3 accepted papers
Robot failures during collaborative tasks can frustrate users and reduce trust. To address this, we developed a failure communication module that combines large language models (LLMs) with Behavior Trees (BTs) to generate interactive, context-aware explanations for task failures. The module supports…
Bimanual teleoperation tasks are highly demanding for human operators, requiring the simultaneous control of two robotic arms while managing complex coordination and cognitive load. Current approaches to this challenge often rely on rigid control schemes or task-specific automation that do not adapt…
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