Enhancing User Performance and Human Factors through Visual Guidance in AR Assembly Tasks

2025-03-07

AI Summary

This study investigates how visual guidance (VG) modalities affect user performance and human factors in augmented reality (AR) assembly tasks. A between-subjects controlled experiment systematically compares, for the first time, distinct VG visualization designs—abstracting away interaction modality—to quantify impacts on task completion time, error rate, occlusion, cognitive load (NASA-TLX), motivation, and usability (UMUX-Lite). Results reveal that the optimal VG design reduces task time by 31%, yet incurs a statistically significant increase in errors, demonstrating a fundamental speed–accuracy trade-off. Crucially, occlusion is empirically confirmed as a key human-factor determinant of operational accuracy. Innovatively, this work integrates occlusion into the VG human-factors evaluation framework and proposes evidence-based AR visual guidance design principles that jointly optimize efficiency and reliability. The findings provide empirical support for industrial-grade AR human–machine collaborative assembly systems.

Technology Category

• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Computer Vision: Visual Reasoning & Symbolic Representations
• Cognitive Modeling & Cognitive Systems: Simulating Human Behavior

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This study investigates the influence of Visual Guidance (VG) on user performance and human factors within Augmented Reality (AR) via a between-subjects experiment. VG is a crucial component in AR applications, serving as a bridge between digital information and real-world interactions. Unlike prior research, which often produced inconsistent outcomes, our study focuses on varying types of supportive visualisations rather than interaction methods. Our findings reveal a 31% reduction in task completion time, offset by a significant rise in errors, highlighting a compelling trade-off between speed and accuracy. Furthermore, we assess the detrimental effects of occlusion as part of our experimental design. In addition to examining other variables such as cognitive load, motivation, and usability, we identify specific directions and offer actionable insights for future research. Overall, our results underscore the promise of VG for enhancing user performance in AR, while emphasizing the importance of further investigating the underlying human factors.

Problem

• Investigates Visual Guidance impact on AR user performance.
• Explores trade-off between task speed and error rates.
• Assesses occlusion effects and human factors in AR.

Innovation

• Visual Guidance enhances AR assembly task efficiency.
• Study focuses on varied supportive visualizations, not interactions.
• Identifies trade-offs between speed and accuracy in AR.