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We present FLEX-SDK: an open-source software development kit that allows creating a social robot from two simple tablet screens. FLEX-SDK involves tools for designing the robot face and its facial expressions, creating screens for input/output interactions, controlling the robot through a Wizard-of-Oz interface, and scripting autonomous interactions through a simple text-based programming interface. We demonstrate how this system can be used to replicate an interaction study and we present nine case studies involving controlled experiments, observational studies, participatory design sessions, and outreach activities in which our tools were used by researchers and participants to create and interact with social robots. We discuss common observations and lessons learned from these case studies. Our work demonstrates the potential of FLEX-SDK to lower the barrier to entry for Human-Robot Interaction research. 

Integrating cultural responsiveness into the educational setting is essential to the success of multilingual students. As social robots present the potential to support multilingual children, it is imperative that the design of social robot embodiments and interactions are culturally responsive. This paper summarizes the current literature on educational robots in culturally diverse settings. We argue the use of the Culturally Localized User Experience (CLUE) Framework is essential to ensure cultural responsiveness in HRI design. We present three case studies illustrating the CLUE framework as a social robot design approach. The results of these studies suggest co-design provides multicultural learners an accessible, nonverbal context through which to provide design requirements and preferences. Furthermore, we demonstrate the importance of key stakeholders (students, parents, and teachers) as essential to ensure a culturally responsive robot. Finally, we reflect on our own work with culturally and linguistically diverse learners and propose three guiding principles for successfully engaging diverse learners as valuable cultural informants to ensure the future success of educational robots. 

Adolescents isolated at home during the COVID19 pandemic lockdown are more likely to feel lonely and in need of social connection. Social robots may provide a much needed social interaction without the risk of contracting an infection. In this paper, we detail our co-design process used to engage adolescents in the design of a social robot prototype intended to broadly support their mental health. Data gathered from our four week design study of nine remote sessions and interviews with 16 adolescents suggested the following design requirements for a home robot: (1) be able to enact a set of roles including a coach, companion, and confidant; (2) amplify human-to-human connection by supporting peer relationships; (3) account for data privacy and device ownership. Design materials are available in open-access, contributing to best practices for the field of Human-Robot Interaction. 

The social robotics market is appealing yet challenging. Though social robots are built few remain on the market for long. Many reasons account for their short lifespan with costs and context-specificity ranking high amount them. In this work, we designed, fabricated, and developed FLEXI, a social robot embodiment kit that enabled unlimited customization, making it applicable for a broad range of use cases. The hardware and software of FLEXI were entirely developed by this research team from scratch. FLEXI includes a rich set of materials and attachment pieces to allow for a diverse range of hardware customizations that ensure the embodiment is appropriate for specific customer/researcher projects. It also includes an open-source end-user programming interface to lower the barrier of robotics access to interdisciplinary teams that populate the field of Human-Robot Interaction. We present an iterative development of this cost-effective kit through the lenses of case studies, conceptual research, and soft deployment of FLEXI in three application scenarios: community-support, mental health, and education. Additionally, we provide in open-access the full list of materials and a tutorial to fabricate FLEXI, making it accessible to any maker space, research lab, or workshop space interested in working with or learning about social robots. 

Despite promises about the near-term potential of social robots to share our daily lives, they remain unable to form autonomous, lasting, and engaging relationships with humans. Many companies are deploying social robots into the consumer and commercial market; however, both the companies and their products are relatively short lived for many reasons. For example, current social robots succeed in interacting with humans only within controlled environments, such as research labs, and for short time periods since longer interactions tend to provoke user disengagement. We interviewed 13 roboticists from robot manufacturing companies and research labs to delve deeper into the design process for social robots and unearth the many challenges robot creators face. Our research questions were: 1) What are the different design processes for creating social robots? 2) How are users involved in the design of social robots? 3) How are teams of robot creators constituted? Our qualitative investigation showed that varied design practices are applied when creating social robots but no consensus exists about an optimal or standard one. Results revealed that users have different degrees of involvement in the robot creation process, from no involvement to being a central part of robot development. Results also uncovered the need for multidisciplinary and international teams to work together to create robots. Drawing upon these insights, we identified implications for the field of Human-Robot Interaction that can shape the creation of best practices for social robot design. 

Social robots have been used to support mental health. In this work, we explored their potential as community-based tools. Visualizing mood data patterns of a community with a social robot might help the community raise awareness about the emotions people feel and affecting factors from life events. This could potentially lead to adaptation of suitable coping skills enhancing the sense of belonging and support among community members. We present preliminary findings and ongoing plans for this human-robot interaction (HRI) research work on data visualizations supporting community mental health. In a two-day study, twelve participants recruited from a university community engaged with a robot displaying mood data. Given the feedback from the study, we improved the data visualization in the robot to increase accessibility, universality, and usefulness of such visualizations. In the future, we plan on conducting studies with this improved version and deploying a social robot for a community setting. 

Social robots may be a promising social-emotional tool to support adolescent mental health. However, how might interactions with a social robot in a school setting be perceived by teens? From previous studies, we gathered qualitative data suggesting a design tension between teens wanting both public and private interactions with our social robot, EMAR. In our current study, we explored interactions between a social robot and a small group of adolescents in a semi-private, school library setting. We found: (1) Some teens preferred to have a friend present while they engaged with the social robot, (2) Teens found comfort in being physically visible, but audibly private during interactions, and finally (3) Strangers in the school environment were not disruptive of the teens' robot interactions, but unexpectedly friends were. After presenting these findings, we briefly discuss how these qualitative data can be situated and our next steps for further exploration. 

Virtual reality (VR) offers potential as a collaborative tool for both technology design and human-robot interaction. We utilized a participatory, human-centered design (HCD) methodology to develop a collaborative, asymmetric VR game to explore teens’ perceptions of, and interactions with, social robots. Our paper illustrates three stages of our design process; ideation, prototyping, and usability testing with users. Through these stages we identified important design requirements for our mid-fidelity environment. We then describe findings from our pilot test of the mid-fidelity VR game with teens. Due to the unique asymmetric virtual reality design, we observed successful collaborations, and interesting collaboration styles across teens. This study highlights the potential for asymmetric VR as a collaborative design tool as well as an appropriate medium for successful teen-to-teen collaboration. 

Background: There are 4.9 million English Language Learners (ELLs) in the United States. Only 2% of educators are trained to support these vulnerable students. Social robots show promise for language acquisition and may provide valuable support for students, especially as we return to needing smaller classes due to COVID-19. While cultural responsiveness increases gains for ELLs, little is known about the design of culturally responsive child–robot interactions. Method: Therefore, using a participatory design approach, we conducted an exploratory study with 24 Spanish-speaking ELLs at a Pacific Northwest elementary school. As cultural informants, students participated in a 15-min, robot-led, small group story discussion followed by a post-interaction feedback session. We then conducted reflexive critiques with six ELL teachers who reviewed the group interactions to provide further interpretation on design feature possibilities and potential interactions with the robot. Results: Students found the social robot engaging, but many were hesitant to converse with the robot. During post-interaction dialogue students articulated the specific ways in which the social robot appearance and behavior could be modified to help them feel more comfortable. Teachers postulated that the social robot could be designed to engage students in peer-to-peer conversations. Teachers also recognized the ELLs verbosity when discussing their experiences with the robot and suggested such interactions could stimulate responsiveness from students. Conclusion: Cultural responsiveness is a key component to successful education in ELLs. However, integrating appropriate, cultural responsiveness into robot interactions may require participants as cultural informants to ensure the robot behaviors and interactions are situated in that educational community. Utilizing a participatory approach to engage ELLs in design decisions for social robots is a promising way to gather culturally responsive requirements to inform successful child–robot interactions.