Jason R. Wilson

Researchers and designers of social robots often approach robot control system design from a single perspective; such as designing autonomous robots, teleoperated robots, or robots programmed by an end-user. While each design approach presents a tradeoff between some advantages and limitations, there is an opportunity to integrate these approaches where people benefit from the best-fit approach for their use case. In this work, we propose integrating these seemingly distinct robot control approaches to uncover a common data representation of social actions defining social expression by a robot. We demonstrate the value of integrating an authoring system, teleoperation interface, and robot planning system by integrating instances of these systems for robot storytelling. By relying on an integrated system, domain experts can define behaviors through end-user interfaces that teleoperators and autonomous robot programmers can use directly thus providing a cohesive expert-driven robot system.

In this paper, we discuss the opportunities and challenges of teaching a human-robot interaction course at an undergraduate liberal arts college. We provide a sample syllabus adapted from a previous version of a course.

Socially assistive robots (SARs) have the potential to revolutionize educational experiences by providing safe, non-judgmental, and emotionally supportive environments for children's social development. The success of SARs relies on the synergy of different modalities, such as speech, gestures, and gaze, to maximize interactive experiences. This paper presents an approach for generating SAR behaviors that extend an upper ontology. The ontology may enable flexibility and scalability for adaptive behavior generation by defining key assistive intents, turn-taking, and input properties. We compare the generated behaviors with hand-coded behaviors that are validated through an experiment with young children. The results demonstrate that the automated approach covers the majority of manually developed behaviors while allowing for significant adaptations to specific circumstances. The technical framework holds the potential for broader interoperability in other assistive domains and facilitates the generation of context-dependent and socially appropriate robot behaviors.

High levels of robot autonomy are a common goal, but there is a significant risk that the greater the autonomy of the robot the lesser the autonomy of the human working with the robot. For vulnerable populations like older adults who already have a diminished level of autonomy, this is an even greater concern. We propose that human autonomy needs to be at the center of the design for socially assistive robots. Towards this goal, we define autonomy and then provide architectural requirements for social robots to support the user's autonomy. As an example of a design effort, we describe some of the features of our Assist architecture.