Robots in Inspection and Monitoring of Buildings and Infrastructure: A Systematic Review

被引:87
作者
Halder, Srijeet [1 ]
Afsari, Kereshmeh [1 ]
机构
[1] Virginia Tech, Myers Lawson Sch Construct, Blacksburg, VA 24061 USA
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 04期
基金
美国国家科学基金会;
关键词
construction robots; project monitoring; robotic inspection; construction automation; autonomous robots; mobile robots; VISUAL INSPECTION; CONSTRUCTION; UAV; REQUIREMENTS; COMPONENTS; MANAGEMENT; SAFETY; DEFECT;
D O I
10.3390/app13042304
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Regular inspection and monitoring of buildings and infrastructure, that is collectively called the built environment in this paper, is critical. The built environment includes commercial and residential buildings, roads, bridges, tunnels, and pipelines. Automation and robotics can aid in reducing errors and increasing the efficiency of inspection tasks. As a result, robotic inspection and monitoring of the built environment has become a significant research topic in recent years. This review paper presents an in-depth qualitative content analysis of 269 papers on the use of robots for the inspection and monitoring of buildings and infrastructure. The review found nine different types of robotic systems, with unmanned aerial vehicles (UAVs) being the most common, followed by unmanned ground vehicles (UGVs). The study also found five different applications of robots in inspection and monitoring, namely, maintenance inspection, construction quality inspection, construction progress monitoring, as-built modeling, and safety inspection. Common research areas investigated by researchers include autonomous navigation, knowledge extraction, motion control systems, sensing, multi-robot collaboration, safety implications, and data transmission. The findings of this study provide insight into the recent research and developments in the field of robotic inspection and monitoring of the built environment and will benefit researchers, and construction and facility managers, in developing and implementing new robotic solutions.
引用
收藏
页数:37
相关论文
共 269 条
[1]   Effectiveness of VR-based training on improving construction workers' knowledge, skills, and safety behavior in robotic teleoperation [J].
Adami, Pooya ;
Rodrigues, Patrick B. ;
Woods, Peter J. ;
Becerik-Gerber, Burcin ;
Soibelman, Lucio ;
Copur-Gencturk, Yasemin ;
Lucas, Gale .
ADVANCED ENGINEERING INFORMATICS, 2021, 50
[2]  
Adan A., 2019, ADV INFORM COMPUTING, P489, DOI DOI 10.1007/978-3-030-00220-6_58
[3]  
Afsari K., 2021, ASC INT P ANN C, P271
[4]  
Afsari K, 2022, CONSTRUCTION RESEARCH CONGRESS 2022: COMPUTER APPLICATIONS, AUTOMATION, AND DATA ANALYTICS, P610
[5]   A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection [J].
Agnisarman, Sruthy ;
Lopes, Snowil ;
Madathil, Kapil Chalil ;
Piratla, Kalyan ;
Gramopadhye, Anand .
AUTOMATION IN CONSTRUCTION, 2019, 97 :52-76
[6]  
Al-Hussein M., 2019, ISARC, P544
[7]   VBII-UAV: Vision-Based Infrastructure Inspection-UAV [J].
Al-Kaff, Abdulla ;
Miguel Moreno, Francisco ;
San Jose, Luis Javier ;
Garcia, Fernando ;
Martin, David ;
de la Escalera, Arturo ;
Nieva, Alberto ;
Meana Garcea, Jose Luis .
RECENT ADVANCES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, 2017, 570 :221-231
[8]   Increasing the robustness of material-specific deep learning models for crack detection across different materials [J].
Alipour, Mohamad ;
Harris, Devin K. .
ENGINEERING STRUCTURES, 2020, 206
[9]   A Multimodal Emotion Detection System during Human-Robot Interaction [J].
Alonso-Martin, Fernando ;
Malfaz, Maria ;
Sequeira, Joao ;
Gorostiza, Javier F. ;
Salichs, Miguel A. .
SENSORS, 2013, 13 (11) :15549-15581
[10]  
Andriani N, 2016, INT CONF INFORM COMM, P124, DOI 10.1109/ICTS.2016.7910285