Novel Direct Multi-View Terrestrial Laser Scanner Data Registration Using Range, Polar and Azimuthal Angles Uncertainties DOI
Janusz Będkowski

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Data integration using deep learning and real-time locating system (RTLS) for automated construction progress monitoring and reporting DOI Creative Commons
Dena Shamsollahi,

Osama Moselhi,

Khashayar Khorasani

et al.

Automation in Construction, Journal Year: 2024, Volume and Issue: 168, P. 105778 - 105778

Published: Sept. 23, 2024

Language: Английский

Citations

4
Centerline-based registration for shield tunnel 3D reconstruction using spinning mid-range LiDAR point cloud and multi-cameras DOI
Liao Jian, Wenge Qiu, Yunjian Cheng

et al.

Automation in Construction, Journal Year: 2025, Volume and Issue: 171, P. 105950 - 105950

Published: Jan. 10, 2025

Language: Английский

Citations

0
Understanding digital construction management DOI
Clinton Aigbavboa, Ernest Kissi

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 38

Published: Jan. 1, 2025

Language: Английский

Citations

0
Indoor visual positioning using stationary semantic distribution registration and building information modeling DOI
Xiaoping Zhou, Yukang Wang, Jichao Zhao

et al.

Automation in Construction, Journal Year: 2025, Volume and Issue: 172, P. 106033 - 106033

Published: Feb. 8, 2025

Language: Английский

Citations

0
SLAM-IMU coupling-based construction personnel positioning in invalid scenario of satellite and aerial triangulation DOI
Yang Gao, Wang Chen,

Liping Huang

et al.

Engineering Construction & Architectural Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Purpose To help supervisors understand the positions of workers in real-time, provide safety guidance for and reduce occurrence accidents. This study proposes a real-time positioning algorithm based on multi-source information coupling, aiming to solve problem workers’ autonomous signal-blind areas. Design/methodology/approach The proposed utilizes visual SLAM IMU sensors perceive environment, construct three-dimensional images, improve accuracy corner point matching, pre-integrate raw data, adopt tightly coupled method couple inertial navigation thereby establishing binocular coupling model. Findings technology shows good effect calculation speed indoor sites, has adaptability different building construction scenarios, error can be controlled within 3%. Originality/value successful effectively alleviates inaccurate caused by signal blind areas existing management system, helps protect lives site improves efficiency supervisors.

Language: Английский

Citations

0
Unsupervised video object segmentation for enhanced SLAM-based localization in dynamic construction environments DOI
Yang Liu, Hubo Cai

Automation in Construction, Journal Year: 2023, Volume and Issue: 158, P. 105235 - 105235

Published: Dec. 11, 2023

Language: Английский

Citations

6
Hierarchical Clustering-Based Image Retrieval for Indoor Visual Localization DOI Open Access
Guanyuan Feng, Zhengang Jiang, Xuezhi Tan

et al.

Electronics, Journal Year: 2022, Volume and Issue: 11(21), P. 3609 - 3609

Published: Nov. 4, 2022

Visual localization is employed for indoor navigation and embedded in various applications, such as augmented reality mixed reality. Image retrieval geometrical measurement are the primary steps visual localization, key to improving efficiency reduce time consumption of image retrieval. Therefore, a hierarchical clustering-based image-retrieval method proposed hierarchically organize an off-line database, resulting control within reasonable range. The database organized by two stages: scene-level clustering sub-scene-level clustering. In clustering, improved cumulative sum algorithm detect change points then group images global features. On basis feature tracking-based introduced further into clusters. An with backtracking mechanism designed applied localization. addition, weighted KNN-based presented, estimated query position solved Armijo–Goldstein algorithm. Experimental results indicate that running does not linearly increase size databases, which beneficial efficiency.

Language: Английский

Citations

9
Two-stage RFID approach for localizing objects in smart homes based on gradient boosted decision trees with under- and over-sampling DOI Open Access
Shadi Abudalfa, Kévin Bouchard

Journal of Reliable Intelligent Environments, Journal Year: 2023, Volume and Issue: 10(1), P. 45 - 54

Published: Jan. 12, 2023

Language: Английский

Citations

5
Pose Graph Relocalization with Deep Object Detection and BIM-Supported Object Landmark Dictionary DOI
Jack C.P. Cheng, Changhao Song, Xiao Zhang

et al.

Journal of Computing in Civil Engineering, Journal Year: 2023, Volume and Issue: 37(5)

Published: May 19, 2023

Indoor localization is a prerequisite for autonomous robot applications in the construction industry. However, traditional techniques rely on low-level features and do not exploit construction-related semantics. They also are sensitive to environmental factors such as illumination reflection rate, therefore suffer from unexpected drifts failures. This study proposes pose graph relocalization framework that utilizes object-level landmarks enhance visual system. The proposed builds an object landmark dictionary Building Information Model (BIM) prior knowledge. Then multimodal deep neural network (DNN) realize 3D detection real time, followed by instance-level association with false-positive rejection, relative estimation outlier removal. Finally, keyframe-based optimization performed rectify of localization. was validated using mobile platform red-green-blue-depth (RGB-D) inertial sensors, test scene indoor office environment furnishing elements. model achieved 62.9% mean average precision (mAP). technique reduced translational 64.67% rotational 41.59% compared visual–inertial odometry.

Language: Английский

Citations

5
Seamless Fusion: Multi-Modal Localization for First Responders in Challenging Environments DOI Creative Commons

Dennis Dahlke,

Petros Drakoulis, Anaida Fernández García

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(9), P. 2864 - 2864

Published: April 30, 2024

In dynamic and unpredictable environments, the precise localization of first responders rescuers is crucial for effective incident response. This paper introduces a novel approach leveraging three complementary modalities: visual-based, Galileo-based, inertial-based. Each modality contributes uniquely to final Fusion tool, facilitating seamless indoor outdoor localization, offering robust accurate solution without reliance on pre-existing infrastructure, essential maintaining responder safety optimizing operational effectiveness. The visual-based method utilizes an RGB camera coupled with modified implementation ORB-SLAM2 method, enabling operation or prior area scanning. Galileo-based employs lightweight prototype equipped high-accuracy GNSS receiver board, tailored meet specific needs responders. inertial-based sensor fusion, primarily smartphone inertial measurement units, predict adjust responders’ positions incrementally, compensating GPS signal attenuation indoors. A comprehensive validation test involving various environmental conditions was carried out demonstrate efficacy proposed fused tool. Our results show that our always provides location regardless (indoors, outdoors, etc.), overall mean error 1.73 m.

Language: Английский

Citations

1