A Reactive Competitive Emotion Selection System

We present a reactive emotion selection system designed to be used in a robot that needs to respond autonomously to relevant events. A variety of emotion selection models based on “cognitive appraisal” theories exist, but the complexity of the concepts used by most of these models limits their use in robotics. Robots have physical constrains that condition their understanding of the world and limit their capacity to built the complex concepts needed for such models. The system presented in this paper was conceived to respond to “disturbances” detected in the environment through a stream of images, and use this low-level information to update emotion intensities. They are increased when specific patterns, based on Tomkins’ affect theory, are detected or reduced when it is not. This system could also be used as part of (or as first step in the incremental design of) a more cognitively complex emotional system for autonomous robots

Explorations in engagement for humans and robots

This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.Comment: 31 pages, 5 figures, 3 table

Prosody based emotion recognition for MEXI

Abstract — This paper describes the emotion recognition from natural speech as realized for the robot head MEXI. We use a fuzzy logic approach for analysis of prosody in natural speech. Since MEXI often communicates with well known persons but also with unknown humans, for instance at exhibitions, we realized a speaker dependent mode as well as a speaker independent mode in our prosody based emotion recognition. A key point of our approach is that it automatically selects the most significant features from a set of twenty analyzed features based on a training database of speech samples. This is important according to our results, since the set of significant features differs considerably between the distinguished emotions. With our approach we reach average recognition rates of 84 % in speaker dependent mode and 60 % in speaker independent mode. Index Terms — Emotion recognition, prosody, fuzzy rules, robot hea

Measuring Engagement in Robot-Assisted Autism Therapy: A Cross-Cultural Study

During occupational therapy for children with autism, it is often necessary to elicit and maintain engagement for the children to benefit from the session. Recently, social robots have been used for this; however, existing robots lack the ability to autonomously recognize the children’s level of engagement, which is necessary when choosing an optimal interaction strategy. Progress in automated engagement reading has been impeded in part due to a lack of studies on child-robot engagement in autism therapy. While it is well known that there are large individual differences in autism, little is known about how these vary across cultures. To this end, we analyzed the engagement of children (age 3–13) from two different cultural backgrounds: Asia (Japan, n = 17) and Eastern Europe (Serbia, n = 19). The children participated in a 25 min therapy session during which we studied the relationship between the children’s behavioral engagement (task-driven) and different facets of affective engagement (valence and arousal). Although our results indicate that there are statistically significant differences in engagement displays in the two groups, it is difficult to make any causal claims about these differences due to the large variation in age and behavioral severity of the children in the study. However, our exploratory analysis reveals important associations between target engagement and perceived levels of valence and arousal, indicating that these can be used as a proxy for the children’s engagement during the therapy. We provide suggestions on how this can be leveraged to optimize social robots for autism therapy, while taking into account cultural differences.MEXT Grant-in-Aid for Young Scientists B (grant no. 16763279)Chubu University Grant I (grant no. 27IS04I (Japan))European Union. HORIZON 2020 (grant agreement no. 701236 (ENGAGEME))European Commission. Framework Programme for Research and Innovation. Marie Sklodowska-Curie Actions (Individual Fellowship)European Commission. Framework Programme for Research and Innovation. Marie Sklodowska-Curie Actions (grant agreement no. 688835 (DE-ENIGMA)

Measuring Engagement in Robot-Assisted Autism Therapy: A Cross-Cultural Study

During occupational therapy for children with autism, it is often necessary to elicit and maintain engagement for the children to benefit from the session. Recently, social robots have been used for this; however, existing robots lack the ability to autonomously recognize the children’s level of engagement, which is necessary when choosing an optimal interaction strategy. Progress in automated engagement reading has been impeded in part due to a lack of studies on child-robot engagement in autism therapy. While it is well known that there are large individual differences in autism, little is known about how these vary across cultures. To this end, we analyzed the engagement of children (age 3–13) from two different cultural backgrounds: Asia (Japan, n = 17) and Eastern Europe (Serbia, n = 19). The children participated in a 25 min therapy session during which we studied the relationship between the children’s behavioral engagement (task-driven) and different facets of affective engagement (valence and arousal). Although our results indicate that there are statistically significant differences in engagement displays in the two groups, it is difficult to make any causal claims about these differences due to the large variation in age and behavioral severity of the children in the study. However, our exploratory analysis reveals important associations between target engagement and perceived levels of valence and arousal, indicating that these can be used as a proxy for the children’s engagement during the therapy. We provide suggestions on how this can be leveraged to optimize social robots for autism therapy, while taking into account cultural differences.MEXT Grant-in-Aid for Young Scientists B (grant no. 16763279)Chubu University Grant I (grant no. 27IS04I (Japan))European Union. HORIZON 2020 (grant agreement no. 701236 (ENGAGEME))European Commission. Framework Programme for Research and Innovation. Marie Sklodowska-Curie Actions (Individual Fellowship)European Commission. Framework Programme for Research and Innovation. Marie Sklodowska-Curie Actions (grant agreement no. 688835 (DE-ENIGMA)

Mitigating emotional risks in human-social robot interactions through virtual interactive environment indication

Humans often unconsciously perceive social robots involved in their lives as partners rather than mere tools, imbuing them with qualities of companionship. This anthropomorphization can lead to a spectrum of emotional risks, such as deception, disappointment, and reverse manipulation, that existing approaches struggle to address effectively. In this paper, we argue that a Virtual Interactive Environment (VIE) exists between humans and social robots, which plays a crucial role and demands necessary consideration and clarification in order to mitigate potential emotional risks. By analyzing the relational nature of human-social robot interaction, we discuss the connotation of such a virtual interactive environment that is similar to the emotional states aroused when reading novels. Building on this comprehension, we further demonstrate that manufacturers should carry out comprehensive Virtual Interactive Environment Indication (VIEI) measures during human-social robot interaction with a stricter sense of responsibility when applying social robots. Finally, we contemplate the potential contributions of virtual interactive environment indication to existing robot ethics guidelines