Article
Engineering, Civil
Feng Wang, Yang Zou, Enrique del Rey Castillo, Youliang Ding, Zhao Xu, Hanwei Zhao, James B. P. Lim
Summary: This paper proposes a novel Building Information Model (BIM)-based 3D path planning method to improve the quality of photogrammetric bridge models by optimizing the UAV flight plan. Through testing on a real bridge, the results show that this method can generate more accurate and higher quality bridge models, and improve the efficiency of photogrammetric 3D bridge reconstruction.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2022)
Article
Computer Science, Information Systems
Yuanlong Li, Shang Gao, Xuewen Liu, Peiliang Zuo, Haoliang Li
Summary: This paper focuses on the automated inspection business of unmanned aerial vehicles (UAVs) dispatched by automated airports in highway scenarios. By considering the shape of highway curves, inspection targets, and the energy consumption characteristics of UAVs, the flight parameters of UAVs are planned using an efficient heuristic method. The simulation and analysis results show that the proposed method possesses good parameter planning efficiency and overall planning performance.
Article
Engineering, Electrical & Electronic
Wenzheng Zhao, Xueqi Wang, Yinhua Liu
Summary: This study proposes a five-axis CMM inspection path planning method, aiming to improve the efficiency of inspecting complex machining parts by considering path length, probe rotation, and path reusability. The method utilizes various algorithms for path planning and demonstrates its effectiveness through a case study.
Review
Computer Science, Artificial Intelligence
Md Shah Alam, Jared Oluoch
Summary: The detection of safe landing zones for UAVs has become crucial in the age of automation, with UAVs needing to determine the safety of landing areas using onboard sensors for ground information. Image processing and algorithms are used to identify optimal landing points, while existing techniques are critiqued and areas for future improvement are pinpointed. Despite shortcomings, current technologies provide guidance for future advancements and research in safe landing zone detection.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Chemistry, Analytical
Iago Z. Biundini, Milena F. Pinto, Aurelio G. Melo, Andre L. M. Marcato, Leonardo M. Honorio, Maria J. R. Aguiar
Summary: Various practical applications have emerged in recent years, requiring periodic inspections to verify structural changes. The Coverage Path Planning aims to find the best inspection path while respecting operation restrictions. By optimizing inspection paths using photometric information, efficiency is effectively improved.
Article
Energy & Fuels
Min Wu, Wuhua Chen, Xiaohong Tian
Summary: This study proposes an energy consumption model for UAV transmission tower inspections and designs an optimized energy consumption path based on the simulated annealing algorithm. Through data collection and analysis, an energy consumption model is established and energy consumption coefficients under different situations are obtained. The effectiveness of the optimized energy consumption path is verified through experimental simulations and actual measurements. The simulation results show that the proposed path can save energy compared to the conventional and shortest paths.
Article
Remote Sensing
Yufeng Sun, Ou Ma
Summary: This paper presents a two-stage approach of automating aircraft scanning with an unmanned aerial vehicle (UAV) equipped with a RGB-D camera. In the first stage, the UAV scans the aircraft from a safe distance to quickly generate a coarse model. In the second stage, an optimal scanning path is computed to closely inspect the surface or generate a dense model. Experimental results showed that this approach is more efficient than manual scanning.
Article
Computer Science, Artificial Intelligence
Manh Duong Phung, Quang Phuc Ha
Summary: This paper introduces a new algorithm named SPSO for UAV path planning, and demonstrates its superiority over other optimization algorithms in various scenarios through comparative experiments.
APPLIED SOFT COMPUTING
(2021)
Article
Mathematics
Faten Aljalaud, Heba Kurdi, Kamal Youcef-Toumi
Summary: This paper presents a novel path planning heuristic inspired by the booby bird's foraging behavior for multi-UAV pipe inspection missions. The heuristic enables each UAV to find an optimal path for defect detection in pipe networks while avoiding collisions. The proposed method outperforms existing algorithms in terms of mean detection time and computational efficiency under different settings.
Article
Remote Sensing
Hannes Brassel, Thomas Zeh, Hartmut Fricke, Anette Eltner
Summary: With unmanned aerial vehicles, quick responses to urgent needs can be realized, but geographical zones restrict their usage. This study combines facility location problem and routing problem to optimize hangar locations and UAV mission trajectories, considering geographical zones, battery constraints, and wind impact. Water rescue missions are used as an example, and the solution decreases the average service time from 570.4s to 351.1s for one hangar and 287.2s for two hangars.
Article
Environmental Sciences
Yinghao Zhao, Li Yan, Yu Chen, Jicheng Dai, Yuxuan Liu
Summary: This paper introduces a robust and efficient trajectory replanning method based on the guiding path for UAV path planning in unknown cluttered environments. By generating a safe guiding path, designing a guided kinodynamic path searching method, and proposing an adaptive optimization function, the proposed method significantly improves the quality and success rate of path planning.
Article
Construction & Building Technology
Changhao Song, Zhengyi Chen, Kai Wang, Han Luo, Jack C. P. Cheng
Summary: This study developed a Building Information Model (BIM)-supported framework to facilitate scan planning and motion planning of autonomous LiDAR-carrying UAVs. Through validation in a simulated construction scenario of water treatment facilities, the planned trajectory demonstrated smoothness, energy efficiency, and sufficient scan coverage.
AUTOMATION IN CONSTRUCTION
(2022)
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
Remote Sensing
Yu Chen, Qi Dong, Xiaozhou Shang, Zhenyu Wu, Jinyu Wang
Summary: Unmanned aerial vehicles (UAVs) are important for reconnaissance missions, but face decision challenges in dynamic and partially observable environments. To address this, we proposed a multi-UAV path planning algorithm based on multi-agent reinforcement learning. By adopting a centralized training-decentralized execution architecture and utilizing the hidden state of a recurrent neural network, we solved the issues of incomplete information and low efficiency in reinforcement learning.
Review
Multidisciplinary Sciences
Faiyaz Ahmed, J. C. Mohanta, Anupam Keshari, Pankaj Singh Yadav
Summary: This article provides a comprehensive survey and overview of commercially available UAVs, highlighting their developments in the past decade. It presents a roadmap for the advancements in terms of structure, mechanism, sensing ability, path planning, and more. The survey also identifies the relevant methodologies and applications in the field.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(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)