Framework for Location Data Fusion and Pose Estimation of Excavators Using Stereo Vision

Soltani, Mohammad Mostafa; Zhu, Zhenhua; Hammad, Amin

doi:10.1061/(asce)cp.1943-5487.0000783

Cited by 81 publications

(32 citation statements)

References 37 publications

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“…The stereo-cameras and triangulation theory were also used to obtain the detailed 3D postures of excavators in one study (Yuan et al, 2017). Soltani et al (2018) further integrated the stereo systems with location sensors (e.g., global positioning systems) for 3D pose estimation of excavators. However, as it is not common to install stereo-cameras on actual jobsites, Konstantinou and Brilakis (2018) proposed an approach that matches construction workers from four different monocular cameras in indoor environments.…”

Section: Multi-camera-based Onsite Information Integration and Constrmentioning

confidence: 99%

“…Previous research confirmed the potential usefulness of location and identity sensors. Soltani et al (2018) proposed a fusion of computer vision and RFID for 3D pose estimation of hydraulic excavators, and Cai and Cai (2020) also combined BLE sensors to obtain the 3D spatial locations of construction workers from onsite images. Second, the integration with construction simulation would be also advantageous.…”

Section: Integration With Other Technologiesmentioning

confidence: 99%

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Visual Analytics for Operation-Level Construction Monitoring and Documentation: State-of-the-Art Technologies, Research Challenges, and Future Directions

Kim

2020

Front. Built Environ.

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Operation-level vision-based monitoring and documentation has drawn significant attention from construction practitioners and researchers. To automate the operation-level monitoring of construction and built environments, there have been much effort to develop computer vision technologies. Despite their encouraging findings, it remains a major challenge to exploit technologies in real construction projects, implying that there are knowledge gaps in practice and theory. To fill such knowledge gaps, this study thoroughly reviews 119 papers on operation-level vision-based construction monitoring, published in mainstream construction informatics journals. Existing research papers can be categorized into three sequential technologies: (1) camera placement for operation-level construction monitoring, (2) single-camera-based construction monitoring and documentation, and (3) multi-camera-based onsite information integration and construction monitoring. For each technology, state-of-the-art algorithms, open challenges, and future directions are discussed.

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Section: Multi-camera-based Onsite Information Integration and Constrmentioning

confidence: 99%

Section: Integration With Other Technologiesmentioning

confidence: 99%

Visual Analytics for Operation-Level Construction Monitoring and Documentation: State-of-the-Art Technologies, Research Challenges, and Future Directions

Kim

2020

Front. Built Environ.

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“…The utilization of computer vision technology in construction jobsites can be categorized into four classes regarding the main purpose of application, namely progress monitoring, quality control, operational productivity analysis [4][5][6][7] (which is to what extent onsite resources are being utilized) and safety assurance [8][9][10][11][12]. Combination of multiple purposes was achieved in some researches [13,14]. Apart from fatality prevention, there is another safety concern named occupational health assessment, referring to [15].…”

Section: Computer Vision In Construction Phasementioning

confidence: 99%

Computer Vision Techniques in Construction, Operation and Maintenance Phases of Civil Assets: A Critical Review

Xu¹,

Wang²,

Wang³

et al. 2019

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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Throughout the life cycle of civil assets, construction, operation and maintenance phases require monitoring to assure reasonable decision makings. Current methods always involve speciallyassigned personnel conducting on-site inspections, which are work-intensive, time-consuming and errorprone. Computer vision, as a powerful alternative to manual inspection, has been extensively studied during the past decades. On the basis of existing summary papers, this paper reviews a wide range of literatures, including journal articles, conference proceedings and other resources. Current applications of computer vision during construction, operation and maintenance stages of civil structures are concluded, with a special focus on operation and maintenance phase. This review aims to provide a comprehensive insight about the utilization of computer vision in civil engineering and an inspiring guidance for future research.

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“…Novel construction site automated data capturing technologies include: Global Positioning System (GPS), Radio Frequency Identification (RFID), Laser Detection and Ranging (LIDAR), Ultra Wideband (UWB), and video/audio capturing systems which call Real-Time Location Systems (RTLSs) to overcome deficiencies of traditional monitoring methods [18]- [23].…”

Section: Monitoring and Detecting Technologies For Over The Ground Objectsmentioning

confidence: 99%

Components of a Technology Roadmap for Automated Excavation

Naghshbandi¹,

Varga²,

Hu³

2019

dteees

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In the construction industry, especially in earthmoving equipment, automation has received a great deal of attention. Fully environmentally friendly automatic construction equipment, such as excavators, are perceived as vital for safe, productive, and resilient future construction sites. However, there is much uncertainty about the technologies which need to be adopted and developed in order to effectively achieve this end and provide the industry with strategic direction. This paper explores current academic thinking about technology roadmaps and technological innovations of excavation operations, in order to identify the components for automated excavation technology roadmaps. Literature in well-established databases are identified using robust search strategies. Text mining, a quantitative approach, was used to analyse and organise findings. Three main technology innovation categories were identified: 1) real time positioning systems; 2) technologies to detect over ground objects, 3) technologies to detect below underground objects. In addition, multi-sensory data fusion methods are identified as an essential and vital requirement for construction automation.

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Framework for Location Data Fusion and Pose Estimation of Excavators Using Stereo Vision

Cited by 81 publications

References 37 publications

Visual Analytics for Operation-Level Construction Monitoring and Documentation: State-of-the-Art Technologies, Research Challenges, and Future Directions

Visual Analytics for Operation-Level Construction Monitoring and Documentation: State-of-the-Art Technologies, Research Challenges, and Future Directions

Computer Vision Techniques in Construction, Operation and Maintenance Phases of Civil Assets: A Critical Review

Components of a Technology Roadmap for Automated Excavation

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