Yik Shin Tey

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About

Yik Shin Tey is a researcher focused on augmented reality (AR) applications in industrial maintenance, particularly for robotic systems. Their most-cited work, "A Review on Augmented Reality Tracking Methods for Maintenance of Robots" (2020), has garnered 5 citations and provides a comprehensive survey of AR tracking techniques tailored to robot maintenance. This review critically examines how AR systems—ranging from marker-based to sensor-driven approaches—can be implemented to guide technicians through complex repair and servicing tasks, bridging the gap between virtual instructions and physical robotic assets. Tey’s contribution lies in synthesizing disparate tracking methods and highlighting their practical trade-offs for real-world maintenance scenarios, from large-scale industrial robots to smaller automated systems. By mapping the landscape of AR-enabled maintenance, Tey offers a valuable resource for researchers and engineers seeking to deploy intuitive, hands-free guidance systems that reduce downtime and human error. This work underscores the potential of AR to transform traditional maintenance workflows, making it a foundational reference for those exploring human-robot interaction and industrial digitalization.