Cooperative social robots to accompany groups of people

This study proposes a new model for guiding people in urban settings using multiple robots that work cooperatively. More speci cally, this investigation describes the circumstances in which people might stray from the formation when following di erent robots' instructions. To this end, we introduce a \Prediction and Anticipation Model" that predicts the position of the group using a Particle Filter, while determining the optimal robot behavior to help people stay in the group in areas where they may become distracted. As a result, this article presents a novel approach to locally optimizing the work performed by robots and people using the minimum robots' work criterion and determining humanfriendly types of movements. The guidance missions were carried out in urban areas that included multiple conflict areas and obstacles. This study also provides an analysis of robots' behavioral reactions to people by simulating di erent situations in the locations that were used for the investigation. The method was tested through simulations that took into account the di culties and technological constraints derived from real-life situations. Despites these problematic issues, we were able to demonstrate the robots' e ect on people in real-life situations in terms of pushing and dragging forces