Towards Engaging Teaching Interfaces for Mobile Robots: Preliminary System Design and Insights on Usability *

As robots will be deployed around non-expert users in unstructured environments, they are bound to fail or behave suboptimally in some cases. Through interactive learning approaches, robots can leverage interaction with non-expert users to refine existing skills or even learn new tasks. If we will (at least partially) rely on these users to occasionally teach robots, we need to make sure the teaching tasks is seen as enjoyable rather than a burden. To this end, this paper presents a preliminary system design and evaluation for a multi-modal teaching system for non-expert users to teach simple navigation tasks to mobile robots. Our design, using human-dog interaction as a metaphor, focuses on creating engaging and embodied interactions that foster a sense of participation. Our preliminary results (N=20) suggest that participants had a positive perception of the learning system, and showed a clear preference for demonstrations over feedback as teaching signal. Participants with more affinity and experience with technology found the system more intuitive and engaging, and provided more accurate demonstrations, underscoring the importance of considering the users’ background and expertise when designing learning systems. This work paves the way towards designing usable and engaging teaching interfaces for robots that reduce barriers for non-expert users and foster a sense of teaching as an act of "care".