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Article
Automation & Control Systems
Chao Zhang et al.
Summary: Thin-walled parts in the aerospace industry often suffer from milling deformation due to their thin-walled draping and large size ratio characteristics. This quality issue greatly impacts the assembly performance and operation safety of aerospace equipment. To address this, a novel online optimal control method using digital twins for thin-walled parts is proposed, which includes a reference framework and three key enabling technologies. The application and evaluation of a prototype system demonstrate the feasibility and effectiveness of the proposed approach.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Engineering, Industrial
Chao Zhang et al.
Summary: Developing intelligent machine tools is crucial for manufacturing enterprises to achieve intelligent manufacturing in Industry 4.0. However, most current approaches focus on single digital twin machine tools with limited intelligence. This paper proposes a novel framework that integrates digital twin with multi-access edge computing (MEC) to construct a knowledge-sharing intelligent machine tool swarm with secure and ultra-low latency performance.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Sung Ho Choi et al.
Summary: This study introduces a novel integrated mixed reality system using deep learning and digital twin generation to accurately measure minimum safe distance and provide task assistance for human operators. By tracking the shared workplace and providing user-centric visualization through smart MR glasses, the system ensures safe and effective human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
Jonas Friederich et al.
Summary: Adoption of digital twins in smart factories can improve productivity and reduce costs and energy consumption. Traditional modeling and simulation approaches are not suitable for rapid transitions and shorter product life cycles. As a solution, we propose a generic data-driven framework that utilizes advancements in machine learning and process mining techniques for automated generation of simulation models, enabling smart factory digital twins.
COMPUTERS IN INDUSTRY
(2022)
Review
Computer Science, Interdisciplinary Applications
Junming Fan et al.
Summary: This paper provides a systematic review of computer vision-based holistic scene understanding in human-robot collaboration (HRC) scenarios. It emphasizes the cognition of key elements such as objects, humans, and the environment. The paper also discusses the challenges and potential research directions in achieving proactive HRC.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
Yongkui Liu et al.
Summary: This paper proposes a digital twin-enabled approach for effective transfer of DRL algorithms to physical robots, addressing the issue of sim-to-real transfer. The experimental results validate the effectiveness of the intelligent grasping algorithm and the digital twin-enabled approach and mechanism.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Review
Engineering, Mechanical
Yang Fu et al.
Summary: Traditional design, manufacturing, and maintenance methods have become inefficient in the digitized world, and there is a need for a unified platform for integration. The concept of digital twin and associated technology provide a solution for the integration of design, manufacturing, and maintenance throughout the product lifecycle.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2022)
Review
Computer Science, Interdisciplinary Applications
Yalda Ghasemi et al.
Summary: This paper reviews the integration of augmented/mixed reality and deep learning for object detection over the past decade and analyzes the advantages and limitations of its applications and computations.
COMPUTERS IN INDUSTRY
(2022)
Article
Computer Science, Interdisciplinary Applications
Chengxi Li et al.
Summary: This research proposes a novel multi-robot collaborative manufacturing system that combines augmented reality and digital twin techniques. The system visualizes digital twins of industrial robots and incorporates a multi-robot communication mechanism to enable human-in-the-loop control. Experimental results demonstrate that the system can efficiently handle multi-robot teleoperation tasks and has the potential to be applied in other complex manufacturing scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Engineering, Industrial
Te Han et al.
Summary: This article presents a novel OOD detection-assisted trustworthy machinery fault diagnosis approach, which integrates multiple deep neural networks and utilizes uncertainty analysis to enhance the reliability and safety of intelligent models, showing significant advantages in identifying OOD samples.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Qinglin Qi et al.
Summary: Digital twin is revolutionizing industry by mirroring almost every facet of a product, process or service in the digital space. However, realizing their full potential is a complex process as researchers need to model different parts of objects or systems, collect and merge varied types of data, and struggle with determining the technologies and tools to be used. The 5-dimension digital twin model provides guidance for understanding and implementing digital twin technologies.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Information Systems
Rafael Padilla et al.
Summary: This study provides an overview of evaluation methods used in object detection competitions, examines the influence of different annotation formats on evaluation results, and offers an open-source toolkit supporting various annotation formats and performance metrics for researchers to evaluate their detection algorithms. Furthermore, it introduces a new metric for evaluating object detection in videos based on spatio-temporal overlap.
Article
Computer Science, Interdisciplinary Applications
Hongyi Liu et al.
Summary: Recent advancements in human-robot collaboration have led to the development of a context awareness-based collision-free system that ensures both human safety and assembly efficiency. This system can plan robotic paths to avoid collisions with human operators while reaching target positions in a timely manner, and can also recognize human operators' poses with low computational costs to further improve assembly efficiency. The system incorporates a collision sensing module with sensor calibration algorithms and a transfer learning-based human pose recognition algorithm to enhance overall system performance.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Review
Chemistry, Analytical
Ziqi Huang et al.
Summary: Digital twin and artificial intelligence technologies play essential roles in Industry 4.0, with a focus on the integration of infrastructure, algorithms, and applications. AI-driven digital twin technologies are widely used in smart manufacturing and advanced robotics, offering advantages for sustainable development.
Article
Computer Science, Interdisciplinary Applications
Ali Ahmad Malik et al.
Summary: This paper discusses the potential of using digital twin technology to tackle the complexity of human-robot collaborative systems, presenting the forms of digital twins throughout the system's life cycle, their building blocks, and the potential advantages. Recommendations for future research and practice in the field of cobotics are provided.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Michael G. Kapteyn et al.
Summary: This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset, enabling the transition from custom implementations to robust digital twin implementations at scale. The model's declarative and general nature allows for rigorous yet flexible application in diverse areas. Demonstrations show how the model can be instantiated and calibrated with experimental data for dynamic decision-making scenarios.
NATURE COMPUTATIONAL SCIENCE
(2021)
Article
Computer Science, Information Systems
Kyeong-Beom Park et al.
Summary: This study introduces a novel hands-free interaction method using multimodal gestures and deep learning for human-robot interaction in mixed reality environments. The method supports coarse-to-fine interactions, utilizing eye gazing for searching and previewing and head gestures for selection and 3D manipulation. Deep learning-based object detection helps estimate initial object positioning, and virtual object-based indirect manipulation enables more intuitive and efficient control of the robot compared to traditional methods.
Review
Computer Science, Theory & Methods
Laith Alzubaidi et al.
Summary: Deep learning has become the gold standard in the machine learning community, widely used in various domains and capable of learning massive data. Through a comprehensive survey, a better understanding of the most important aspects of deep learning is provided.
JOURNAL OF BIG DATA
(2021)
Review
Computer Science, Information Systems
M. Mazhar Rathore et al.
Summary: Digital twinning has emerged as a top technology trend in recent years, especially in the industrial sector, due to its integration with big data analytics and AI-ML techniques. Despite the lack of a systematic review on digital twinning focusing on the role of big data and AI-ML, this technology shows great potential for future developments in academia and industry. Through a systematic review, researchers have highlighted the importance of big data and AI-ML in the creation of digital twins for various industrial applications.
Article
Computer Science, Interdisciplinary Applications
Emanuele Magrini et al.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2020)
Article
Computer Science, Interdisciplinary Applications
Antti Hietanen et al.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2020)
Article
Automation & Control Systems
Fei Tao et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2019)
Article
Computer Science, Interdisciplinary Applications
C. Y. Siew et al.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2019)
Article
Computer Science, Interdisciplinary Applications
Chiara Cimino et al.
COMPUTERS IN INDUSTRY
(2019)
Proceedings Paper
Engineering, Industrial
Xin Ma et al.
11TH CIRP CONFERENCE ON INDUSTRIAL PRODUCT-SERVICE SYSTEMS
(2019)
Review
Robotics
Eloise Matheson et al.
Article
Automation & Control Systems
Valeria Villani et al.
Review
Psychology, Multidisciplinary
Shanee Honig et al.
FRONTIERS IN PSYCHOLOGY
(2018)
Article
Computer Science, Artificial Intelligence
Shaoqing Ren et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Kaiming He et al.
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)
(2017)
Article
Automation & Control Systems
Carlos E. Agueero et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2015)
Article
Computer Science, Artificial Intelligence
Mark Everingham et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2015)
Article
Computer Science, Artificial Intelligence
Fabrizio Flacco et al.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2015)
Proceedings Paper
Computer Science, Artificial Intelligence
Ross Girshick
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV)
(2015)
Article
Engineering, Industrial
Bernard Schmidt et al.
JOURNAL OF MANUFACTURING SYSTEMS
(2014)
Article
Computer Science, Artificial Intelligence
J. R. R. Uijlings et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2013)
