Naomi T. Fitter’s research while affiliated with Oregon State University and other places

In early motor interventions from clinical rehabilitation to physical activity encouragement, one major challenge is maintaining child engagement and motivation. Robots show unique promise for addressing this challenge, but providing robots with new types of autonomous functionality is vital for promoting robot integration and usefulness in the clinic and home spaces. To provide needed autonomy capabilities for GoBot, our assistive robot for child-robot motion interventions, we propose a behavior tree framework. Within our framework, we build two trees: one manually designed based on expert knowledge of the child-robot interaction domain, and a second automatically synthesized and requiring minimal human input and time to construct. We tested each behavior tree with N = 11 children who interacted with GoBot during two behavior tree phases and a stationary-robot control phase. Our results show that both behavior tree phases tended to yield more child motion and significantly higher parent perception of child engagement, compared to the control phase. We showed that GoBot, equipped with our framework, has the potential to encourage movement and interaction in children, and that a synthesized tree can be competitive with a manually-designed tree. The products of this work can benefit researchers of behavior trees and child-robot interaction.

Young children with motor disabilities face barriers and delays to learning motor skills such as walking. Pediatric body-weight support harness systems (BWSHes) are a newer technology for helping young children to practice supported motor skills. Incorporating an assistive robot to mediate BWSH interventions can support further child motion and engagement, but almost no work to date has studied autonomous robot-mediated BWSH use. We conducted a six-month-long single-case study series with two participants to evaluate the effectiveness of an autonomous assistive robot in motivating the children to move and stay engaged while in the BWSH. We collected and analyzed objective movement data and self-reported parent survey data to determine how much the child moved and stayed engaged during sessions. Our results showed that both children displayed more movement while the assistive robot was active (relative to in prior no-robot periods). Parents also rated their children as more engaged while the assistive robot was present. An autonomous assistive robot may provide motivation for a child to move and stay engaged while using a pediatric rehabilitation aid such as a BWSH. The products of this work can benefit roboticists who work with children with disabilities and researchers who use pediatric rehabilitation technologies.

The rise in prevalence of AI-enabled technologies (from voice assistants to social robots) has not yet been accompanied by an analogous mastery of computer-mediated humor. Although humans often use jokes to repair interactions and navigate uncomfortable scenarios, social robots in similar roles typically fall short at reading the room and adapting behavior according to sensed social contexts and reactions. We pursued two studies to gain clearer evidence about adaptive robot joking's influence (compared to hardcoded repartee or no robot banter). The first study ( $N = 48$ , between-subjects design) examined in-person one-on-one human-robot interactions across the three conditions. The results indicated that adaptive repartee by robots tended to increase perceived warmth, competence, comfort, social closeness feelings, and humorousness, and that human behavioral responses varied significantly between conditions, with any repartee leading to significant gains over no repartee. The second study used an online video-based survey with a within-subjects design ( $N = 99$ ) to examine the same conditions. This follow-up effort showed significant gains in perceived competence and anthropomorphism for any type of repartee, although this banter also made the robot more discomforting. Our work can help practitioners who are interested in applying playful banter to enhance robot charm and success.

Despite sound being a promising modality of communication in robotics (possessing, for example, the ability to improve people’s perceptions of robots and help localize robotic systems in space), its facilitator, speakers, are a seldom-explored topic of study in robotics literature. To address this gap, we conducted three explorations into physical speaker design that identified what current robot speakers lack and potential remedies, low-level design improvements, and post hoc hardware additions. Further, we detail and explore the application of speakers on three different robotic platforms (including one industrial robot used for construction), the last evaluation of which involved an empirical study (N=21) that sought to better understand the implications associated with poor-quality speakers in a mock service robotics context. Our results suggest that greater internal cavity volume is a key strength in speaker design. We also observed greater effects of the presence (vs. absence) of a service robot voice compared to other factors. This work can inform the process of creating custom speakers for robots and augmenting current robotic systems with new speaker additions (whether commercial or custom, and across use contexts from construction to service). In particular, the work can help to guide roboticists who may be unfamiliar with nuanced audio engineering techniques and designers who seek to improve robotics platform standards with human interlocutors in mind.

As people live longer, the population of older adults in need of support continues to expand relative to the available workforce of caregivers, necessitating new solutions to supplement caregiver availability for the physical, cognitive, and social needs of older adults. Robotics and automation present strong possible solutions. Past solutions have typically supported short-term rehabilitation and aging in place, yet many older adults live in skilled nursing facilities (SNFs), a setting reached by relatively little research to date. In this paper, we examine the unique needs of staff and residents at SNFs, after which we begin an iterative design process of robot-mediated wellness activities for the SNF space. We worked closely with domain experts in exercise science and physical therapy for older adults and a local SNF to design and test a series of robot-mediated activity prototypes with residents, visitors, and staff. We found that while both residents and staff highly value physical activity, there are nuanced challenges associated with supporting resident activity (one important element of overall wellbeing). As a result, we considered and tested a wide range of intervention options from usual approaches (e.g., mirroring movements) to creative approaches (e.g., social engagement via lewd humor). Our final design insights can inform practitioners who wish to use robots to support resident wellbeing in SNFs.

Objective: Children worldwide are becoming increasingly inactive, leading to significant wellness challenges. Initial findings from our research team indicate that robots could potentially provide a more effective approach (compared to other age-appropriate toys) for encouraging physical activity in children. However, the basis of this past work relied on either interactions with groups of children (making it challenging to isolate specific factors that influenced activity levels) or a preliminary version of results of the present study (which centered on just a single more exploratory method for assessing child movement). Methods and Procedures: This paper delves into more controlled interactions involving a single robot and a child participant, while also considering observations over an extended period to mitigate the influence of novelty on the study outcomes. We discuss the outcomes of a two-month-long deployment, during which N = 8 participants engaged with our custom robot, GoBot, in weekly sessions. During each session, the children experienced three different conditions: a teleoperated robot mode, a semi-autonomous robot mode, and a control condition in which the robot was present but inactive. Results: Compared to our past related work, the results expanded our findings by confirming with greater clout (based on multiple data streams, including one more robust measure compared to the past related work) that children tended to be more physically active when the robot was active, and interestingly, there were no significant differences between the teleoperated and semi-autonomous modes in terms of our study measures. Conclusion: These insights can inform future applications of assistive robots in child motor interventions, including the guiding of appropriate levels of autonomy for these systems. Clinical Impact: This study demonstrates that incorporating robotic systems into play environments can boost physical activity in young children, indicating potential implementation in settings crafted to enhance children’s physical movement.