Platform-independent visual installation progress monitoring for construction automation
Efficient interior progress monitoring is crucial for the timely completion of construction projects. Although robots have been used for data acquisition to automate interior progress monitoring, existing methods do not adequately consider the variations of robot platforms and different types of con...
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sg-ntu-dr.10356-1713712023-10-23T05:45:08Z Platform-independent visual installation progress monitoring for construction automation Zhao, Xinge Jin, Yuxin Selvaraj, Nithish Muthuchamy Muhammad Ilyas Cheah, Chien Chern School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Construction Progress Monitoring Robotics For Construction Automation Efficient interior progress monitoring is crucial for the timely completion of construction projects. Although robots have been used for data acquisition to automate interior progress monitoring, existing methods do not adequately consider the variations of robot platforms and different types of construction environments, which makes it challenging to apply these methods to various robots and environments. This paper proposes an integrated system that achieves automated interior installation progress monitoring, which can be applied to various construction environments and robot platforms. Algorithms are proposed to systematically generate navigation goal points for robot navigations based on BIM information of objects, which enables the detection of target objects with the proper viewing distance and angle. A transformer-based object detector is used to recognize the installation status of building elements, and a progress updating module is developed to correlate the detection results with the robot's sensory and BIM information to generate a construction progress report for interior installation. This framework hierarchically estimates the percentage of project completion and allows for tracking of the installation work progress. The proposed system has been verified through laboratory and onsite experiments using various platforms, including a mobile robot, a four-legged robot, a drone, and a smartphone camera. Agency for Science, Technology and Research (A*STAR) Building and Construction Authority (BCA) This work is supported by the Agency For Science, Technology and Research (A*STAR), Singapore, under the National Robotics Program (NRP)-Robotics Domain Specific (RDS: Ref. [1922200001]). Special thanks to Teambuild Construction Group, Singapore, and Building and Construction Authority (BCA), Singapore, for providing support and research resources. 2023-10-23T05:45:08Z 2023-10-23T05:45:08Z 2023 Journal Article Zhao, X., Jin, Y., Selvaraj, N. M., Muhammad Ilyas & Cheah, C. C. (2023). Platform-independent visual installation progress monitoring for construction automation. Automation in Construction, 154, 104996-. https://dx.doi.org/10.1016/j.autcon.2023.104996 0926-5805 https://hdl.handle.net/10356/171371 10.1016/j.autcon.2023.104996 2-s2.0-85164280932 154 104996 en 1922200001 Automation in Construction © 2023 Elsevier B.V. All rights reserved. |
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Engineering::Electrical and electronic engineering Construction Progress Monitoring Robotics For Construction Automation Zhao, Xinge Jin, Yuxin Selvaraj, Nithish Muthuchamy Muhammad Ilyas Cheah, Chien Chern Platform-independent visual installation progress monitoring for construction automation |
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Efficient interior progress monitoring is crucial for the timely completion of construction projects. Although robots have been used for data acquisition to automate interior progress monitoring, existing methods do not adequately consider the variations of robot platforms and different types of construction environments, which makes it challenging to apply these methods to various robots and environments. This paper proposes an integrated system that achieves automated interior installation progress monitoring, which can be applied to various construction environments and robot platforms. Algorithms are proposed to systematically generate navigation goal points for robot navigations based on BIM information of objects, which enables the detection of target objects with the proper viewing distance and angle. A transformer-based object detector is used to recognize the installation status of building elements, and a progress updating module is developed to correlate the detection results with the robot's sensory and BIM information to generate a construction progress report for interior installation. This framework hierarchically estimates the percentage of project completion and allows for tracking of the installation work progress. The proposed system has been verified through laboratory and onsite experiments using various platforms, including a mobile robot, a four-legged robot, a drone, and a smartphone camera. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Zhao, Xinge Jin, Yuxin Selvaraj, Nithish Muthuchamy Muhammad Ilyas Cheah, Chien Chern |
format |
Article |
author |
Zhao, Xinge Jin, Yuxin Selvaraj, Nithish Muthuchamy Muhammad Ilyas Cheah, Chien Chern |
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Zhao, Xinge |
title |
Platform-independent visual installation progress monitoring for construction automation |
title_short |
Platform-independent visual installation progress monitoring for construction automation |
title_full |
Platform-independent visual installation progress monitoring for construction automation |
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Platform-independent visual installation progress monitoring for construction automation |
title_full_unstemmed |
Platform-independent visual installation progress monitoring for construction automation |
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platform-independent visual installation progress monitoring for construction automation |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/171371 |
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