HCC: Medium: Proactive Physical Assistance for Collaborative Human-Robot Teams

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It is essential that robots working side-by-side with people be able to offer physical assistance. However, robots do not yet take the initiative to help. Instead, they typically follow preset plans for collaboration, or respond only when users explicitly ask for help. While useful in many situations, this reactive approach is poorly suited for many collaborative applications. This project focuses on enabling robots to proactively offer physical assistance that is timely, task-appropriate, and wanted by their human partners. The goal is to construct robots that can answer three key questions: (1) Does a teammate need help? (2) Can I (or someone else) help? and (3) Should I help? By enabling these capabilities, this project will make collaborative human-robot teams function more fluently and efficiently. To develop these capabilities, three research thrusts that are naturally intertwined but that capture important computational aspects of these tasks, will be advanced. First, perceiving other agents through a Theory of Mind for robots. The research team will develop computational models derived from our understanding of how humans represent the knowledge, beliefs, and desires of others to maintain context-sensitive models of the mental states of human and robotic teammates. Second, planning for supportive actions. The team will construct a system that generates possible supportive actions that the robot could take to help a teammate by using a trained model of the robot's own capabilities along with a predictive planning system that determines if these actions have value to the team. Third, decision making within the dynamics of a group. The robot will monitor and engage in social activities that support the overall dynamics of its partners including both conventional conversational interfaces and more subtle social mechanisms that facilitate collaboration.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.