Towards Efficient Collaborations with Trust-Seeking Adaptive Robots

Abstract

We are interested in asymmetric human-robot teams, where a human supervisor occasionally takes over control to aid an autonomous robot in a given task. Our research aims to optimize team efficiency by improving the robot’s task per-formance, decreasing the human’s workload, and building trust in the team. We envision synergistic collaborations where the robot adapts its behaviors dynamically to opti-mize efficacy, reduce manual interventions, and actively seek for greater trust. We describe recent works that study two facets of this trust-seeking adaptive methodology: model-ing human-robot trust dynamics, and developing interactive behavior adaptation techniques. We also highlight ongo-ing efforts to combine these works, which will enable future human-robot teams to be maximally trusting and efficient. 1