Abstract:
Robots, and autonomous systems in general, are becoming increasingly more advanced beyond traditional functions. This can potentially widen the mismatch between human expectations of system behaviors during interaction, especially when the systems behave unexpectedly. Unexpected system behaviors could induce negative emotional responses in humans, which not all systems have the capability of recognizing and detecting in real-time. To prevent such situations, systems should communicate system behavior expectations to humans during the task. In addition, after a mismatch, the systems should perform post-hoc strategies to mitigate human’s negative emotional responses, through explanations or corrective behaviors.

This thesis proposal investigates how systems can communicate expectations to humans in situ using legible motion planning, how systems can detect subtle emotional responses to unexpected system behaviors, and post-hoc expectation mismatch mitigation strategies. For the latter, we focus on explanation and corrective behavior, to mitigate negative emotional responses from humans using verbal, visual, and nonverbal modalities.

Thesis Committee Members:
Aaron Steinfeld (Chair)
Fernando De La Torre Frade
Nikolas Martelaro
Brian Mok (BMW Group)

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