Improving Human-Robot Team Performance with Proactivity and Shared Mental Models
Abstract
Recent work in human-robot teaming has demonstrated that when robots build and maintain "shared mental models", the effectiveness of the whole human-robot team is overall better compared to a baseline with no shared mental models. In this work, we expand on this insight by introducing proactive behaviors to investigate potential further improvements of team performance and task efficiency. We hypothesize that, combined with shared mental models, robots with these more proactive behaviors become even more effective teammates. To this end, we developed a set of robot behaviors aligned with reactive, active and proactive team behaviors in human-human teams. We ran a human behavioral study to evaluate our system. The results show that proactive robot behavior improves task efficiency and performance over mere reactive behavior in high cognitive load environments.