. While there exist assistive robotics [1] (e.g., intelligent walkers, wheelchair robots, manipulator arms and exoskeletons), they lack the social aspect as well as the affective component.…”

Section: Introductionmentioning

confidence: 99%

Emotion Analysis in Human–Robot Interaction

et al. 2020

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This paper connects two large research areas, namely sentiment analysis and human–robot interaction. Emotion analysis, as a subfield of sentiment analysis, explores text data and, based on the characteristics of the text and generally known emotional models, evaluates what emotion is presented in it. The analysis of emotions in the human–robot interaction aims to evaluate the emotional state of the human being and on this basis to decide how the robot should adapt its behavior to the human being. There are several approaches and algorithms to detect emotions in the text data. We decided to apply a combined method of dictionary approach with machine learning algorithms. As a result of the ambiguity and subjectivity of labeling emotions, it was possible to assign more than one emotion to a sentence; thus, we were dealing with a multi-label problem. Based on the overview of the problem, we performed experiments with the Naive Bayes, Support Vector Machine and Neural Network classifiers. Results obtained from classification were subsequently used in human–robot experiments. Despise the lower accuracy of emotion classification, we proved the importance of expressing emotion gestures based on the words we speak.

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Section: Introductionmentioning

confidence: 99%

Emotion Analysis in Human–Robot Interaction

et al. 2020

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“…The majority of remote robot interaction research focuses on either how to communicate with a robot in a remote environment (Mackey et al, 2020;Sierra et al, 2019) or teleoperationhow to control the robot from a remote location or by using augmented reality (AR) or other simulated environments (Yanco et al, 2005;Qian et al, 2013;Nagy et al, 2015;Chiou et al, 2016;Chivarov et al, 2019;Xue et al, 2020). Some studies have looked at how to improve HRI outcomes by using the common ground principle to improve communication between humans and robots.…”

Section: Related Workmentioning

confidence: 99%

Remote HRI: a Methodology for Maintaining COVID-19 Physical Distancing and Human Interaction Requirements in HRI Studies

Gittens

2021

Inf Syst Front

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Observing how humans and robots interact is an integral part of understanding how they can effectively coexist. This ability to undertake these observations was taken for granted before the COVID-19 pandemic restricted the possibilities of performing HRI study-based interactions. We explore the problem of how HRI research can occur in a setting where physical separation is the most reliable way of preventing disease transmission. We present the results of an exploratory experiment that suggests Remote-HRI (R-HRI) studies may be a viable alternative to traditional face-to-face HRI studies. An R-HRI study minimizes or eliminates in-person interaction between the experimenter and the participant and implements a new protocol for interacting with the robot to minimize physical contact. Our results showed that participants interacting with the robot remotely experienced a higher cognitive workload, which may be due to minor cultural and technical factors. Importantly, however, we also found that whether participants interacted with the robot in-person (but socially distanced) or remotely over a network, their experience, perception of, and attitude towards the robot were unaffected.

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