Valuable Robotic Teammates: Algorithms That Reason About the Multiple Dimensions of Human-Robot Teamwork

As robots enter our homes and work places, one of the roles they will have to fulfill is being a teammate. Prior approaches in human-robot teamwork enabled robots to reason about intent, decide when and how to help, and allocate tasks to achieve efficiency. However, these existing algorithms mostly focused on understanding intent and providing help and assumed that teamwork is always present. Overall, effective robotic teammates must be able to reason about the multi-dimensional aspects of teamwork. Working towards this challenge, we present empirical findings and an algorithm that enables robots to understand the human's intent, communicate their own intent, display effortful behavior, and provide help to optimize the team's task performance. In addition to task performance, people also care about being treated fairly. As part of future work, we propose an algorithm that reasons about task performance and fairness to achieve lasting human-robot partnerships.

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