Supervisory control of multiple social robots for navigation

This paper presents a human study and system implementation for the supervisory control of multiple social robots for navigational tasks. We studied the acceptable range of speed for robots interacting with people through navigation, and we discovered that entertaining people by speaking during navigation can increase people's tolerance toward robots' slow locomotion speed. Based on these results and using a robot safety model developed to ensure safety of robots during navigation, we implemented an algorithm which can proactively adjust robot behaviors during navigation to improve the performance of a human-robot team consisting of a single operator and multiple mobile social robots. Finally, we implemented a semi-autonomous robot system and conducted experiments in a shopping mall to verify the effectiveness of our proposed methods in a real-world environment.