User Interface Interventions for Improving Robot Learning from Demonstration

Teaching robots can be challenging, particularly for novice human users who struggle to understand the robot's learning process. Current research in interactive robot learning lacks effective methods for assessing a user's interpretation of the robot's learning state, which makes it difficult to compare different teaching approaches. To address these issues, we propose and demonstrate a method for assessing the user's interpretation of the robot's learning state in an interactive learning scenario with a robotic manipulator. Additionally, we draw on existing literature to categorise types of interface interventions that can enhance the human-robot teaching process for novice users - both pragmatically and hedonically. In a user study (N=30), we implement two of these interventions and show how they improve robot performance, teaching efficiency and interpretability. These findings provide preliminary insights into the design of effective human-robot teaching interfaces and can be used to assist the development of future teaching approaches.