The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

We design models and algorithms that enable robots to infer human cognitive state and learn implicit constraints and preferences of human team members from listening, watching, and practicing/training with human teams. Through this process, robots and machines learn “unwritten rules of the game” for working with teams of people in complex organizations and can collaborate to strengthen team plans. We also develop algorithms that enable robots to make fast adjustments to team plans in response to disturbances — to “play the game” with people. This work has been translated to enable new forms of human-machine teaming in manufacturing assembly lines, healthcare applications, transportation, and defense.

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