Robot-assisted object detection for construction automation : data and information-driven approach
In construction automation, robotics solution is becoming an emerging technology with the advent of artificial intelligence and advancement in mechatronic systems. In construction buildings, regular inspections are carried out to ensure project completion as per approved plans and quality standards....
| Main Authors: | , , , , , |
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| Format: | Journal Article |
| Language: | English |
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2021
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| Online Access: | https://hdl.handle.net/10356/153478 |
| _version_ | 1811681703642529792 |
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| author | Muhammad Ilyas Khaw, Hui Ying Selvaraj, Nithish Muthuchamy Jin, Yuxin Zhao, Xinge Cheah, Chien Chern |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Muhammad Ilyas Khaw, Hui Ying Selvaraj, Nithish Muthuchamy Jin, Yuxin Zhao, Xinge Cheah, Chien Chern |
| author_sort | Muhammad Ilyas |
| collection | NTU |
| description | In construction automation, robotics solution is becoming an emerging technology with the advent of artificial intelligence and advancement in mechatronic systems. In construction buildings, regular inspections are carried out to ensure project completion as per approved plans and quality standards. Currently, expert human inspectors are deployed onsite to perform inspection tasks with the naked eye and conventional tools. This process is time-consuming, labor-intensive, dangerous, repetitive, and may yield subjective results. In this paper, we propose a robotic system equipped with perception sensors and intelligent algorithms to help construction supervisors remotely identify the construction materials, detect component installations and defects, and generate report of their status and location information. Building Information Model (BIM) is used for mobile robot navigation and to retrieve building component's location information. Unlike the current deep learning-based object detection which depends heavily on training data, this work proposes a data and information-driven approach which incorporates offline training data, sensor data and BIM information to achieve BIM-based object coverage navigation, BIM-based false detection filtering, and a fine manoeuvre technique to improve on object detections during real-time automated task execution by robots. This allows the user to select building components to be inspected and the mobile robot navigates autonomously to the target components using BIM generated navigation map. An object detector then detects the building components and materials and generates an inspection report. The proposed system is verified through laboratory and onsite experiments. |
| first_indexed | 2024-10-01T03:45:10Z |
| format | Journal Article |
| id | ntu-10356/153478 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:45:10Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1534782021-12-07T13:31:34Z Robot-assisted object detection for construction automation : data and information-driven approach Muhammad Ilyas Khaw, Hui Ying Selvaraj, Nithish Muthuchamy Jin, Yuxin Zhao, Xinge Cheah, Chien Chern School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Robot-Assisted Object Detection Construction Inspection Intelligent Monitoring Building Information Model BIM-Based Navigation Object Coverage In construction automation, robotics solution is becoming an emerging technology with the advent of artificial intelligence and advancement in mechatronic systems. In construction buildings, regular inspections are carried out to ensure project completion as per approved plans and quality standards. Currently, expert human inspectors are deployed onsite to perform inspection tasks with the naked eye and conventional tools. This process is time-consuming, labor-intensive, dangerous, repetitive, and may yield subjective results. In this paper, we propose a robotic system equipped with perception sensors and intelligent algorithms to help construction supervisors remotely identify the construction materials, detect component installations and defects, and generate report of their status and location information. Building Information Model (BIM) is used for mobile robot navigation and to retrieve building component's location information. Unlike the current deep learning-based object detection which depends heavily on training data, this work proposes a data and information-driven approach which incorporates offline training data, sensor data and BIM information to achieve BIM-based object coverage navigation, BIM-based false detection filtering, and a fine manoeuvre technique to improve on object detections during real-time automated task execution by robots. This allows the user to select building components to be inspected and the mobile robot navigates autonomously to the target components using BIM generated navigation map. An object detector then detects the building components and materials and generates an inspection report. The proposed system is verified through laboratory and onsite experiments. Agency for Science, Technology and Research (A*STAR) Accepted version This work is supported by the Agency For Science, Technology and Research of Singapore (A*STAR), Singapore, under the National Robotics Program (NRP)-Robotics Domain Specific (RDS: Ref. 1922200001). 2021-12-07T13:31:33Z 2021-12-07T13:31:33Z 2021 Journal Article Muhammad Ilyas, Khaw, H. Y., Selvaraj, N. M., Jin, Y., Zhao, X. & Cheah, C. C. (2021). Robot-assisted object detection for construction automation : data and information-driven approach. IEEE/ASME Transactions On Mechatronics. https://dx.doi.org/10.1109/TMECH.2021.3100306 1083-4435 https://hdl.handle.net/10356/153478 10.1109/TMECH.2021.3100306 2-s2.0-85111589102 en 1922200001 IEEE/ASME Transactions on Mechatronics © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TMECH.2021.3100306. application/pdf |
| spellingShingle | Engineering::Electrical and electronic engineering Robot-Assisted Object Detection Construction Inspection Intelligent Monitoring Building Information Model BIM-Based Navigation Object Coverage Muhammad Ilyas Khaw, Hui Ying Selvaraj, Nithish Muthuchamy Jin, Yuxin Zhao, Xinge Cheah, Chien Chern Robot-assisted object detection for construction automation : data and information-driven approach |
| title | Robot-assisted object detection for construction automation : data and information-driven approach |
| title_full | Robot-assisted object detection for construction automation : data and information-driven approach |
| title_fullStr | Robot-assisted object detection for construction automation : data and information-driven approach |
| title_full_unstemmed | Robot-assisted object detection for construction automation : data and information-driven approach |
| title_short | Robot-assisted object detection for construction automation : data and information-driven approach |
| title_sort | robot assisted object detection for construction automation data and information driven approach |
| topic | Engineering::Electrical and electronic engineering Robot-Assisted Object Detection Construction Inspection Intelligent Monitoring Building Information Model BIM-Based Navigation Object Coverage |
| url | https://hdl.handle.net/10356/153478 |
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