Review
Chemistry, Analytical
Andreas Sjolander, Valeria Belloni, Anders Ansell, Erik Nordstrom
Summary: With increased urbanization, cities have become densely populated and heavily reliant on transportation infrastructure. The downtime of important parts of the infrastructure, such as tunnels and bridges, significantly affects the transportation system's efficiency. Technological advancements in computer vision, AI, and robotics have opened up the possibilities of automated inspections, which can greatly decrease infrastructure downtime.
Article
Construction & Building Technology
Xin Chen, Qingsong Zhang, Rentai Liu, Xiaofeng Wang, Wanli He
Summary: Inspection robots are rarely used in metro tunnels due to the unbalanced technical indicators. This study proposes a method to develop a maintenance strategy and assess the life-cycle cost of inspection robots in metro tunnels. It is found that the inspection cycle has a non-linear relationship with the life-cycle cost, and the detection accuracy of the inspection subject is negatively correlated with the cost. An evaluation model is established to guide the intervention indexes of the inspection robot.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Engineering, Civil
Wonseok Seo, Byungjoo Choi, Dongyoun Shin, Jinyoung Kim
Summary: The precast concrete (PC) method is a process of manufacturing reinforced concrete building components in a factory and then transporting them to and assembling them on a construction site. It is widely used as an advantageous means to create a sustainable environment and improve construction quality. However, due to time and cost increase, many modern PC factories only inspect randomly selected component samples using paper-based forms for inspection reports. This study developed a mobile application that automates documentation and storage, and allows for systematic data input to achieve comprehensive quality management and assurance within PC factories.
JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Seungbo Shim, Seong-Won Lee, Gye-Chun Cho, Jin Kim, Sung-Mo Kang
Summary: To ensure the safety of concrete structures, accurate and periodic inspection for damage is necessary. However, manual inspection methods are prone to inaccurate diagnoses due to reliance on operator experience and subjective judgment. This study proposes an objective and automated inspection method using an inspection robot and management system. The robot autonomously navigates tunnels, using stereo vision to inspect concrete damage, while the management system remotely controls and monitors the robot. This method has the potential to be a core technology for unmanned and automated tunnel maintenance in the future.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Review
Materials Science, Multidisciplinary
David Curiel, Fernando Veiga, Alfredo Suarez, Pedro Villanueva
Summary: Robotic welding manufacturing of metal parts is crucial in heavy industries like shipbuilding, oil and gas, automotive, and aerospace. Various techniques for manufacturing through robotic welding exist, and continuous advancements aim to prevent defects. Despite research progress, this publication focuses on defining and reviewing recent works that showcase advancements in inspection, modeling, monitoring, and automated operations during the welding process to ensure high-quality welds.
Article
Environmental Sciences
Bianca Bendris, Julian Cayero Becerra
Summary: Current railway tunnel inspections rely on expert operators performing visual examinations and manually annotating defects. This study proposes an aerial robotic solution equipped with visual and thermal sensors to autonomously inspect tunnel-like infrastructures, optimizing data quality and surface coverage through a path planning algorithm.
Article
Construction & Building Technology
Cynthia Brosque, Gunnar Skeie, Martin Fischer
Summary: The use of robots has improved safety, productivity, and quality in the construction industry, while reducing costs. Research shows that robotic drilling offers significant advantages over traditional methods, reducing work hours, improving worker ergonomics, and lowering rework rates.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2021)
Article
Engineering, Marine
Alexander G. Rumson
Summary: This paper focuses on recent innovations in external remote subsea pipeline inspection methods, specifically highlighting the unmanned method of using AUV and USV for inspections. Results from a recent project are presented, showing how automated workflows were integrated with existing hardware and software to operate AUV from shore remotely.
Article
Robotics
Yalun Wen, Daniel J. Jaeger, Prabhakar R. Pagilla
Summary: This study introduces a novel solution to cover the surface area of a curved surface with varying curvatures using a circular, flat finishing tool. The strategy involves developing a local contact shape descriptor and utilizing position-dependent contact area to achieve full and uniform coverage of free-form surfaces. Experimental validation confirms the effectiveness of the proposed approach.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Construction & Building Technology
Naotoshi Yasuda, Norikazu Misaki, Yoshinori Shimada, Oleg Kotyaev
Summary: This study confirms the feasibility of using remote laser sensing for reinforced concrete tunnel linings, although environmental factors in the field may affect the results, it still provides an effective quantitative evaluation.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2021)
Article
Engineering, Chemical
M. Calixto-Rodriguez, Jorge S. Valdez Martinez, M. A. Meneses-Arcos, Jose Ortega-Cruz, E. Sarmiento-Bustos, Adriana Reyes-Mayer, Michelle Gonzalez-Castaneda, Rodolfo Omar Dominguez Garcia
Summary: This translation introduces the design of inexpensive equipment for depositing semiconductor thin films by SILAR method, controlled through a human-machine interface and programming based on state machines. The system was tested with copper oxide thin films on glass substrates and characterized for structural, optical, and morphological properties using XRD, UV-VIS, and SEM.
Review
Construction & Building Technology
Samuel Leder, Achim Menges
Summary: This paper reviews architectural design research in collective robotic construction (CRC), aiming to reduce barriers in working with such novel construction automation systems, by categorizing and understanding different design approaches and their implications.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Automation & Control Systems
Jun Younes Louhi Kasahara, Hiromitsu Fujii, Atsushi Yamashita, Hajime Asama
Summary: The article introduces a new approach for weakly supervised acoustic defect detection in concrete structures, which allows for significant performance gains with low amounts of weak supervision.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2021)
Article
Engineering, Chemical
Liwei Cao, Danilo Russo, Alexei A. Lapkin
Summary: Product design for formulations is an active and challenging area of research that requires re-examining existing theoretical frameworks to adapt to the new reality of digitalization in business and research. Automation and machine-learning-guided optimization play important roles in formulated product design.
Review
Construction & Building Technology
Jing Wang, Jiaqi Zhang, Anthony G. G. Cohn, Zhengfang Wang, Hanchi Liu, Wenqiang Kang, Peng Jiang, Fengkai Zhang, Kefu Chen, Wei Guo, Yanfei Yu
Summary: This paper presents an automatic scheme based on (RDCNN)-D-2 and GPR images for accurate detection of defects and rebars in tunnel lining. Experimental results show that (RDCNN)-D-2 outperforms (RCNN)-C-2 in both synthetic and real GPR images.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Automation & Control Systems
David Estevez, Juan G. Victores, Raul Fernandez-Fernandez, Carlos Balaguer
ROBOTICS AND AUTONOMOUS SYSTEMS
(2020)
Article
Chemistry, Analytical
Noe Perez-Higueras, Alberto Jardon, Angel Rodriguez, Carlos Balaguer
Article
Chemistry, Analytical
Edwin Daniel Ona, Alberto Jardon, Alicia Cuesta-Gomez, Patricia Sanchez-Herrera-Baeza, Roberto Cano-de-la-Cuerda, Carlos Balaguer
Review
Chemistry, Analytical
Ruben De-la-Torre, Edwin Daniel Ona, Carlos Balaguer, Alberto Jardon
Article
Chemistry, Multidisciplinary
Andrea Gil Ruiz, Juan G. Victores, Bartek Lukawski, Carlos Balaguer
APPLIED SCIENCES-BASEL
(2020)
Review
Computer Science, Information Systems
Juan Miguel Garcia-Haro, Edwin Daniel Ona, Juan Hernandez-Vicen, Santiago Martinez, Carlos Balaguer
Summary: With the advancement of robotics technology, waiter robots and other "catering robotics" are gradually entering professional fields such as restaurants. These robots have social capacities to interact with consumers and other robots, as well as physical skills to perform complex tasks in environments like restaurants.
Article
Automation & Control Systems
J. Hernandez-Vicen, S. Martinez, C. Balaguer
Summary: This article introduces an application that uses computer vision techniques to identify boxes, extracting characteristics and determining the opening side based on a decision tree. The goal is to develop a future application where the humanoid robot TEO can learn to find and manipulate the opening of boxes in an automated system.
REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL
(2021)
Article
Robotics
Panagiotis Vartholomeos, Panos Marantos, George Karras, Elisabeth Menendez, Marcos Rodriguez, Santiago Martinez, Carlos Balaguer
Summary: The letter introduces the BADGER autonomous underground robot, which utilizes inchworm biomimetic motion to build curved tunnels underground. Efficient motion control strategies, including gait sequence and motion controller, are designed using dynamic modeling and a model-based approach.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Information Systems
Juan Hernandez-Vicen, Santiago Martinez, Raul de Santos-Rico, Elisabeth Menendez, Carlos Balaguer
Summary: This study examines three different movement strategies for bi-manipulating a box, studies the dynamics involved, conducts experiments, and creates primitive movements based on force and position information in the end effectors.
Article
Mathematics
Luis Nagua, Carlos Relano, Concepcion A. Monje, Carlos Balaguer
Summary: A soft joint with 2 Degrees of Freedom designed to function as a robotic joint utilizing a Cable-Driven Parallel Mechanism. A test platform using components manufactured in a 3D printer with a flexible polymer was developed to analyze its performance in detail. The mathematical kinematics model of the soft joint including a blocking mechanism and workspace morphology was validated through Finite Element Analysis, with experimental tests confirming the inverse kinematic model and potential use in robotic platforms.
Article
Computer Science, Artificial Intelligence
Raul Fernandez-Fernandez, Juan G. Victores, Jennifer J. Gago, David Estevez, Carlos Balaguer
Summary: This study applies the concept of style transfer to deep reinforcement learning, proposing the Neural Policy Style Transfer algorithm that can transfer the style of one policy to another while maintaining the content. Experimental results show that the algorithm can successfully perform style transfer under different Q-network architectures.
COGNITIVE SYSTEMS RESEARCH
(2022)
Article
Mathematics, Interdisciplinary Applications
Carlos Relano, Jorge Munoz, Concepcion A. Monje, Santiago Martinez, Daniel Gonzalez
Summary: This paper investigates the identification and control problems of a novel two-degrees-of-freedom, tendon-actuated, soft robotic arm. A decoupled identification approach is proposed, and a fractional order control strategy is experimentally tested and compared with PI solutions. Simulation and experimental results demonstrate the effectiveness of the discussed modeling and control approaches.
FRACTAL AND FRACTIONAL
(2023)
Proceedings Paper
Automation & Control Systems
Raul Fernandez-Fernandez, Marco Aggravi, Paolo Robuffo Giordano, Juan G. Victores, Claudio Pacchierotti
Summary: Neural Style Transfer (NST) is an algorithm that allows an element to adopt the appearance or style of another element. This paper presents a custom NST framework for transferring styles to robotic motion. By using an autoencoder architecture and TD3 network, the robot's motion can be altered and adapted offline or online.
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2022)
(2022)
Article
Construction & Building Technology
Jia Liang, Qipeng Zhang, Xingyu Gu
Summary: A lightweight PCSNet-based segmentation model is developed to address the issues of insufficient performance in feature extraction and boundary loss information. The introduction of generalized Dice loss improves prediction performance, and the visualization of class activation mapping enhances model interpretability.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Gilsu Jeong, Minhyuk Jung, Seongeun Park, Moonseo Park, Changbum Ryan Ahn
Summary: This study introduces a contextual audio-visual approach to recognize multi-equipment activities in tunnel construction sites, improving monitoring effectiveness. Tested against real-world operation data, the model achieved remarkable results, emphasizing the potential of contextual multimodal models in enhancing operational efficiency in complex construction sites.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Jin Wang, Zhigao Zeng, Pradip Kumar Sharma, Osama Alfarraj, Amr Tolba, Jianming Zhang, Lei Wang
Summary: This study presents a dual-path network for pavement crack segmentation, combining Convolutional Neural Network (CNN) and transformer. A lightweight CNN encoder is used for local feature extraction, while a novel transformer encoder integrates high-low frequency attention mechanism and efficient feedforward network for global feature extraction. Additionally, a complementary fusion module is introduced to aggregate intermediate features extracted from both encoders. Evaluation on three datasets confirms the superior performance of the proposed network.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Pierre Gilibert, Romain Mesnil, Olivier Baverel
Summary: This paper introduces a flexible method for crafting 2D assemblies adaptable to various geometric assumptions in the realm of sustainable construction. By utilizing digital fabrication technologies and optimization approaches, precise control over demountable buildings can be achieved, improving mechanical performance and sustainability.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Jorge Loy-Benitez, Myung Kyu Song, Yo-Hyun Choi, Je-Kyum Lee, Sean Seungwon Lee
Summary: This paper discusses the advancement of tunnel boring machines (TBM) through the application of artificial intelligence. It highlights the significance of AI-based management subsystems for automatic TBM operations and presents recent contributions in this field. The paper evaluates modeling, monitoring, and control subsystems and suggests research paths for integrating existing management subsystems into TBM automation.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Alireza Shamshiri, Kyeong Rok Ryu, June Young Park
Summary: This paper reviews the application of text mining and natural language processing in the construction field, highlighting the need for automation and minimizing manual tasks. The study identifies potential research opportunities in strengthening overlooked construction aspects, coupling diverse data formats, and leveraging pre-trained language models and reinforcement learning.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zhengyi Chen, Hao Wang, Keyu Chen, Changhao Song, Xiao Zhang, Boyu Wang, Jack C. P. Cheng
Summary: This study proposes an improved coverage path planning system that leverages building information modeling and robotic configurations to optimize coverage performance in indoor environments. Experimental validation shows the effectiveness and applicability of the system. Future research will focus on further enhancing coverage ratio and optimizing computation time.
AUTOMATION IN CONSTRUCTION
(2024)
Review
Construction & Building Technology
Yonglin Fu, Junjie Chen, Weisheng Lu
Summary: This study presents a review of human-robot collaboration (HRC) in modular construction manufacturing (MCM), focusing on tasks, human roles, and interaction levels. The review found that HRC solutions are applicable to various MCM tasks, with a primary focus on timber component production. It also revealed the diverse collaborative roles humans can play and the varying levels of interaction with robots.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Qiong Liu, Shengbo Cheng, Chang Sun, Kailun Chen, Wengui Li, Vivian W. Y. Tam
Summary: This paper presents an approach to enhance the path-following capability of concrete printing by integrating steel cables into the printed mortar strips, and validates the feasibility and effectiveness of this approach through experiments.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Honghu Chu, Lu Deng, Huaqing Yuan, Lizhi Long, Jingjing Guo
Summary: The study proposes a method called Cascade CATransUNet for high-resolution crack image segmentation. This method combines the coordinate attention mechanism and self-cascaded design to accurately segment cracks. Through a customized feature extraction architecture and an optimized boundary loss function, the proposed method achieves impressive segmentation performance on HR images and demonstrates its practicality in UAV crack detection tasks.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Daniel Lamas, Andres Justo, Mario Soilan, Belen Riveiro
Summary: This paper introduces a new method for creating synthetic point clouds of truss bridges and demonstrates the effectiveness of a deep learning approach for semantic and instance segmentation of these point clouds. The proposed methodology has significant implications for the development of automated inspection and monitoring systems for truss bridges.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Kahyun Jeon, Ghang Lee, Seongmin Yang, Yonghan Kim, Seungah Suh
Summary: This study proposes two enhanced unsupervised text classification methods for domain-specific non-English text. The results of the tests show that these methods achieve excellent performance on Korean building defect complaints, outperforming state-of-the-art zero-shot and few-shot text classification methods, with minimal data preparation effort and computing resources.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Yoonhwa Jung, Julia Hockenmaier, Mani Golparvar-Fard
Summary: This study introduces a transformer-based natural language processing model, UNIfORMATBRIDGE, that automatically labels activities in a project schedule with Uniformat classification. Experimental results show that the model performs well in matching unstructured schedule data to Uniformat classifications. Additionally, the study highlights the importance of this method in developing new techniques.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Keivan Bamdad, Tosin Famakinwa
Summary: This paper introduces a digital twin technology combining Building Information Modelling and the Internet of Things for the construction industry, aiming to optimize building conditions. The technology is implemented in a university library, successfully achieving real-time data capture and visual representation of internal conditions.
AUTOMATION IN CONSTRUCTION
(2024)
Article
Construction & Building Technology
Zaolin Pan, Yantao Yu
Summary: The construction industry faces safety and workforce shortages globally, and worker-robot collaboration is seen as a solution. However, robots face challenges in recognizing worker intentions in construction. This study tackles these challenges by proposing a fusion method and investigating the best granularity for recognizing worker intentions. The results show that the proposed method can recognize multi-granular worker intentions effectively, contributing to seamless worker-robot collaboration in construction.
AUTOMATION IN CONSTRUCTION
(2024)
