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Applied Sciences
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Robotics and Automation Systems in Construction: Trends and Prospects
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Robotics and Automation Systems in Construction: Trends and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 July 2025 | Viewed by 3917

Special Issue Editors

Dr. Phuong Hoang Dat Nguyen

E-Mail Website
Guest Editor
Department of Construction & Concrete Industry Management, South Dakota State University, Brookings, SD 57007, USA
Interests: artificial intelligence and automation in construction; innovative project delivery methods; construction labor productivity and safety
Dr. Alireza Golabchi

E-Mail Website
Guest Editor
Construction Innovation Centre, University of Alberta, Edmonton, AB T6G 1H9, Canada
Interests: construction robotics and automation; construction safety and ergonomics

Special Issue Information

Dear Colleagues,

Robotics and automation systems play a crucial role in revolutionizing the construction industry by enhancing productivity, improving safety, and addressing labor shortages. Research highlights the benefits of automation in construction, including increased worker safety, improved quality, cost-effectiveness, and enhanced job efficiency. Studies emphasize that automation and robotics can contribute to circular construction by boosting productivity, reducing waste, and mitigating labor shortages, especially in concrete construction projects. However, challenges such as fragmented construction processes, worker resistance, lack of expertise, and inadequate support from top-level management hinder the full deployment of robotics and automation systems in the construction industry. In this regard, this Special Issue invites you to submit original research papers focused on “Robotics and Automation System in Construction: Trends and Prospects”. Topics may include, but are not limited to, the following:

  • Artificial intelligence and automation in construction;
  • Human–robot collaboration;
  • Construction robotics and equipment in safety management;
  • Robotics systems for sustainable construction;
  • On-site automated and robotic systems;
  • Off-site automated prefabrication systems;
  • Drones and autonomous vehicles in construction;
  • Sensing technologies and construction automation.

Dr. Phuong Hoang Dat Nguyen
Dr. Alireza Golabchi
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. Applied Sciences 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 2400 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 engineering and management
  • robotic construction equipment
  • 3D printing
  • drones
  • exoskeletons
  • building information modeling
  • artificial intelligence
  • unmanned aircraft systems

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Published Papers (2 papers)

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28 pages, 36682 KiB  
Article
Augmented Data-Driven Approach towards 3D Printed Concrete Mix Prediction
by Saif Ur Rehman, Raja Dilawar Riaz, Muhammad Usman and In-Ho Kim
Appl. Sci. 2024, 14(16), 7231; https://doi.org/10.3390/app14167231 - 16 Aug 2024
Cited by 2 | Viewed by 2893
Abstract
Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); [...] Read more.
Formulating a mix design for 3D concrete printing (3DCP) is challenging, as it involves an iterative approach, wasting a lot of resources, time, and effort to optimize the mix for strength and printability. A potential solution is mix formulation through artificial intelligence (AI); however, being a new and emerging field, the open-source availability of datasets is limited. Limited datasets significantly restrict the predictive performance of machine learning (ML) models. This research explores data augmentation techniques like deep generative adversarial network (DGAN) and bootstrap resampling (BR) to increase the available data to train three ML models, namely support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting regression (XGBoost). Their performance was evaluated using R2, MSE, RMSE, and MAE metrics. Models trained on BR-augmented data showed higher accuracy than those trained on the DGAN-augmented data. The BR-trained XGBoost exhibited the highest R2 scores of 0.982, 0.970, 0.972, 0.971, and 0.980 for cast compressive strength, printed compressive strength direction 1, 2, 3, and slump flow respectively. The proposed method of predicting the slump flow (mm), cast, and anisotropic compressive strength (MPa) can effectively predict the mix design for printable concrete, unlocking its full potential for application in the construction industry. Full article
(This article belongs to the Special Issue Robotics and Automation Systems in Construction: Trends and Prospects)
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Review

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20 pages, 30275 KiB  
Review
Robotics in the Construction Industry: A Bibliometric Review of Recent Trends and Technological Evolution
by Lu Xu, Yulin Zhang, Mengjiao Liu, Yanhong Li, Yihang Li, Yaqing Yu, Qi Tang, Shaobin Weng, Kun Sang and Guiye Lin
Appl. Sci. 2025, 15(11), 6277; https://doi.org/10.3390/app15116277 - 3 Jun 2025
Viewed by 460
Abstract
The construction industry faces persistent challenges, including labor shortages and safety hazards, while traditional construction methods are increasingly strained by the complexity and sustainability demands of modern projects. The integration of robotics shows significant potential for mitigating labor shortages and enhancing safety on [...] Read more.
The construction industry faces persistent challenges, including labor shortages and safety hazards, while traditional construction methods are increasingly strained by the complexity and sustainability demands of modern projects. The integration of robotics shows significant potential for mitigating labor shortages and enhancing safety on construction sites. The current adoption of robotics technologies is driven by both the maturity of robotics technology and the potential for cost reduction compared with manual labor. This review synthesizes recent advancements and trends in construction robotics through a bibliometric analysis of 212 publications indexed in Web of Science from 2002 to 2024. Key findings indicate a 320% increase in research output from 2015 to 2022, with dominant clusters focusing on autonomous navigation, human–robot collaboration, and sustainability-driven automation. Geographically, China and the United States lead in number of publications, with 67 and 65 articles, respectively; however, cross-border collaborations remain sparse, constituting fewer than 5% of co-authored papers. Keyword co-occurrence analysis reveals evolving priorities, including artificial intelligence (AI)-driven adaptive control, modular prefabrication, and the ethical implications of automation. Despite technological advancements, critical gaps remain in terms of interoperability, workforce retraining, and regulatory frameworks. This study emphasizes the need for interdisciplinary integration, standardized protocols, and policy alignment to bridge the divide between academic innovation and industry adoption, ultimately facilitating the global transition toward Construction 4.0. Full article
(This article belongs to the Special Issue Robotics and Automation Systems in Construction: Trends and Prospects)
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