Abstract
Concrete structures require precise temperature and humidity monitoring during curing to ensure optimal strength and prevent defects like cracking. A compact optical sensing system was developed using a single fiber that can be embedded directly within the concrete. The system functions as both a temperature and humidity sensor when paired with a spectral interrogation unit operating in the 1500-1600 nm range. Temperature monitoring is achieved through a Fiber Bragg Grating, while humidity sensing is facilitated by a Fabry-Perot interferometer at the fiber tip. The interferometer cavity is formed with a layer of polyvinylpyrrolidone (PVP). Initial air humidity sensor tests showed a significant change in the interference period with RH, demonstrating low hysteresis and high reproducibility. Calibration of one sensor revealed an approximately 3 nm period decrease when RH increased from 55% to 95%, with results suggesting a quadratic relationship between the interference period and RH values.

Abstract

Abstract
Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing facility for evaluating mobile robots and pilot robotic systems in a research laboratory environment. The platform integrates high-fidelity physical and environmental models, providing a controlled yet dynamic setting for analyzing robotic behavior. A key feature of the system is its comprehensive data collection framework, capturing critical parameters such as position, orientation, and velocity, which can be leveraged for machine learning, performance optimization, and decision-making. The facility also supports the simulation of discrete operational systems, using predictive modeling to bridge informational gaps when real-time data updates are unavailable. The digital twin was validated through a matrix manufacturing system simulation, with an Augmented Reality (AR) interface on the HoloLens 2 to overlay digital information onto mobile platform controllers, enhancing situational awareness. The main contributions include a digital twin framework for deploying data-driven robotic systems and three key AR/VR integration optimization methods. Demonstrated in a laboratory setting, the system is a versatile tool for research and industrial applications, fostering insights into robotic automation and digital twin scalability while reducing costs and risks associated with real-world testing.

Abstract

Abstract
Hyperbolic Metamaterials (HMM) are a class of photonic metamaterials exhibiting hyperbolic dispersion due to strong anisotropy. This work presents a numerical analysis and experimental characterization of a hyperbolic multilayer structure supporting surface plasmon polaritons for refractometric sensing applications. The device consists of a multilayer HMM composed of alternate Au and TiO2 layers, and the interaction of different plasmonic modes at each interface of the HMM is reported to enhance light- matter coupling, leading to an increased refractometric sensitivity. The hyperbolic dispersion and its effects on sensor performance are numerically investigated using the Effective Medium Theory (EMT) and validated through the Transfer Matrix Method (TMM). A fair match was obtained between EMT and TMM simulated spectra, validating the EMT approach for simulation of the optical properties of multilayer HMMs. Despite not predicting figures of merit (FOM) accurately, both the TMM and EMT approaches closely replicated the obtained experimental refractometric sensitivity.

Abstract
The growing reliance on e-commerce and the demand for efficient intralogistics operations have increased the need for automation, while labour shortages continue to pose significant challenges. When combined with the inherent risks of forklift operation, this circumstance prompted businesses to look for robotic solutions for intralogistics tasks. However, robots are still limited when they come across situations that are outside of their programming scope and often need assistance from humans. To achieve the long-term goal of enhancing intralogistics operation, we propose the development of a virtual reality-based teleoperation system that allows remote operation of robot forklifts with minimal latency. Considering the specificities of the teleoperation process and network dynamics, we conduct detailed modelling to analyse latency factors, optimise system performance, and ensure a seamless user experience. Experimental results on a mobile robot have shown that the proposed teleoperation system achieves an average glass-to-glass latency of 368 ms, with capturing latency contributing to approximately 60% of the total delay. The results also indicate that network oscillations significantly impact image quality and user experience, emphasising the importance of a stable network infrastructure.