SAR4SLPs: An Asynchronous Survey of Speech-Language Pathologists' Perspectives on Socially Assistive Robots

Socially Assistive Robots (SARs) offer unique opportunities within speech language pathology (SLP) education and practice by supporting interactive interventions for children with communication disorders. This paper explores the implementation of SAR4SLPs (Socially Assistive Robots for Speech-Language Pathologists) to investigate aspects such as engagement, therapeutic strategy discipline, and consistent intervention support. We assessed the current application of technology to clinical and educational settings, especially with respect to how SLPs might use SAR in their therapeutic work. An asynchronous remote community (ARC) collaborated with a cohort of practicing SLPs to consider the feasibility, potential effectiveness, and anticipated challenges with implementing SARs in day-to-day interventions and as practice facilitators. We focus in particular on the expressive functionality of SARs, modeling a foundational strategy that SLPs employ across various intervention targets. This paper highlights clinician-driven insights and design implications for developing SARs that support specific treatment goals through collaborative and iterative design.

Design Activity for Robot Faces: Evaluating Child Responses To Expressive Faces

Facial expressiveness plays a crucial role in a robot's ability to engage and interact with children. Prior research has shown that expressive robots can enhance child engagement during human-robot interactions. However, many robots used in therapy settings feature non-personalized, static faces designed with traditional facial feature considerations, which can limit the depth of interactions and emotional connections. Digital faces offer opportunities for personalization, yet the current landscape of robot face design lacks a dynamic, user-centered approach. Specifically, there is a significant research gap in designing robot faces based on child preferences. Instead, most robots in child-focused therapy spaces are developed from an adult-centric perspective. We present a novel study investigating the influence of child-drawn digital faces in child-robot interactions. This approach focuses on a design activity with children instructed to draw their own custom robot faces. We compare the perceptions of social intelligence (PSI) of two implementations: a generic digital face and a robot face, personalized using the user's drawn robot faces. The results of this study show the perceived social intelligence of a child-drawn robot was significantly higher compared to a generic face.

Through the Clutter: Exploring the Impact of Complex Environments on the Legibility of Robot Motion

The environments in which the collaboration of a robot would be the most helpful to a person are frequently uncontrolled and cluttered with many objects present. Legible robot arm motion is crucial in tasks like these in order to avoid possible collisions, improve the workflow and help ensure the safety of the person. Prior work in this area, however, focuses on solutions that are tested only in uncluttered environments and there are not many results taken from cluttered environments. In this research we present a measure for clutteredness based on an entropic measure of the environment, and a novel motion planner based on potential fields. Both our measures and the planner were tested in a cluttered environment meant to represent a more typical tool sorting task for which the person would collaborate with a robot. The in-person validation study with Baxter robots shows a significant improvement in legibility of our proposed legible motion planner compared to the current state-of-the-art legible motion planner in cluttered environments. Further, the results show a significant difference in the performance of the planners in cluttered and uncluttered environments, and the need to further explore legible motion in cluttered environments. We argue that the inconsistency of our results in cluttered environments with those obtained from uncluttered environments points out several important issues with the current research performed in the area of legible motion planners.