Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization
This addresses usability challenges for both naive and expert users in industrial robotics, though it is incremental as it builds on existing XAI methods.
The paper tackled the limited adoption of deep learning in manufacturing by designing an Explanation User Interface (XUI) for a robot program optimizer, which improved task performance and user satisfaction based on a preliminary survey.
While recent advances in deep learning have demonstrated its transformative potential, its adoption for real-world manufacturing applications remains limited. We present an Explanation User Interface (XUI) for a state-of-the-art deep learning-based robot program optimizer which provides both naive and expert users with different user experiences depending on their skill level, as well as Explainable AI (XAI) features to facilitate the application of deep learning methods in real-world applications. To evaluate the impact of the XUI on task performance, user satisfaction and cognitive load, we present the results of a preliminary user survey and propose a study design for a large-scale follow-up study.