TY - GEN
T1 - Conceptual Design of a Robotic Building Envelope Assessment System for Energy Efficiency
AU - Xu, Xuchu
AU - Lu, Daniel
AU - Sher, Bilal
AU - Kim, Sunglyoung
AU - Rathod, Abhishek
AU - Ergan, Semiha
AU - Feng, Chen
N1 - Publisher Copyright:
© 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Building air leakage and moisture issues can result in significant energy loss, shorten the building envelope life cycle, and require additional maintenance costs. While these issues present risks to a building and its occupants, they could be difficult to detect during building maintenance and early stages of retrofit projects. Currently, mapping air leakage and moisture issues over a building’s envelope relies on manual inspections. These methods are intrusive, expensive, and hazardous to inspectors’ safety. To address these challenges, we propose a non-invasive and safe conceptual solution, a Robotic Envelope Assessment System for Energy Efficiency (EASEEbot), to locate and document moisture intrusion, thermal bridges, and air leaks. EASEEbot is a high-power wall climbing drone and comes with a multi-function toolbox. It can capture 3D thermal images and auto-generate 3D models using image-based Structure from Motion (SfM) and Visual Simultaneous Localization and Mapping (VSLAM). Our deep learning algorithms will rapidly identify common building envelope defects from multi-modal sensing data. EASEEbot is also designed with a tethered wall-climbing mode and will use long-wave ground penetrating radar (GPR) to detect hidden trapped interstitial moisture and other major envelope defects.
AB - Building air leakage and moisture issues can result in significant energy loss, shorten the building envelope life cycle, and require additional maintenance costs. While these issues present risks to a building and its occupants, they could be difficult to detect during building maintenance and early stages of retrofit projects. Currently, mapping air leakage and moisture issues over a building’s envelope relies on manual inspections. These methods are intrusive, expensive, and hazardous to inspectors’ safety. To address these challenges, we propose a non-invasive and safe conceptual solution, a Robotic Envelope Assessment System for Energy Efficiency (EASEEbot), to locate and document moisture intrusion, thermal bridges, and air leaks. EASEEbot is a high-power wall climbing drone and comes with a multi-function toolbox. It can capture 3D thermal images and auto-generate 3D models using image-based Structure from Motion (SfM) and Visual Simultaneous Localization and Mapping (VSLAM). Our deep learning algorithms will rapidly identify common building envelope defects from multi-modal sensing data. EASEEbot is also designed with a tethered wall-climbing mode and will use long-wave ground penetrating radar (GPR) to detect hidden trapped interstitial moisture and other major envelope defects.
KW - Building Envelope Inspection
KW - Building Moisture
KW - Remote Inspection System
KW - Thermal Leak Detection
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M3 - Conference contribution
AN - SCOPUS:85127611997
T3 - Proceedings of the International Symposium on Automation and Robotics in Construction
SP - 653
EP - 660
BT - Proceedings of the 38th International Symposium on Automation and Robotics in Construction, ISARC 2021
A2 - Feng, Chen
A2 - Linner, Thomas
A2 - Brilakis, Ioannis
PB - International Association for Automation and Robotics in Construction (IAARC)
T2 - 38th International Symposium on Automation and Robotics in Construction, ISARC 2021
Y2 - 2 November 2021 through 4 November 2021
ER -