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Robots and other autonomous agents are well-positioned in the research discourse to support the care of people with challenges such as physical and/or cognitive disabilities. However, designing these robots can be complex as it involves considering a wide range of factors (e.g., individual needs, physical environment, technology capabilities, digital literacy), stakeholders (e.g., care recipients, formal and informal caregivers, technology developers), and contexts (e.g., hospitals, nursing homes, outpatient care facilities, private homes). The challenges are in gaining design insights for this unique use case and translating this knowledge into actionable, generalizable guidelines for other designers. This one-day workshop seeks to bring together researchers with diverse expertise and experience across academia, healthcare, and industry, spanning perspectives from multiple disciplines, including design, robotics, and human-computer interaction, with the primary goal being a consensus on best practices for generating and operationalizing design knowledge for robotic systems for care settings. 

Novel end-user programming (EUP) tools enable on-the-fly (i.e., spontaneous, easy, and rapid) creation of interactions with robotic systems. These tools are expected to empower users in determining system behavior, although very little is understood about how end users perceive, experience, and use these systems. In this paper, we seek to address this gap by investigating end-user experience with on-the-fly robot EUP. We trained 21 end users to use an existing on-the-fly EUP tool, asked them to create robot interactions for four scenarios, and assessed their overall experience. Our findings provide insight into how these systems should be designed to better support end-user experience with on-the-fly EUP, focusing on user interaction with an automatic program synthesizer that resolves imprecise user input, the use of multimodal inputs to express user intent, and the general process of programming a robot. 

Collaborative robots (cobots) are increasingly utilized within the manufacturing industry. However, despite the promise of collaboration and easier programming when compared to traditional industrial robots, cobots introduce new interaction paradigms that require more thought about the environment and distribution of tasks to fully realize their collaboration capabilities. Due to these additional requirements, these collaboration capabilities are underutilized in current manufacturing. Therefore, to make cobots more accessible and easy to use, new systems need to be developed that support users during interaction. In this research, we propose a set of tools that target cobot use for multiple groups of individuals that use them, to better support users and simplify cobot collaboration. 

Authored robotics applications have a diverse set of requirements for their authoring interfaces, being dependent on the underlying architecture of the program, the capabilities of the programmers and engineers using them, and the capabilities of the robot. Visual programming approaches have long been favored for both novice-level accessibility and clear graphical representations, but current tools are limited in their customizability and ability to be integrated holistically into larger design interfaces. OpenVP attempts to address this by providing a highly configurable and customizable component library that can be integrated easily into other modern web-based applications. 

Robots are ubiquitous in small-to-large-scale manufacturers. While collaborative robots (cobots) have significant potential in these settings due to their flexibility and ease of use, proper integration is critical to realize their full potential. Specifically, cobots need to be integrated in ways that utilize their strengths, improve manufacturing performance, and facilitate use in concert with human workers. Efective integration requires careful consideration and the knowledge of roboticists, manufacturing engineers, and business administrators. We propose an approach involving the stages of planning, analysis, development, and presentation, to inform manufacturers about cobot integration within their facilities prior to the integration process. We contextualize our approach in a case study with an SME collaborator and discuss insights learned. 

Large-language models (LLMs) hold significant promise in improving human-robot interaction, offering advanced conversational skills and versatility in managing diverse, open-ended user requests in various tasks and domains. Despite the potential to transform human-robot interaction, very little is known about the distinctive design requirements for utilizing LLMs in robots, which may differ from text and voice interaction and vary by task and context. To better understand these requirements, we conducted a user study (n = 32) comparing an LLM-powered social robot against text- and voice-based agents, analyzing task-based requirements in conversational tasks, including choose, generate, execute, and negotiate. Our findings show that LLM-powered robots elevate expectations for sophisticated non-verbal cues and excel in connection-building and deliberation, but fall short in logical communication and may induce anxiety. We provide design implications both for robots integrating LLMs and for fine-tuning LLMs for use with robots. 

End-user development (EUD) represents a key step towards making robotics accessible for experts and non-experts alike. Within academia, researchers investigate novel ways that EUD tools can capture, represent, visualize, analyze, and test developer intent. At the same time, industry researchers increasingly build and ship programming tools that enable customers to interact with their robots. However, despite this growing interest, the role of EUD within HRI is not well defined. EUD struggles to situate itself within a growing array of alternative approaches to application development, such as robot learning and teleoperation. EUD further struggles due to the wide range of individuals who can be considered end users, such as independent third-party application developers, consumers, hobbyists, or even employees of the robot manufacturer. Key questions remain such as how EUD is justified over alternate approaches to application development, which contexts EUD is most suited for, who the target users of an EUD system are, and where interaction between a human and a robot takes place, amongst many other questions. We seek to address these challenges and questions by organizing the frst End-User Development for Human-Robot Interaction (EUD4HRI) workshop at the 2024 International Conference of Human-Robot Interaction. The workshop will bring together researchers with a wide range of expertise across academia and industry, spanning perspectives from multiple subfields of robotics, with the primary goal being a consensus of perspectives about the role that EUD must play within human-robot interaction. 

We argue for the use of Petri nets as a modeling language for the iterative development process of interactive robotic systems. Petri nets, particularly Timed Colored Petri nets (TCPNs), have the potential to unify various phases of the development process-design, specification, simulation, validation, implementation, and deployment. We additionally discuss future directions for creating a domain-specific variant of TCPNs tailored specifically for HRI systems development. 

As service robots become more capable of autonomous behaviors, it becomes increasingly important to consider how people will be able to communicate with a robot about what task it should perform and how to do the task. There has been a rise in attention to end-user development (EUD), where researchers create interfaces that enable non-roboticist end users to script tasks for autonomous robots to perform. Currently, state-of-the-art interfaces are largely constrained, often through simplified domains or restrictive end-user interaction. Motivated by our past qualitative design work exploring how to integrate a care robot in an assisted living community, we discuss challenges of EUD in this complex domain. One set of challenges stems from different user-facing representations, e.g., certain tasks may lend themselves better to a rule-based trigger-action representations, whereas other tasks may be easier to specify via a sequence of actions. The other stems from considering the needs of multiple stakeholders, e.g., caregivers and residents of the facility may all create tasks for the robot, but the robot may not be able to share information about all tasks with all residents due to privacy concerns. We present scenarios that illustrate these challenges and also discuss possible solutions. 

We present a participatory design method to design human-robot interactions with older adults and its application through a case study of designing an assistive robot for a senior living facility. The method, called Situated Participatory Design (sPD), was designed considering the challenges of working with older adults and involves three phases that enable designing and testing use scenarios through realistic, iterative interactions with the robot. In design sessions with nine residents and three caregivers, we uncovered a number of insights about sPD that help us understand its benefits and limitations. For example, we observed how designs evolved through iterative interactions and how early exposure to the robot helped participants consider using the robot in their daily life. With sPD, we aim to help future researchers to increase and deepen the participation of older adults in designing assistive technologies.