Search Results (631)

Digital twin, as a new generation of industrial intelligent technology, has become a key technology for achieving virtual-physical interaction and real-time optimization in intelligent manufacturing systems due to its capability for high-fidelity virtual mapping of physical systems. Production scheduling, as the core link in the operation of intelligent workshops, faces challenges such as frequent dynamic disturbances, rendering traditional static scheduling approaches inadequate to meet the real-time and flexibility requirements of backdrop operations. In this context, the significant potential of the deep integration of digital twin technology and workshop scheduling in enhancing scheduling real-time performance, agility, and robustness has increasingly been highlighted. This paper reviews the research progress in workshop digital twin scheduling technology over the past five years, focusing on the development paths and technical characteristics of typical workshop digital twin modeling techniques, intelligent scheduling algorithms, and system frameworks. Based on this, the paper proposes a conceptual framework for digital twin scheduling in complex manufacturing scenarios, providing theoretical references for developing highly real-time and robust intelligent manufacturing scheduling systems, and highlights future research directions and developmental trends. Full article

With origins in video gaming, 3D virtual worlds (VWs) are digital environments where people engage and interact synchronously using digital characters called avatars. VWs may have future potential for delivering youth mental health (YMH) services. Despite progress in developing VW-based YMH interventions, limited consultation with young people may be contributing to mixed uptake and engagement. This study aimed to understand how young people with experiences accessing YMH services view the potential (i.e., hypothetical) use of VWs for YMH service delivery to understand qualitative factors influencing uptake. Eleven 18–25-year-old consumers (M = 22.91 years; five women, five men, and one non-binary person) took part in one-on-one, semi-structured interviews via videoconferencing. Interviews explored anticipated ease of use, helpfulness, and perceived intention to use VW-based YMH interventions if they were made available. Interviews were analysed using reflexive thematic analysis. Four themes were produced: (1) VWs as unique therapeutic spaces; (2) creative engagement for therapy; (3) VW communication promoting both connection and distance; (4) flexible access. All participants expressed a level of openness towards the potential use of VWs for YMH interventions. Features such as creative world-building and avatar customisation, increased anonymity, and remote accessibility were seen as ways to improve access to convenient, personalised, and engaging mental healthcare. Concerns included technology misuse, privacy risks, and reduced physical and emotional presence. Future research and service development should test real-world outcomes to ensure clinical benefit and employ codesign approaches that leverage servicer-users’ expectations to ensure accessible and acceptable delivery. Full article

Real-time hybrid simulation (RTHS) evaluates the dynamic performance of a structure by physically testing the selected components while modeling the remaining structure numerically, making it efficient in both cost and testing space requirements. In RTHS, accurately imposing target boundary conditions on specimens is critical, as it directly influences test accuracy and overall simulation stability. However, boundary condition application often experiences tracking errors due to the dynamics of the servo–hydraulic loading system and control-structural interaction. This challenge intensifies with multiple actuators operating in a multi-axial setup, introducing dynamic coupling effects. Thus, an outer-loop controller enabling precise actuator tracking of reference boundary conditions is essential for reliable RTHS. While advancements in outer-loop controllers for uniaxial RTHS exist, multi-axial RTHS (maRTHS) employing multiple degrees of freedom control remains underexplored. This study applies the adaptive discrete feedforward controller (ADFC), consisting of a discrete feedforward compensator and an online identifier, to a multi-input, multi-output (MIMO) system for maRTHS. To validate ADFC’s performance and robustness, 1000 virtual maRTHS tests incorporating plant uncertainties were conducted under seismic excitations. Ten evaluation criteria were applied. Results confirm that ADFC achieves robust and stable control by reducing phase and amplitude errors, while also improving estimation accuracy at the physical–numerical interface. Full article

This study investigates the coupling and coordination mechanisms between virtual and physical spatial heat in coastal internet-famous streets under the influence of social media. Taking Dalian’s coastal internet-famous street as a case study, user interaction data (likes, favorites, shares, and comments) from the Xiaohongshu platform were integrated with multi-source spatio-temporal big data, including Baidu Heat Maps, to construct an “online–offline” heat coupling and coordination evaluation framework. The entropy-weight method was employed to quantify online heat, while nonlinear regression analysis and a coupling coordination degree model were applied to examine interaction mechanisms and spatio-temporal differentiation patterns. The results show that online heat demonstrates significant polarization with strong agglomeration in the Donggang area, while offline heat fluctuates periodically, rising during the day, stabilizing at night, and peaking on holidays at up to 3.5 times weekday levels with marginal diminishing effects. Forwarding behavior is confirmed as the core driver of online popularity, highlighting the central role of cross-circle communication. The coupling coordination model identifies states ranging from high-quality coordination during holidays to discoordination in daily under-conversion or overload scenarios. These findings verify the leading role of algorithmic recommendation in redistributing spatial power and demonstrate that the sustainability of coastal check-in destinations depends on balancing short-term traffic surges with long-term spatial quality, providing practical insights for governance and sustainable urban planning. Full article

People with limited mobility experience disadvantages when participating in outdoor activities such as cycling, which can lead to negative consequences. This study proposes an indoor physical cycling activity, with the help of technological solutions, for people with limited mobility. The aim is to use enhanced reality (ER) technology, based on virtual reality, to exercise in the person’s own indoor environment. In this system, real track and speed information is received by a 360-degree camera, GPS, and gyroscope sensors and presented to the mechanical system in the electromechanical bike structure with real-time interaction. The pedal force system of the exercise bike is driven using information of the incline, and data from the bike’s speed sensor and head movements are transferred in real time to the track image on the user’s head-up display, creating a realistic experience. With this system, it is possible to maintain an experience close to real cycling through human–computer interaction with hardware and software integration. Thus, using this system, people with limited mobility can improve their quality of life by performing indoor physical activities with an experience close to reality. Full article

STEM (Science, Technology, Engineering, and Mathematics) education faces the challenge of incorporating advanced technologies that foster motivation, collaboration, and hands-on learning. This study proposes a portable system capable of transforming ordinary surfaces into interactive learning spaces through gamification and spatial perception. A prototype based on multi-agent architecture was developed on the PANGEA (Platform for automatic coNstruction of orGanizations of intElligent agents) platform, integrating LIDAR (Light Detection and Ranging) sensors for gesture detection, an ultra-short-throw projector for visual interaction and a web platform to manage educational content, organize activities and evaluate student performance. The data from the sensors is processed in real time using ROS (Robot Operating System), generating precise virtual interactions on the projected surface, while the web allows you to configure physical and pedagogical parameters. Preliminary tests show that the system accurately detects gestures, translates them into digital interactions, and maintains low latency in different classroom environments, demonstrating robustness, modularity, and portability. The results suggest that the combination of multi-agent architectures, LIDAR sensors, and gamified platforms offers an effective approach to promote active learning in STEM, facilitate the adoption of advanced technologies in diverse educational settings, and improve student engagement and experience. Full article

This paper presents the development and evaluation of a method for rendering realistic haptic textures in virtual environments, with the goal of enhancing immersion and surface recognizability. By using Blender for the creation of geometric models, Unity for real-time interaction, and integration with the Touch haptic device from 3D Systems, virtual surfaces were developed with parameterizable characteristics of friction, stiffness, and relief, simulating different physical textures. The methodology was assessed through two experimental phases involving a total of 47 participants, examining both tactile recognition accuracy and the perceived realism of the textures. Results demonstrated improved overall performance and reduced variability between textures, suggesting that the approach can provide convincing haptic experiences. The proposed method has potential applications across a wide range of domains, including education, medical simulation, cartography, e-commerce, entertainment, and artistic creation. The main contribution of this research lies in the introduction of a simple yet effective methodology for haptic texture rendering, which is based on the flexible adjustment of key parameters and iterative optimization through human feedback. Full article

According to previous research, young children’s numeracy skills may be scaffolded by practicing on the number line. A number line estimation task (NLET) is often conducted with pen and paper, while linear number games are often implemented on a computer or a tablet. If and how the format—physical or digital—influences the accuracy of the estimations is, however, not well-known. If regarding NLET performance as dependent on specific strategies and hypothesizing that these strategies may be affected by the material used, we may also assume that different materials may either support or hinder children’s learning. In this paper, we explore whether training with a physical versus a virtual NLET game will affect children’s strategies when solving NLETs, and if these strategies relate to the accuracy of the estimations. Sixty-two 6-year-old children played an NLET game (virtual or physical) for three sessions, being scaffolded and guided by a researcher. NLET performance was measured by pre- and post-tests, as well as during the intervention. The results show that even if the condition did not significantly affect the children’s overall numeracy skills, the children in the physical condition did express more advanced strategies during the intervention. These strategies, in turn, predicted NLET performance. Full article

The aim of this study is to examine the role and use of augmented reality in engineering education by examining the existing literature. A total of 235 studies from Scopus and Web of Science published during 2011–2025 were examined. The study focused on analyzing the main characteristics of the studies, identifying the main topics, and exploring the use of augmented reality in engineering education. The study also highlighted current challenges and limitations and suggested future research directions. Based on the results, 7 main topics arose which were related to (i) Immersive technologies in engineering education, (ii) Gamified learning experiences, (iii) Remote and virtual laboratories, (iv) Visualization and 3D modeling, (v) Student motivation, (vi) Collaborative and interactive learning environments, and (vii) User-centered design and user experience. Augmented reality emerged as an effective educational tool that can positively impact engineering education and support both students and teachers. Specifically, physical, remote, and virtual laboratories that can improve students’ learning performance, motivation, creativity, engagement, and satisfaction can be created through augmented reality. Using augmented reality, students can develop their practical skills and knowledge within low-risk and secure learning environments. Additionally, via the realistic and interactive visualization, students’ knowledge acquisition and understanding can be enhanced. Finally, its ability to effectively support collaborative learning and experiential learning arose. Full article

Robotic systems play an increasingly significant role in both education and industry; however, access to physical robots remains a challenge due to high costs and operational risks. This work presents a training platform based on Digital Twins, aimed at active learning in the control of robotic manipulators, with a focus on the UFACTORY 850 arm. The proposed approach integrates mathematical modeling, interactive simulation, and experimental validation, enabling the implementation and testing of control strategies in three virtual scenarios that replicate real-world conditions: a laboratory, a service environment, and an industrial production line. The system relies on kinematic and dynamic models of the manipulator, using maneuverability velocities as input signals, and employs ROS as middleware to link the Unity 2022.2.14 graphics engine with the control algorithms developed in MATLAB R2022a. Experimental results demonstrate the accuracy of the implemented models and the effectiveness of the control algorithms, validating the usefulness of Digital Twins as a pedagogical tool to support safe, accessible, and innovative learning in robotic engineering. Full article

In recent decades, simulation has emerged as a pivotal educational tool, bolstering scientific knowledge and honing decision-making skills across diverse disciplines. Surgery and flight simulators are well-known tools used to practice and train safely in surgeries and piloting. Meanwhile, the development of simulation games advances in other scientific fields, such as economics, management, engineering, and mathematics. These simulations offer learners a risk-free virtual platform to apply and refine their knowledge, leveraging animations, graphics, and interactive environments to enrich the learning experience. In engineering, while simulation is widely utilized as a powerful training tool for heavy equipment and process handling, the creation of strategy games for educational purposes is less frequent. This gap primarily stems from the challenge of converting complex engineering concepts and theories into a user-friendly yet comprehensive setup that preserves the more difficult aspects. This study adopts a design-based research approach to develop and evaluate an educational simulation game aimed at enhancing probabilistic and spatial reasoning in mineral exploration. The application generates random scenarios, within which users deploy strategies based on their knowledge, while accommodating the randomness of physical phenomena. The simulation game is adopted as an educational tool in the course “Introduction to Mineral Exploration” in the School of Mining and Metallurgical Engineering of the National Technical University of Athens. Additionally, we present the outcomes of game analytics and a qualitative evaluation derived from three workshops at higher education institutions in Greece. Full article

Precision manufacturing requires handling multi-physics coupling during processing, where digital twin and AI technologies enable rapid robot programming under customized requirements. However, heterogeneous data sources, diverse domain models, and rapidly changing demands pose significant challenges to digital twin system integration. To overcome these limitations, this paper proposes a digital twin modeling strategy based on a metamodel and a virtual–real fusion architecture, which unifies models between the virtual and physical domains. Within this framework, subsystems achieve rapid integration through ontology-driven knowledge configuration, while ROS provides the execution environment for establishing robot manufacturing digital twin scenarios. A case study of a robot shaping system demonstrates that the proposed architecture effectively addresses heterogeneous data association, model interaction, and application customization, thereby enhancing the adaptability and intelligence of precision manufacturing processes. Full article

As stroke is becoming more frequent nowadays, cutting edge rehabilitation approaches are required to recover upper limb functionalities and to support patients during daily activities. Recently, focus has moved to robotic rehabilitation; however, therapeutic devices are still highly expensive, making rehabilitation not easily affordable. Moreover, devices are not easily accepted by patients, who can refuse to use them due to not feeling comfortable. The presented work proposes the exploitation of a virtual prototype of the human–robot ecosystem for the study and analysis of patient–robot interactions, enabling their simulation-based investigation in multiple scenarios. For the accomplishment of this task, the Dynamics of Multi-physical Systems platform, previously presented by the authors, is further developed to enable the integration of biomechanical models of the human body with mechatronics models of robotic devices for motion assistance, as well as with PID-based control strategies. The work begins with (1) a description of the background; hence, the current state of the art and purpose of the study; (2) the platform is then presented and the system is formalized, first from a general side and then (3) in the application-specific scenario. (4) The use case is described, presenting a controlled gym weightlifting exercise supported by an exoskeleton and the results are analyzed in a final paragraph (5). Full article

The growing complexity of distribution-level virtual power plants (VPPs) demands a rethinking of how flexible demand is modeled, aggregated, and dispatched under uncertainty. Traditional optimization frameworks often rely on deterministic or homogeneous assumptions about end-user behavior, thereby overestimating controllability and underestimating risk. In this paper, we propose a behavior-aware, two-stage stochastic dispatch framework for VPPs that explicitly models heterogeneous user participation via integrated behavioral economics and social interaction structures. At the behavioral layer, user responses to demand response (DR) incentives are captured using a Prospect Theory-based utility function, parameterized by loss aversion, nonlinear gain perception, and subjective probability weighting. In parallel, social influence dynamics are modeled using a peer interaction network that modulates individual participation probabilities through local contagion effects. These two mechanisms are combined to produce a high-dimensional, time-varying participation map across user classes, including residential, commercial, and industrial actors. This probabilistic behavioral landscape is embedded within a scenario-based two-stage stochastic optimization model. The first stage determines pre-committed dispatch quantities across flexible loads, electric vehicles, and distributed storage systems, while the second stage executes real-time recourse based on realized participation trajectories. The dispatch model includes physical constraints (e.g., energy balance, network limits), behavioral fatigue, and the intertemporal coupling of flexible resources. A scenario reduction technique and the Conditional Value-at-Risk (CVaR) metric are used to ensure computational tractability and robustness against extreme behavior deviations. Full article

In response to the growing demand for automation in aerospace harness manufacturing, this study proposes a digital twin-based intelligent monitoring system for robotic wiring operations. The system integrates a seven-degree-of-freedom robotic platform with an adaptive servo gripper and employs a five-dimensional digital twin framework to synchronize physical and virtual entities. Key innovations include a coordinated motion model for minimizing joint displacement, a particle-swarm-optimized backpropagation neural network (PSO-BPNN) for adaptive gripping based on wire characteristics, and a virtual–physical closed-loop interaction strategy covering the entire wiring process. Methodologically, the system enables motion planning, quality prediction, and remote monitoring through Unity3D visualization, SQL-driven data processing, and real-time mapping. The experimental results demonstrate that the system can stably and efficiently complete complex wiring tasks with 1:1 trajectory reproduction. Moreover, the PSO-BPNN model significantly reduces prediction error compared to standard BPNN methods. The results confirm the system’s capability to ensure precise wire placement, enhance operational efficiency, and reduce error risks. This work offers a practical and intelligent solution for aerospace harness production and shows strong potential for extension to multi-robot collaboration and full production line scheduling. Full article