Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works

Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, create documents for safety, and inspect existing structures, particularly for hard-to-reach areas. The purpose of this paper is to provide a concise review of the most recent methods that streamline collection, analysis, visualization, and communication of the visual data captured from these platforms, with and without using Building Information Models (BIM) as a priori information. Specifically, the most relevant works from Civil Engineering, Computer Vision, and Robotics communities are presented and compared in terms of their potential to lead to automatic construction monitoring and civil infrastructure condition assessment.

[1]  Youngjib Ham,et al.  3D as-is building energy modeling and diagnostics: A review of the state-of-the-art , 2015, Adv. Eng. Informatics.

[2]  Meng-Han Tsai,et al.  A review of rotorcraft Unmanned Aerial Vehicle (UAV) developments and applications in civil engineering , 2014 .

[3]  Burcin Becerik-Gerber,et al.  A Data Quality-Driven Framework for Asset Condition Assessment Using LiDAR and Image Data , 2015 .

[4]  Jiaojiao Gao,et al.  Research on the application of UAV Remote Sensing in Geologic Hazards Investigation for Oil and Gas Pipelines , 2011 .

[5]  David A. Forsyth,et al.  ConstructAide: analyzing and visualizing construction sites through photographs and building models , 2014, ACM Trans. Graph..

[6]  Fabio Remondino,et al.  3d Surveying and modelling of the Archaeological Area of Paestum, Italy , 2015 .

[7]  Carl T. Haas,et al.  State of research in automatic as-built modelling , 2015, Adv. Eng. Informatics.

[8]  Kazuya Yoshida,et al.  Collaborative mapping of an earthquake‐damaged building via ground and aerial robots , 2012, J. Field Robotics.

[9]  Chunsun Zhang,et al.  An Unmanned Aerial Vehicle‐Based Imaging System for 3D Measurement of Unpaved Road Surface Distresses 1 , 2012, Comput. Aided Civ. Infrastructure Eng..

[10]  Chen-Ming Kuo,et al.  Unmanned Aircraft Systems for Remote Building Inspection and Monitoring , 2012 .

[11]  G. Vosselman,et al.  SEGMENTATION OF UAV-BASED IMAGES INCORPORATING 3D POINT CLOUD INFORMATION , 2015 .

[12]  Jochen Teizer,et al.  Status quo and open challenges in vision-based sensing and tracking of temporary resources on infrastructure construction sites , 2015, Adv. Eng. Informatics.

[13]  Roland Siegwart,et al.  Vision based MAV navigation in unknown and unstructured environments , 2010, 2010 IEEE International Conference on Robotics and Automation.

[14]  Horst Bischof,et al.  Interactive 4D overview and detail visualization in augmented reality , 2012, 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[15]  Vijay Kumar,et al.  Cooperative localization and mapping of MAVs using RGB-D sensors , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[16]  Shih-Chung Kang,et al.  Augmented Reality and Unmanned Aerial Vehicle Assist in Construction Management , 2014 .

[17]  Jochen Teizer,et al.  Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system , 2014 .

[18]  Norman Kerle,et al.  Urban structural damage assessment with oblique UAV imagery, object-based image analysis and semantic reasoning , 2014 .

[19]  Z. Lin,et al.  STUDY ON CONSTRUCTION OF 3D BUILDING BASED ON UAV IMAGES , 2012 .

[20]  Horst Bischof,et al.  AVSS 2011 demo session: Construction site monitoring from highly-overlapping MAV images , 2011, AVSS.

[21]  Anu Pradhan,et al.  Automated Detection of Damaged Areas after Hurricane Sandy using Aerial Color Images , 2014 .

[22]  T. Katayama,et al.  MEASUREMENT OF LARGE-SCALE SOLAR POWER PLANT BY USING IMAGES ACQUIRED BY NON-METRIC DIGITAL CAMERA ON BOARD UAV , 2012 .

[23]  Tom Drummond,et al.  Image based optimisation without global consistency for constant time monocular visual SLAM , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[24]  Norman Kerle,et al.  UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning , 2014 .

[25]  Tsuyoshi Yamamoto,et al.  Data Collection System for a Rapid Recovery Work: Using Digital Photogrammetry and a Small Unmanned Aerial Vehicle (UAV) , 2014 .

[26]  Javier Irizarry,et al.  UAS4SAFETY: The Potential of Unmanned Aerial Systems for Construction Safety Applications , 2014 .

[27]  Horst Bischof,et al.  Augmented Reality for Construction Site Monitoring and Documentation , 2014, Proceedings of the IEEE.

[28]  Rongjun Qin,et al.  An Object-Based Hierarchical Method for Change Detection Using Unmanned Aerial Vehicle Images , 2014, Remote. Sens..

[29]  Richard J. Dobson,et al.  Developing an unpaved road assessment system for practical deployment with high-resolution optical data collection using a helicopter UAV , 2013, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[30]  O. Hellwich,et al.  Three-Dimensional Building Reconstruction Using Images Obtained by Unmanned Aerial Vehicles , 2012 .

[31]  Javier Irizarry,et al.  Usability assessment of drone technology as safety inspection tools , 2012, J. Inf. Technol. Constr..

[32]  Frédéric Bosché,et al.  As-built data acquisition and its use for production monitoring and automated layout in civil infrastructure: a survey , 2015 .

[33]  Ji Zhang,et al.  LOAM: Lidar Odometry and Mapping in Real-time , 2014, Robotics: Science and Systems.

[34]  Patricio A. Vela,et al.  Construction performance monitoring via still images, time-lapse photos, and video streams: Now, tomorrow, and the future , 2015, Adv. Eng. Informatics.