Andreas Naoum

Adapting Robot's Explanation for Failures Based on Observed Human Behavior in Human-Robot Collaboration

This work aims to interpret human behavior to anticipate potential user confusion when a robot provides explanations for failure, allowing the robot to adapt its explanations for more natural and efficient collaboration. Using a dataset [1] that included facial emotion detection, eye gaze estimation