scholarly journals Vision-assisted BIM reconstruction from 3D LiDAR point clouds for MEP scenes

2022 ◽  
Vol 133 ◽  
pp. 103997
Author(s):  
Boyu Wang ◽  
Qian Wang ◽  
Jack C.P. Cheng ◽  
Changhao Song ◽  
Chao Yin
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2016 ◽  
Vol 5 (5) ◽  
pp. 60 ◽  
Author(s):  
Miaole Hou ◽  
Shukun Li ◽  
Lili Jiang ◽  
Yuhua Wu ◽  
Yungang Hu ◽  
...  

Author(s):  
Boyang Li ◽  
Hao Meng ◽  
Yuzhang Zhu ◽  
Rihui Song ◽  
Mingyue Cui ◽  
...  
Keyword(s):  

2019 ◽  
Vol 8 (3) ◽  
pp. 144 ◽  
Author(s):  
Marek Kulawiak ◽  
Marcin Kulawiak ◽  
Zbigniew Lubniewski

The rapid increase in applications of Light Detection and Ranging (LiDAR) scanners, followed by the development of various methods that are dedicated for survey data processing, visualization, and dissemination constituted the need of new open standards for storage and online distribution of collected three-dimensional data. However, over a decade of research in the area has resulted in a number of incompatible solutions that offer their own ways of disseminating results of LiDAR surveys (be it point clouds or reconstructed three-dimensional (3D) models) over the web. The article presents a unified system for remote processing, storage, visualization, and dissemination of 3D LiDAR survey data, including 3D model reconstruction. It is built with the use of open source technologies and employs open standards, such as 3D Tiles, LASer (LAS), and Object (OBJ) for data distribution. The system has been deployed for automatic organization, processing, and dissemination of LiDAR surveys that were performed in the city of Gdansk. The performance of the system has been measured using a selection of LiDAR datasets of various sizes. The system has shown to considerably simplify the process of data organization and integration, while also delivering tools for easy discovery, inspection, and acquisition of desired datasets.


Data in Brief ◽  
2020 ◽  
Vol 29 ◽  
pp. 105248 ◽  
Author(s):  
Jordi Gené-Mola ◽  
Eduard Gregorio ◽  
Fernando Auat Cheein ◽  
Javier Guevara ◽  
Jordi Llorens ◽  
...  

2020 ◽  
Vol 44 (4) ◽  
pp. 530-540
Author(s):  
Michael R. Wrock ◽  
Scott B. Nokleby

In this work, an approach to generating a set of via points for use in manipulator trajectory path planning is presented. The approach was developed for use on a robotic underground mining system, particularly for the task of autonomous application of a sprayable concrete called shotcrete. A LiDAR (light detection and ranging) scanner on a nodding head produces point clouds that are used as the input for the via-point selection algorithm. The algorithm generates a set of position and orientation via points that the manipulator must follow to perform the shotcreting task. The developed algorithm has been successfully tested on an autonomous mobile-manipulator system in a scaled mock-up of an underground mine. The main advantage of this algorithm is the ability to generate via points for any section of an underground mine in any position relative to the robot.


Author(s):  
Antonio Pomares ◽  
Jorge L. Martinez ◽  
Anthony Mandow ◽  
Maria A. Martinez ◽  
Mariano Moran ◽  
...  
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Author(s):  
B. Douillard ◽  
J. Underwood ◽  
N. Kuntz ◽  
V. Vlaskine ◽  
A. Quadros ◽  
...  
Keyword(s):  

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