Modeling Group Dynamics for Personalized Robot-Mediated Interactions

The field of human-human-robot interaction (HHRI) uses social robots to positively influence how humans interact with each other. This objective requires models of human understanding that consider multiple humans in an interaction as a collective entity and represent the group dynamics that exist within it. Understanding group dynamics is important because these can influence the behaviors, attitudes, and opinions of each individual within the group, as well as the group as a whole. Such an understanding is also useful when personalizing an interaction between a robot and the humans in its environment, where a group-level model can facilitate the design of robot behaviors that are tailored to a given group, the dynamics that exist within it, and the specific needs and preferences of the individual interactants. In this paper, we highlight the need for group-level models of human understanding in human-human-robot interaction research and how these can be useful in developing personalization techniques. We survey existing models of group dynamics and categorize them into models of social dominance, affect, social cohesion, and conflict resolution. We highlight the important features these models utilize, evaluate their potential to capture interpersonal aspects of a social interaction, and highlight their value for personalization techniques. Finally, we identify directions for future work, and make a case for models of relational affect as an approach that can better capture group-level understanding of human-human interactions and be useful in personalizing human-human-robot interactions

"How Did They Come Across?" Lessons Learned from Continuous Affective Ratings

Social distance, or perception of the other, is recognized as a dynamic dimension of an interaction, but yet to be widely explored or understood. Through CORAE, a novel web-based open-source tool for COntinuous Retrospective Affect Evaluation, we collected retrospective ratings of interpersonal perceptions between 12 participant dyads. In this work, we explore how different aspects of these interactions reflect on the ratings collected, through a discourse analysis of individual and social behavior of the interactants. We found that different events observed in the ratings can be mapped to complex interaction phenomena, shedding light on relevant interaction features that may play a role in interpersonal understanding and grounding. This paves the way for better, more seamless human-robot interactions, where affect is interpreted as highly dynamic and contingent on interaction history.Comment: arXiv admin note: substantial text overlap with arXiv:2306.1662

CORAE: A Tool for Intuitive and Continuous Retrospective Evaluation of Interactions

This paper introduces CORAE, a novel web-based open-source tool for COntinuous Retrospective Affect Evaluation, designed to capture continuous affect data about interpersonal perceptions in dyadic interactions. Grounded in behavioral ecology perspectives of emotion, this approach replaces valence as the relevant rating dimension with approach and withdrawal, reflecting the degree to which behavior is perceived as increasing or decreasing social distance. We conducted a study to experimentally validate the efficacy of our platform with 24 participants. The tool's effectiveness was tested in the context of dyadic negotiation, revealing insights about how interpersonal dynamics evolve over time. We find that the continuous affect rating method is consistent with individuals' perception of the overall interaction. This paper contributes to the growing body of research on affective computing and offers a valuable tool for researchers interested in investigating the temporal dynamics of affect and emotion in social interactions

Adaptive framework for emotional engagement in child-robot interactions for autism interventions

Socially assistive robots have been used extensively in designing therapy interventions for children on the autism spectrum. One of the major challenges facing this field is the difficulty in sustaining the child\u27s engagement in a designed activity for longitudinal studies once the novelty of the robot wears off. Another major challenge is the design of intervention strategies that can be adapted to suit the specific needs of every child. This paper presents a novel adaptive framework that addresses both these problems by implementing intervention methods that are tailored to each individual child

Spinach powder as soil conditioner enhances physiochemical properties of soil and growth characteristics of Solanum melongena

Purpose (i) To evaluate the efficacy of spinach in dry powdered and liquid form as a sustainable substitute for chemical fertilizers; (ii) To analyze and compare the morphological and yield-related parameters of Solanum melongena plants using spinach powder and compost as compared to the control treatment.Method In a pot experiment, Solanum melongena seeds were sowed in soil mixed with spinach powder and compost while the control pots were without any amendment to the soil. The spinach -amended soil, compost-amended soil, and control soil sample were compared in terms physiochemical characteristics like pH , EC ,TDS, organic matter , nutrients i.e. nitrogen , phosphorus, potassium ,calcium ,magnesium and heavy metals. While, plant morphological traits plant height, root length, numbers of flowers and fruits were recorded.Results The pH of spinach-amended soil was slightly alkaline before plantation as compared to control soil. The nitrogen, phosphorus, and potassium content in spinach dry powder was 15%, 36% and 49%, respectively. The organic carbon content was 56% with moderate amount of micronutrients like calcium, magnesium and iron. Spinach powder-amended soil significantly improved the plant morphological characteristics like stem height, root length and able to produce more flowers and mature fruits as compared to compost-amended soil and control soil.Conclusion The use of spinach in powder and liquid concoction was a suitable alternative to chemical fertilizers. It was able to deliver all major macro- and micronutrients to soil thus improving the fertility and has significant impact on plant growth and yield

Autism in the Gulf States: Why social robotics is the way forward

In this paper, we assess the current situation in the Gulf States with respect to autism awareness and diagnostic facilities, and emphasize the need for epidemiology studies in light of prevalence statistics available for the Gulf region. We then inspect social robotics as a possible therapeutic tool, now popularly used in the western countries, to design intervention techniques in order to tackle the increasing rate of autism occurrence in the Gulf. We study effective robot design methodologies, and the measures that must be taken to improve the facilities in the said region.Scopu

Culture as a driver for the design of social robots for Autism spectrum disorder interventions in the Middle East

In this paper, we discuss the prevalence of Autism Spectrum Disorder (ASD) in the Gulf region. We examine the importance of providing state-of-the-art ASD interventions, and highlight social robots as therapeutic tools that have gained popularity for their use in ASD therapy in the West. We also elaborate on the features of social robots that make them effective and describe how they can be used in such settings. We then emphasize the significance of taking cultural context into account in order to develop indigenous tools for ASD therapy, and explain the different ways in which social robots can be made culturally adaptive to maximize their potential impact on children with ASD. Springer International Publishing AG 2016.The work is supported by an NPRP grant from the Qatar National Research Fund under the grant No. NPRP 7-673-2-251. The statements made herein are solely the responsibility of the authors.Scopu

Robot-assisted socio-emotional intervention framework for children with Autism Spectrum disorder

This paper presents a novel robot-assisted intervention framework designed to target sensory processing and emotion regulation difficulties in children with autism spectrum disorder. Three types of systems are utilized to provide scalable robotic interactions with gesture-based and character-based socio-emotional expressions. The intervention framework includes (1) an emotional interaction and regulation game in mobile computing settings, (2) interactive robotic sessions with socio-emotional scenarios, and (3) gesture identification games to measure emotion processing and verbal skills in socio-emotional settings. This paper also presents preliminary results obtained from a pilot study conducted to evaluate the three interventions