What Questions Should Robots Be Able to Answer? A Dataset of User Questions for Explainable Robotics
Researchers have developed a new dataset of 1,893 user questions specifically designed for explainable robotics. This dataset, collected from 100 participants, categorizes questions into 12 types, focusing on user expectations for robot capabilities and task execution details. The findings indicate that while users frequently ask about basic task information, they consider questions about hypothetical scenarios and ensuring correct behavior to be the most important. This resource aims to aid in developing better question-answering modules and explanation strategies for human-robot interaction. AI
IMPACT Provides a benchmark for developing more intuitive and informative human-robot interaction systems.