Your Way Or My Way: Improving Human-Robot Co-Navigation Through Robot Intent and Pedestrian Prediction Visualisations

As mobile robots enter shared urban spaces, operating in close proximity to people, this raises new challenges in terms of how these robots communicate with passers-by. Following an iterative process involving expert focus groups (n=8), we designed an augmented reality concept that visualises the robot's navigation intent and the pedestrian's predicted path. To understand the impact of path visualisations on trust, sense of agency, user experience, and robot understandability, we conducted a virtual reality evaluation (n=20). We compared visualising both robot intent and pedestrian path prediction against just visualising robot intent and a baseline without augmentation. The presence of path visualisations resulted in a significant improvement of trust. Triangulation of quantitative and qualitative results further highlights the impact of pedestrian path prediction visualisation on robot understandability as it allows for exploratory interaction.