On Teammate-Pattern-Aware Autonomy

Edmund H. Durfee (University of Michigan), Abhishek Thakur (BRINC Drones), Eli Goldweber (University of Michigan)

Abstract

We describe an approach for constraining robot autonomy based on the robot's awareness of patterns of its human teammates' behaviors, rather than either ignoring its teammates (which is fast but dangerous) or inferring their plans (which is safer but slow). We evaluate this approach in a series of simulated problems where an unmanned ground vehicle and its human teammates must rapidly respond to a sudden context shift, and identify conditions that should be (purposely) met such that a pattern-aware approach is particularly effective compared to the alternatives.