Automation in Construction最新文献_第7页

Extrusion under material uncertainty with pressure-based closed-loop feedback control in robotic concrete additive manufacturing 基于压力闭环反馈控制的机械混凝土增材制造中材料不确定性的挤压

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-02 DOI: 10.1016/j.autcon.2025.106494

Mahsa Rabiei, Reza Moini

{"title":"Extrusion under material uncertainty with pressure-based closed-loop feedback control in robotic concrete additive manufacturing","authors":"Mahsa Rabiei, Reza Moini","doi":"10.1016/j.autcon.2025.106494","DOIUrl":"10.1016/j.autcon.2025.106494","url":null,"abstract":"<div><div>One of the main challenges in extrusion-based robotic concrete additive manufacturing process is material uncertainty under pressure which leads to geometric inaccuracies. Here, a real-time pressure-based closed-loop feedback control system is developed to address the geometric fidelity challenges that arise from the material uncertainty under extrusion. A robotic extrusion process is instrumented with a load sensor and assessed with and without activation of the pressure-based controller. The reliability and robustness of a pressure-based closed-loop control system is examined by introducing single- and double-perturbation of the extrusion and assessing the recovery of the geometry (width, height) of the extruded filaments to a baseline reference. The developed control system reacts to retrieve and maintain geometric fidelity among all experiments and repetitions, thereby highlighting the utility of pressure as a feedback parameter to handle material uncertainty that is common in extrusion-based robotic manufacturing process. Future directions include evaluating the control system in unseen conditions.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106494"},"PeriodicalIF":11.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bimodal defect segmentation with Geometric Prior-supported Anti-imbalance Learning for pavement defect evaluation and repair 基于几何先验支持的抗失衡学习双峰缺陷分割用于路面缺陷评估与修复

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-02 DOI: 10.1016/j.autcon.2025.106497

Yanyan Wang , Kechen Song , Yuyuan Liu , Tianze Li , Yunhui Yan , Gustavo Carneiro

{"title":"Bimodal defect segmentation with Geometric Prior-supported Anti-imbalance Learning for pavement defect evaluation and repair","authors":"Yanyan Wang , Kechen Song , Yuyuan Liu , Tianze Li , Yunhui Yan , Gustavo Carneiro","doi":"10.1016/j.autcon.2025.106497","DOIUrl":"10.1016/j.autcon.2025.106497","url":null,"abstract":"<div><div>Pavement defect segmentation benefits from integrating 2D images with 3D depth data, enabling more accurate evaluation and repair decisions. However, current methods suffer from indiscriminate feature extraction that overlooks severe class imbalance, limited adaptability to defects with diverse shapes and appearances, and a lack of publicly available bimodal datasets with multi-class annotations. To address these challenges, this paper proposes Geometric Prior-supported Anti-imbalance Learning (GPAL), a bimodal segmentation framework based on the Segment Anything Model (SAM). GPAL introduces: (1) Defect-centric Reinforcing (DR) prompting, which leverages geometric priors derived from depth flow to enhance the image encoder’s focus on defect details in a defect-oriented manner; and (2) Depth Prototype-support Uniform Prompting (DPUP), which extends SAM for bimodal, multi-class defect segmentation by learning class-balanced depth prototypes. Additionally, the Bimodal Multi-category Pavement Defect (BMPD) dataset is constructed, containing 5,059 samples across four defect categories. Experimental results demonstrate that the proposed method effectively highlights defects under imbalanced conditions and adapts to diverse defects, achieving an mF1 score of 86.01% on the BMPD dataset. This advancement supports reliable pavement assessment and repair decisions, while laying a foundation for addressing class imbalance in diverse tasks through geometric priors and prompting strategies.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106497"},"PeriodicalIF":11.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leveraging digital enabling technologies for integrating climate adaptation and mitigation in urban design 利用数字技术将气候适应和减缓融入城市设计

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-02 DOI: 10.1016/j.autcon.2025.106504

Guglielmo Ricciardi , Guido Callegari , Mattia Federico Leone

{"title":"Leveraging digital enabling technologies for integrating climate adaptation and mitigation in urban design","authors":"Guglielmo Ricciardi , Guido Callegari , Mattia Federico Leone","doi":"10.1016/j.autcon.2025.106504","DOIUrl":"10.1016/j.autcon.2025.106504","url":null,"abstract":"<div><div>Integrating climate change adaptation (CCA) and mitigation (CCM) into urban design remains a challenge due to methodological fragmentation and lack of cross-scalar tools. The Fourth Industrial Revolution offers transformative potential. This paper explores which digital enabling technologies (DETs) are most effective in supporting urban design scenarios addressing both CCA and CCM. A systematic literature review of 84 empirical studies was conducted, evaluating 12 DETs based on their capabilities in urban design scenario and climate performance. Results show that Remote Sensing, Geographic Information Systems (GIS), and Cloud Services are the most coherent technologies for combining climate with design workflows. Conversely, widely used tools like Building Information Modelling (BIM) show limited capacity to support ecological or carbon goals. These findings emphasise the necessity of interoperable, hybrid DET frameworks to enable CCA and CCM urban design. The paper offers insights for practitioners, paving the way for digitally enabled climate strategies in urban environments.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"180 ","pages":"Article 106504"},"PeriodicalIF":11.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144934151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Heavy lifting localization system using sliding window filtering and sequential quadratic programming for safe modular integrated construction 采用滑动窗口滤波和顺序二次规划的安全模块化集成结构的重吊装定位系统

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-02 DOI: 10.1016/j.autcon.2025.106473

Aimin Zhu, Zhiqian Zhang, Wei Pan

{"title":"Heavy lifting localization system using sliding window filtering and sequential quadratic programming for safe modular integrated construction","authors":"Aimin Zhu, Zhiqian Zhang, Wei Pan","doi":"10.1016/j.autcon.2025.106473","DOIUrl":"10.1016/j.autcon.2025.106473","url":null,"abstract":"<div><div>Heavy lifting is crucial in Modular integrated Construction (MiC), where ultra-wideband (UWB) technology can accurately track the lifting process for safe module installation. However, UWB's potential on lifting remains underutilized, particularly under non-line-of-sight propagation. This paper aims to develop a UWB-based Heavy Lifting Localization (HeLLo) system designed for achieving safe MiC during module lifting. The system integrates two lifting-specific localization models: Sliding Window Filtering-(Weighted) and Sequential Quadratic Programming models for line-of-sight and non-line-of-sight conditions, respectively. The system was verified using lab tests and computer simulations and was validated using a real-life MiC project. Results demonstrated that the HeLLo system's models outperformed other models such as Newton and Powell in accuracy and efficiency, achieving 25.66 cm in line-of-sight and 36.05 cm in non-line-of-sight accuracies within 1 ms. The HeLLo system ensures centimeter-level accuracy and millisecond-level efficiency to prevent lifting collisions, enhancing safety in MiC. The findings should stimulate the adoption of modular construction globally.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"179 ","pages":"Article 106473"},"PeriodicalIF":11.5,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond barriers: Stage-based and pathway-oriented conceptual model of resistance to BIM innovation 超越障碍：基于阶段和路径的BIM创新阻力概念模型

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-02 DOI: 10.1016/j.autcon.2025.106503

Yuanyuan Tan , Hanbing Wang , Ruopeng Huang , Daniel Hall , Ad Straub , Queena K. Qian

引用次数: 0

Vision-based automated cable tension monitoring using pixel tracking 使用像素跟踪的基于视觉的自动电缆张力监测

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-01 DOI: 10.1016/j.autcon.2025.106488

Dongyoung Ko , Minsoo Park , Sujin Jin , Pa Pa Win Aung , Seunghee Park

{"title":"Vision-based automated cable tension monitoring using pixel tracking","authors":"Dongyoung Ko , Minsoo Park , Sujin Jin , Pa Pa Win Aung , Seunghee Park","doi":"10.1016/j.autcon.2025.106488","DOIUrl":"10.1016/j.autcon.2025.106488","url":null,"abstract":"<div><div>Traditional methods for monitoring cable tension rely on indirect measurements such as cable vibrations and often require specialized calibration. These approaches limit the efficiency, and non-contact capability of tension monitoring across various structures. This paper presents a vision-based framework for automated cable tension monitoring, which directly captures image data of internal steel strands. By leveraging advanced computer vision techniques — such as zero-shot segmentation, depth estimation, edge detection, and dense pixel tracking — critical geometric parameters are extracted and integrated into a kinematic-based model for tension estimation. A calibration-free method for estimating real-world pixel size, derived from the helical geometry of the strands, enables field deployment without the need for camera setup information. Experimental results show strong correlation with reference data, achieving a mean absolute error of 4.94% under elastic conditions. These findings pave the way for a promising alternative in vision-based structural health monitoring for prestressed structures.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"179 ","pages":"Article 106488"},"PeriodicalIF":11.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AI applications for structural design automation 人工智能应用于结构设计自动化

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-09-01 DOI: 10.1016/j.autcon.2025.106496

Hao Xie, Qipei Mei, Ying Hei Chui

引用次数: 0

Multimodal data fusion for ergonomic assessment of construction workers in visually obstructed environments 视觉障碍环境下建筑工人工效学评估的多模态数据融合

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-30 DOI: 10.1016/j.autcon.2025.106495

Xinyu Chen , Yantao Yu , Yunpeng Wang , Zhen-Zhong Hu

{"title":"Multimodal data fusion for ergonomic assessment of construction workers in visually obstructed environments","authors":"Xinyu Chen , Yantao Yu , Yunpeng Wang , Zhen-Zhong Hu","doi":"10.1016/j.autcon.2025.106495","DOIUrl":"10.1016/j.autcon.2025.106495","url":null,"abstract":"<div><div>Work-related musculoskeletal disorders are the leading cause of nonfatal injuries in the construction industry. Ergonomic assessment methods can effectively prevent these disorders. Vision-based ergonomic risk assessment methods are widely applied in construction sites due to their cost-effectiveness and non-invasiveness. However, existing vision-based methods often face challenges in accurately estimating worker pose in real construction sites with visually obstructed environments, such as self-obstruction, object obstruction, and body parts out of view. Additionally, these methods lack consideration of external load factors for ergonomics. To overcome these issues, this paper proposes a multimodal ergonomic assessment method, combining visual data and pressure signals. Multimodal method integrates pressure and visual data in a unified feature space, improving pose estimation results and providing external load metrics for a more comprehensive ergonomic assessment. Field experiments show that the accuracy of pose estimation and risk assessment is enhanced, supporting the safety and health of construction workers.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"179 ","pages":"Article 106495"},"PeriodicalIF":11.5,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Natural language-extracted and BIM-referenced knowledge base for construction quality inspection via augmented reality 基于增强现实的自然语言提取和bim参考知识库

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-29 DOI: 10.1016/j.autcon.2025.106500

Han Liu , Donghai Liu , Junjie Chen

引用次数: 0

Enhancing visual-LLM for construction site safety compliance via prompt engineering and Bi-stage retrieval-augmented generation 通过快速工程和双阶段检索增强生成，增强建筑工地安全合规的可视化llm

IF 11.5 1区工程技术

Automation in Construction Pub Date : 2025-08-29 DOI: 10.1016/j.autcon.2025.106490

Koi Xiaowen Guo , Peter Kok-Yiu Wong , Jack C.P. Cheng , Chak-Fu Chan , Pak-Him Leung , Xingyu Tao

{"title":"Enhancing visual-LLM for construction site safety compliance via prompt engineering and Bi-stage retrieval-augmented generation","authors":"Koi Xiaowen Guo , Peter Kok-Yiu Wong , Jack C.P. Cheng , Chak-Fu Chan , Pak-Him Leung , Xingyu Tao","doi":"10.1016/j.autcon.2025.106490","DOIUrl":"10.1016/j.autcon.2025.106490","url":null,"abstract":"<div><div>The escalating frequency of safety incidents on construction sites requires an effective safety management framework. Traditional computer vision systems are constrained by their static nature, limited generalization, and inadequate semantic comprehension. This paper integrates a multi-modal Visual Language Model (VLM) with our proposed Bi-stage Retrieval-Augmented Generation (BiRAG) framework, which enhances safety compliance monitoring based on construction site images, with high scalability and adaptiveness to evolving safety standards without tedious model fine-tuning. A TriPhased prompt (TPP) and a decision-tree-based compliance judgment prompt are designed to enhance the VLM's ability to interpret worker behaviors and safety compliance from site images. A context-aware chunking strategy and hybrid retrieval algorithm are developed to improve the analysis against relevant safety regulations. Experiments with images collected from a real construction site in Hong Kong demonstrated a 7.73 % increase in retrieval accuracy and an 11.66 % improvement in compliance analysis accuracy, offering a holistic construction safety management solution.</div></div>","PeriodicalId":8660,"journal":{"name":"Automation in Construction","volume":"179 ","pages":"Article 106490"},"PeriodicalIF":11.5,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0