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Buildings
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Automation and Robotics in Building Design and Construction
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Automation and Robotics in Building Design and Construction

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 771

Special Issue Editors

Dr. Minkoo Kim

E-Mail Website
Guest Editor
Department of Architectural Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: construction automation; robotics; construction safety; smart sensing technologies
Dr. Tae Wan Kim

E-Mail Website
Guest Editor
Division of Architecture and Urban Design, Incheon National University, Incheon 22012, Republic of Korea
Interests: automation in construction; offsite construction; decision support systems; digital twin and simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Jung In Kim

E-Mail Website
Guest Editor
School of Civil Systems Engineering, Kookmin University, Seoul 02707, Republic of Korea
Interests: construction management; smart city; building information modeling; construction technologies
Dr. Sungjin Kim

E-Mail Website
Guest Editor
Department of Architectural Engineering, Hanbat National University, Daejeon 34158, Republic of Korea
Interests: construction automation; robotics; construction management; smart sensing technologies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Construction robots are increasingly being adopted in the construction industry and building construction projects due to their potential to address several challenges and improve efficiency, safety, and quality. In addition, automation is inevitable across industries, and the construction sector must prepare its workforce for this transition. For all these reasons, construction robots and automation are playing a crucial role in advancing the current construction environment in a smart and safe manner.

This Special Issue, entitled “Automation and Robotics in Building Design and Construction”, aims to cover topics related to the technological improvement of construction robots in all phases of construction projects, such as the following:

  • Automated data acquisition of construction environments using construction robots;
  • Robot-oriented design in construction;
  • Data flow from data acquisition by construction robots to on-site works;
  • Robotic off-site manufacturing;
  • Robotic on-site execution and maintenance;
  • Computational design oriented to robotics;
  • Human–robot collaboration;
  • Construction management under human–robot collaboration;
  • Construction automation using robotics.

We look forward to receiving your contributions.

Dr. Minkoo Kim
Dr. Tae Wan Kim
Dr. Jung In Kim
Dr. Sungjin Kim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • construction robots
  • building construction
  • smart sensing
  • design for construction robots
  • operation platform
  • human–robot collaboration
  • construction management

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

16 pages, 6476 KiB  
Article
Evaluation of Worker Fatigue During Exoskeleton-Assisted Tasks with Varying Intensities
by Daehwi Jo, Gu Young Cho, Kyung-In Kang and Hyunsoo Kim
Buildings 2025, 15(9), 1503; https://doi.org/10.3390/buildings15091503 - 29 Apr 2025
Viewed by 247
Abstract
Worker fatigue is a significant concern in construction environments, particularly for high-intensity repetitive tasks that contribute to physical strain and increase the risk of accidents. This study evaluates the impact of exoskeleton-assisted work on fatigue reduction across different construction tasks and intensity levels. [...] Read more.
Worker fatigue is a significant concern in construction environments, particularly for high-intensity repetitive tasks that contribute to physical strain and increase the risk of accidents. This study evaluates the impact of exoskeleton-assisted work on fatigue reduction across different construction tasks and intensity levels. Using inertial measurement unit (IMU) sensors and the dynamic time warping (DTW) algorithm, we quantitatively analyzed movement patterns and fatigue accumulation in workers performing carrying, scaffold installation, and masonry tasks under both low-intensity and high-intensity conditions. The results demonstrate that exoskeleton support effectively reduces DTW values, indicating improved movement consistency and lower fatigue levels. Specifically, DTW values were reduced by approximately 15–25% with exoskeleton use, with the most significant reductions observed in scaffold installation (25%) and carrying tasks (22%). Time-series analysis further revealed that exoskeletons not only decrease overall fatigue accumulation but also slow the rate of fatigue increase, extending the period in which workers can maintain safe and efficient movement patterns. The findings highlight the potential of exoskeleton technology to enhance worker safety and reduce fatigue-related risks in physically demanding construction tasks. This study contributes to the advancement of objective fatigue assessment methodologies and provides insights into the practical implementation of exoskeletons in construction environments. However, this study is limited by its short-term design, task scope, and the absence of long-term fatigue tracking, which will be addressed in future work. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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24 pages, 4936 KiB  
Article
A Practical Image Augmentation Method for Construction Safety Using Object Range Expansion Synthesis
by Jaemin Kim, Ingook Wang, Jungho Yu and Seulki Lee
Buildings 2025, 15(9), 1447; https://doi.org/10.3390/buildings15091447 - 24 Apr 2025
Viewed by 281
Abstract
This study aims to propose a practical and realistic synthetic data generation method for object recognition in hazardous and data-scarce environments, such as construction sites. Artificial intelligence (AI) applications in such dynamic domains require domain-specific datasets, yet collecting real-world data can be challenging [...] Read more.
This study aims to propose a practical and realistic synthetic data generation method for object recognition in hazardous and data-scarce environments, such as construction sites. Artificial intelligence (AI) applications in such dynamic domains require domain-specific datasets, yet collecting real-world data can be challenging due to safety concerns, logistical constraints, and high labor costs. To address these limitations, we introduce object range expansion synthesis (ORES), a lightweight and non-generative method for generating synthetic image data by inserting real object masks into varied background scenes using open datasets. ORES synthesizes new scenes, while preserving scale and ground alignment, enabling controllable and realistic data augmentation. A dataset of 30,000 synthetic images was created using the proposed method and used to train an object recognition model. When tested on real-world construction site images, the model achieved a mean average precision at IoU 0.50 (mAP50) of 98.74% and a recall of 54.55%. While recall indicates room for improvement, the high precision highlights the practical value of synthetic data in enhancing model performance without requiring extensive field data collection. This research contributes a scalable approach to data generation in safety-critical and data-deficient environments, reducing dependence on direct data acquisition, while maintaining model efficacy. It provides a foundation for accelerating the deployment of AI technologies in high-risk industries by overcoming data bottlenecks and supporting real-world applications through practical synthetic augmentation. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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