Conveying Emotions by Touch to the Nao Robot: A User Experience Perspective

Alenljung, Beatrice; Andreasson, Rebecca; Lowe, Robert; Billing, Erik; Lindblom, Jessica

doi:10.3390/mti2040082

Cited by 15 publications

(7 citation statements)

References 66 publications

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“…Users would like NAO to be more emotionally expressive, responsive, and have a natural voice and gesturing (Anastasiou et al, 2013;Ahmad et al, 2017). Authors used a variety of questionnaires to evaluate NAO's characteristics and performance based on: anthropomorphism (Zlotowski et al, 2014;Kraus et al, 2016), user experience (Alenljung et al, 2018;Olde Keizer et al, 2019), user acceptability (Ahmad et al, 2017), robot personality (Liles and Beer, 2015;Peters et al, 2017;Kraus et al, 2018), robot behaviors (Pan et al, 2013;Njeri et al, 2016;Rossi et al, 2019), user expectations and evaluation (Anastasiou et al, 2013;Henkel et al, 2019), and perceived trustworthiness (Jessup et al, 2019). Table 4 presents common questionnaires that are used in evaluating human-oriented perception of NAO.…”

Section: The Human Perception Of Naomentioning

confidence: 99%

“…When touching the robot, positive experiences with NAO were characterized as fun and engaging, while negative experiences were described to be odd and unsafe due to its small size and hard surface (Alenljung et al, 2018). Comparing low and high interactivity, Tozadore et al (2017) found that children enjoy their experience with the high interactive NAO that use a warm greeting and recognizes their names.…”

Section: The Human Perception Of Naomentioning

confidence: 99%

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10 Years of Human-NAO Interaction Research: A Scoping Review

et al. 2021

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The evolving field of human-robot interaction (HRI) necessitates that we better understand how social robots operate and interact with humans. This scoping review provides an overview of about 300 research works focusing on the use of the NAO robot from 2010 to 2020. This study presents one of the most extensive and inclusive pieces of evidence on the deployment of the humanoid NAO robot and its global reach. Unlike most reviews, we provide both qualitative and quantitative results regarding how NAO is being used and what has been achieved so far. We analyzed a wide range of theoretical, empirical, and technical contributions that provide multidimensional insights, such as general trends in terms of application, the robot capabilities, its input and output modalities of communication, and the human-robot interaction experiments that featured NAO (e.g. number and roles of participants, design, and the length of interaction). Lastly, we derive from the review some research gaps in current state-of-the-art and provide suggestions for the design of the next generation of social robots.

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Section: The Human Perception Of Naomentioning

confidence: 99%

Section: The Human Perception Of Naomentioning

confidence: 99%

10 Years of Human-NAO Interaction Research: A Scoping Review

et al. 2021

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“…Factors such as affective touch interaction, touch parts (e.g., head or hand) [18], strength (perceived pain) [19], and frequency would influence appropriate reaction timing. Past studies have shown that these touch characteristics would change based on conveyed emotions via touches [20][21][22]. In this study, we used a gentle touch on the left shoulder.…”

Section: Factors That Possibly Change Impressionsmentioning

confidence: 99%

From When to When: Evaluating Naturalness of Reaction Time via Viewing Turn around Behaviors

et al. 2021

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This paper addresses the effects of visual reaction times of a turn around behavior toward touch stimulus in the context of perceived naturalness. People essentially prefer a quick and natural reaction time to interaction partners, but appropriate reaction times will change due to the kinds of partners, e.g., humans, computers, and robots. In this study, we investigate two visual reaction times in touch interaction: the time length from the touched timing to the start of a reaction behavior, and the time length of the reaction behavior. We also investigated appropriate reaction times for different beings: three robots (Sota, Nao and Pepper) and humans (male and female). We conducted a web-survey based experiment to investigate natural reaction times for robots and humans, and the results concluded that the best combinations of both reaction times are different between each robot (i.e., among Sota, Nao and Pepper) and the humans (i.e., between male and female). We also compared the effect of using the best combinations for each robot and human to prove the importance of using each appropriate reaction timing for each being. The results suggest that an appropriate reaction time combination investigated from the male model is not ideal for robots, and the combination investigated from the female model is a better choice for robots. Our study also suggests that calibrating parameters for individual robots’ behavior design would enable better performances than using parameters of robot behaviors based on observing human-human interaction, although such an approach is a typical method of robot behavior design.

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“…Due to the advancement of touch interaction-related research works, robots have also acquired the ability to express emotions through touch interactions. For example, a past study investigated how participants touch a robot when they express emotions to elucidate the relationships between the touched parts of the robot and the emotions expressed by people (Alenljung et al, 2018). Other past studies investigated the relationships between facial expressions and touch characteristics to express a robot's emotions and intimacy with their interacting partners (Zheng et al, 2019a;Zheng et al, 2019b).…”

Section: Introductionmentioning

confidence: 99%

Implementation and Evaluation of a Grip Behavior Model to Express Emotions for an Android Robot

et al. 2021

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In this study, we implemented a model with which a robot expressed such complex emotions as heartwarming (e.g., happy and sad) or horror (fear and surprise) by its touches and experimentally investigated the effectiveness of the modeled touch behaviors. Robots that can express emotions through touching behaviors increase their interaction capabilities with humans. Although past studies achieved ways to express emotions through a robot’s touch, such studies focused on expressing such basic emotions as happiness and sadness and downplayed these complex emotions. Such studies only proposed a model that expresses these emotions by touch behaviors without evaluations. Therefore, we conducted the experiment to evaluate the model with participants. In the experiment, they evaluated the perceived emotions and empathies from a robot’s touch while they watched a video stimulus with the robot. Our results showed that the touch timing before the climax received higher evaluations than touch timing after for both the scary and heartwarming videos.

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Conveying Emotions by Touch to the Nao Robot: A User Experience Perspective

Cited by 15 publications

References 66 publications

10 Years of Human-NAO Interaction Research: A Scoping Review

10 Years of Human-NAO Interaction Research: A Scoping Review

From When to When: Evaluating Naturalness of Reaction Time via Viewing Turn around Behaviors

Implementation and Evaluation of a Grip Behavior Model to Express Emotions for an Android Robot

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