Related papers: Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization

Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization

URL: http://arxiv.org/abs/2404.19349v1
Date: Tue, 30 Apr 2024 08:20:31 GMT
Title: Human-AI Interaction in Industrial Robotics: Design and Empirical Evaluation of a User Interface for Explainable AI-Based Robot Program Optimization
Authors: Benjamin Alt, Johannes Zahn, Claudius Kienle, Julia Dvorak, Marvin May, Darko Katic, Rainer Jäkel, Tobias Kopp, Michael Beetz, Gisela Lanza,
Abstract summary: We present an Explanation User Interface (XUI) for a state-of-the-art deep learning-based robot program. XUI provides both naive and expert users with different user experiences depending on their skill level.
Score: 5.537321488131869
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: 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.

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