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More than 1 billion people in the world are estimated to experience significant disability. These disabilities can impact people's ability to independently conduct activities of daily living, including ambulating, eating, dressing, taking care of personal hygiene, and more. Mobile and manipulator robots, which can move about human environments and physically interact with objects and people, have the potential to assist people with disabilities in activities of daily living. Although the vision of physically assistive robots has motivated research across subfields of robotics for decades, such robots have only recently become feasible in terms of capabilities, safety, and price. More and more research involves end-to-end robotic systems that interact with people with disabilities in real-world settings. In this article, we survey papers about physically assistive robots intended for people with disabilities from top conferences and journals in robotics, human–computer interactions, and accessible technology, to identify the general trends and research methodologies. We then dive into three specific research themes—interaction interfaces, levels of autonomy, and adaptation—and present frameworks for how these themes manifest across physically assistive robot research. We conclude with directions for future research. 

Demonstration is an effective end-user development paradigm for teaching robots how to perform new tasks. In this paper, we posit that demonstration is useful not only as a teaching tool, but also as a way to understand and assist end-user developers in thinking about a task at hand. As a first step toward gaining this understanding, we constructed a lightweight web interface to crowdsource step-by-step instructions of common household tasks, leveraging the imaginations and past experiences of potential end-user developers. As evidence of the utility of our interface, we deployed the interface on Amazon Mechanical Turk and collected 207 task traces that span 18 different task categories. We describe our vision for how these task traces can be operationalized as task models within end-user development tools and provide a roadmap for future work. 

Service robots for personal use in the home and the workplace require end-user development solutions for swiftly scripting robot tasks as the need arises. Many existing solutions preserve ease, efficiency, and convenience through simple programming interfaces or by restricting task complexity. Others facilitate meticulous task design but often do so at the expense of simplicity and efficiency. There is a need for robot programming solutions that reconcile the complexity of robotics with the on-the-fly goals of end-user development. In response to this need, we present a novel, multimodal, and on-the-fly development system, Tabula. Inspired by a formative design study with a prototype, Tabula leverages a combination of spoken language for specifying the core of a robot task and sketching for contextualizing the core. The result is that developers can script partial, sloppy versions of robot programs to be completed and refined by a program synthesizer. Lastly, we demonstrate our anticipated use cases of Tabula via a set of application scenarios. 

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. 

Socially interactive robots present numerous unique programming challenges for interaction developers. While modern authoring tools succeed at making the authoring experience approachable and convenient for developers from a wide variety of backgrounds, they are less successful at targeting assistance to developers based on the specific task or interaction being authored. We propose interaction templates, a data-driven solution for (1) matching in-progress robot programs to candidate task or interaction models and then (2) providing assistance to developers by using the matched models to generate modifications to in-progress programs. In this paper, we present the various dimensions that define first how interaction templates might be used, then how interaction templates may be represented, and finally how they might be collected. 

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. 

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.