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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 January 2026 | Viewed by 6573

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 (6 papers)

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Research

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23 pages, 10369 KB  
Article
YOLOv8-SAMURAI: A Hybrid Tracking Framework for Ladder Worker Safety Monitoring in Occlusion Scenarios
by Sangyoon Yun and Hyunsoo Kim
Buildings 2025, 15(11), 1836; https://doi.org/10.3390/buildings15111836 - 27 May 2025
Viewed by 745
Abstract
Monitoring worker safety during ladder operations at construction sites is challenging due to occlusion, where workers are partially or fully obscured by objects or other workers, and overlapping, which makes individual tracking difficult. Traditional object detection models, such as YOLOv8, struggle to maintain [...] Read more.
Monitoring worker safety during ladder operations at construction sites is challenging due to occlusion, where workers are partially or fully obscured by objects or other workers, and overlapping, which makes individual tracking difficult. Traditional object detection models, such as YOLOv8, struggle to maintain tracking continuity under these conditions. To address this, we propose an integrated framework combining YOLOv8 for initial object detection and the SAMURAI tracking algorithm for enhanced occlusion handling. The system was evaluated across four occlusion scenarios: non-occlusion, minor occlusion, major occlusion, and multiple worker overlap. The results indicate that, while YOLOv8 performs well in non-occluded conditions, the tracking accuracy declines significantly under severe occlusions. The integration of SAMURAI improves tracking stability, object identity preservation, and robustness against occlusion. In particular, SAMURAI achieved a tracking success rate of 94.8% under major occlusion and 91.2% in multiple worker overlap scenarios—substantially outperforming YOLOv8 alone in maintaining tracking continuity. This study demonstrates that the YOLOv8-SAMURAI framework provides a reliable solution for real-time safety monitoring in complex construction environments, offering a foundation for improved compliance monitoring and risk mitigation. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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16 pages, 6476 KB  
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 1151
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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23 pages, 4936 KB  
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 723
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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Review

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32 pages, 2341 KB  
Review
Human and Multi-Robot Collaboration in Indoor Environments: A Review of Methods and Application Potential for Indoor Construction Sites
by Francis Xavier Duorinaah, Mathanraj Rajendran, Tae Wan Kim, Jung In Kim, Seulbi Lee, Seulki Lee and Min-Koo Kim
Buildings 2025, 15(15), 2794; https://doi.org/10.3390/buildings15152794 - 7 Aug 2025
Viewed by 702
Abstract
The integration of robotic agents into complex indoor construction environments is increasing, particularly through human–robot collaboration (HRC) and multi-robot collaboration (MRC). These collaborative frameworks hold great potential to enhance productivity and safety. However, indoor construction environments present unique challenges, such as dynamic layouts, [...] Read more.
The integration of robotic agents into complex indoor construction environments is increasing, particularly through human–robot collaboration (HRC) and multi-robot collaboration (MRC). These collaborative frameworks hold great potential to enhance productivity and safety. However, indoor construction environments present unique challenges, such as dynamic layouts, constrained spaces, and variable lighting conditions, which complicate the safe and effective deployment of collaborative robot teams. Existing studies have primarily addressed various HRC and MRC challenges in manufacturing, logistics, and outdoor construction, with limited attention given to indoor construction settings. To this end, this review presents a comprehensive analysis of human–robot and multi-robot collaboration methods within various indoor domains and critically evaluates the potential of adopting these methods for indoor construction. This review presents three key contributions: (1) it provides a structured evaluation of current human–robot interaction techniques and safety-enhancing methods; (2) it presents a summary of state-of-the-art multi-robot collaboration frameworks, including task allocation, mapping, and coordination; and (3) it identifies major limitations in current systems and provides research directions for enabling scalable, robust, and context-aware collaboration in indoor construction. By bridging the gap between current robotic collaboration methods and the needs of indoor construction, this review lays the foundation for the development of adaptive and optimized collaborative robot deployment frameworks for indoor built environments. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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19 pages, 1563 KB  
Review
Autonomous Earthwork Machinery for Urban Construction: A Review of Integrated Control, Fleet Coordination, and Safety Assurance
by Zeru Liu and Jung In Kim
Buildings 2025, 15(14), 2570; https://doi.org/10.3390/buildings15142570 - 21 Jul 2025
Viewed by 625
Abstract
Autonomous earthwork machinery is gaining traction as a means to boost productivity and safety on space-constrained urban sites, yet the fast-growing literature has not been fully integrated. To clarify current knowledge, we systematically searched Scopus and screened 597 records, retaining 157 peer-reviewed papers [...] Read more.
Autonomous earthwork machinery is gaining traction as a means to boost productivity and safety on space-constrained urban sites, yet the fast-growing literature has not been fully integrated. To clarify current knowledge, we systematically searched Scopus and screened 597 records, retaining 157 peer-reviewed papers (2015–March 2025) that address autonomy, integrated control, or risk mitigation for excavators, bulldozers, and loaders. Descriptive statistics, VOSviewer mapping, and qualitative synthesis show the output rising rapidly and peaking at 30 papers in 2024, led by China, Korea, and the USA. Four tightly linked themes dominate: perception-driven machine autonomy, IoT-enabled integrated control systems, multi-sensor safety strategies, and the first demonstrations of fleet-level collaboration (e.g., coordinated excavator clusters and unmanned aerial vehicle and unmanned ground vehicle (UAV–UGV) site preparation). Advances include centimeter-scale path tracking, real-time vision-light detection and ranging (LiDAR) fusion and geofenced safety envelopes, but formal validation protocols and robust inter-machine communication remain open challenges. The review distils five research priorities, including adaptive perception and artificial intelligence (AI), digital-twin integration with building information modeling (BIM), cooperative multi-robot planning, rigorous safety assurance, and human–automation partnership that must be addressed to transform isolated prototypes into connected, self-optimizing fleets capable of delivering safer, faster, and more sustainable urban construction. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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Other

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30 pages, 2830 KB  
Systematic Review
The Role of AI in On-Site Construction Robotics: A State-of-the-Art Review Using the Sense–Think–Act Framework
by Zhihao Ren and Jung In Kim
Buildings 2025, 15(13), 2374; https://doi.org/10.3390/buildings15132374 - 7 Jul 2025
Viewed by 2033
Abstract
The construction sector is confronted with significant challenges, such as reduced productivity, high injury rates, and labor deficits, driving research into autonomous robotics as a viable solution. This study delivers a comprehensive review of recent advancements in AI-driven autonomous construction robotics, organized within [...] Read more.
The construction sector is confronted with significant challenges, such as reduced productivity, high injury rates, and labor deficits, driving research into autonomous robotics as a viable solution. This study delivers a comprehensive review of recent advancements in AI-driven autonomous construction robotics, organized within the sense–think–act (STA) framework. A rigorous bibliometric analysis of 319 selected publications from 2015 to 2024 highlights key research trends and notable contributors. A systematic content analysis elaborates on advancements in each STA component, including technologies for perception and environmental understanding, decision-making algorithms for reasoning and planning, and varied actuation methods addressing scale and collaborative robotics. The study also explores challenges such as environmental unpredictability, specialized task demands, and structural safety concerns. Finally, it underscores future research priorities, focusing on balanced robotic system design, dataset standardization, domain-specific knowledge incorporation, and enhanced robustness to support the broader implementation of autonomous construction robotics. Full article
(This article belongs to the Special Issue Automation and Robotics in Building Design and Construction)
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