WeldAR: Augmenting Live Hands-On Training with In-Situ Guidance for Novice Learners

2026-03-05

AI Summary

This study addresses the limitation of existing extended reality systems, which are largely confined to simulated training and struggle to provide real-time, in-situ guidance during actual physical tasks. To bridge this gap, the authors propose WeldAR—the first augmented reality system integrated into a welding helmet—that delivers real-time feedback on four critical welding parameters, including travel speed and work angle, through five dedicated learning modules. By synergistically combining head-mounted AR, a sensor-equipped welding torch, and real-time performance monitoring algorithms, WeldAR establishes a novel paradigm for embodied skill acquisition. In a controlled experiment with 24 novice welders, WeldAR significantly outperformed conventional video-based instruction, enhancing welding performance both during assisted practice and unassisted assessment, with particularly notable improvements in travel speed and work angle control.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Extended Reality (XR) systems for physical skill training have largely emphasized simulation rather than real-time in-situ instruction. We present WeldAR, an Augmented Reality (AR) system with five learning modules that overlays real-time guidance during live welding using a headset integrated into a welding helmet and a torch attachment. We conducted an in-situ within-subjects study with 24 novices, comparing AR guidance to video instruction for live welding across practice and unassisted tests. AR improved performance in both assisted practice and unassisted tests, primarily driven by gains in travel speed and work angle. By offering real-time feedback on four performance measures, AR supported novices in carrying embodied knowledge into independent tasks. Our contributions include: (1) WeldAR for in-situ physical skill training; (2) empirical evidence that AR enhances composite welding performance and key physical skills; and (3) implications for the development of AR systems that support in-situ, embodied skill training in welding and related trades.

Problem

• Extended Reality
• physical skill training
• in-situ guidance
• Augmented Reality
• novice learners

Innovation

• Augmented Reality
• in-situ guidance
• physical skill training
• real-time feedback
• embodied learning