Frédéric Bosché

Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction

The construction industry lacks solutions for accurately, comprehensively and efficiently tracking the three-dimensional (3D) status of buildings under construction. Such information is however critical to the successful management of construction projects: It supports fundamental activities such as progress tracking and construction dimensional quality control. In this paper, a new approach for automated recognition of project 3D Computer-Aided Design (CAD) model objects in large laser scans is presented, with significant improvements compared to the one originally proposed in Bosche et al. (in press) [11]. A more robust point matching method is used and registration quality is improved with the implementation of an Iterative Closest Point (ICP)-based fine registration step. Once the optimal registration of the projects CAD model with a site scan is obtained, a similar ICP-based registration algorithm is proposed to calculate the as-built poses of the CAD model objects. These as-built poses are then used for automatically controlling the compliance of the project with respect to corresponding dimensional tolerances. Experimental results are presented with data obtained from the erection of an industrial buildings steel structure. They demonstrate the performance in real field conditions of the model registration and object recognition algorithms, and show the potential of the proposed approach for as-built dimension calculation and control.

Tracking the Built Status of MEP Works: Assessing the Value of a Scan-vs-BIM System

AbstractMechanical, electrical, and plumbing (MEP) works constitute a large portion of construction costs and thus need to be appropriately tracked. Assessment of the built status of MEP works in construction projects is however typically limited to subcontractor claims augmented and contrasted with periodic manual inspection. A more detailed manual inspection is costly and not considered worthwhile on most projects. Within a Scan-vs-BIM object recognition framework, three-dimensional laser scanning and project 3D/4D BIM models jointly offer the opportunity for a frequent, detailed, and semantically rich assessment of as-built status of construction projects at a cost that continues to decline. This potential has already been demonstrated for tracking structural works, but remains to be assessed in regard to other work sections, in particular MEP works. This paper explores that opportunity. A Scan-vs-BIM processing system is described with some enhancements over previous works. It is then tested with a re...

Plane-based registration of construction laser scans with 3D/4D building models

With the development of building information modelling (BIM) and terrestrial laser scanning (TLS) in the architecture, engineering, construction and facility management (AEC/FM) industry, the registration of site laser scans and project 3D (BIM) models in a common coordinate system is becoming critical to effective project control. The co-registration of 3D datasets is normally performed in two steps: coarse registration followed by fine registration. Focusing on the coarse registration, model-scan registration has been well investigated in the past, but it is shown in this article that the context of the AEC/FM industry presents specific (1) constraints that make fully-automated registration very complex and often ill-posed, and (2) advantages that can be leveraged to develop simpler yet effective registration methods. This paper thus presents a novel semi-automated plane-based registration system for coarse registration of laser scanned 3D point clouds with project 3D models in the context of the AEC/FM industry. The system is based on the extraction of planes from the laser scanned point cloud and project 3D/4D model. Planes are automatically extracted from the 3D/4D model. For the point cloud data, two methods are investigated. The first one is fully automated, and the second is a semi-automated but effective one-click RANSAC-supported extraction method. In both cases, planes are then manually but intuitively matched by the user. Experiments, which compare the proposed system to software packages commonly used in the AEC/FM industry, demonstrate that at least as good registration quality can be achieved by the proposed system, in a simpler and faster way. It is concluded that, in the AEC/FM context, the proposed plane-based registration system is a compelling alternative to standard point-based registration techniques.

Toward automated earned value tracking using 3D imaging tools

AbstractAccurate and frequent construction progress tracking provides critical input data for project systems such as cost, schedule control, and billing. Unfortunately, conventional progress tracking is labor intensive, sometimes subject to negotiation, and often driven by arcane rules. Attempts to improve progress tracking have recently focused on automation, using technologies such as three-dimensional imaging, global positioning systems, ultra wide band (UWB) indoor locating, handheld computers, voice recognition, wireless networks, and other technologies in various combinations. However, one limit of these approaches is their focus on counting objects or milestones rather than value. In this paper, a four-dimensional model recognition-driven automated progress tracking system that transforms objects to their earned values is examined via the analysis of data from the construction of a steel reinforced concrete structure and a steel structure. It is concluded that automated, object oriented recognitio...

As-built data acquisition and its use in production monitoring and automated layout of civil infrastructure

Access to reliable 3D as-built data is a critical issue in civil infrastructure.Applications to production monitoring and automated layout are discussed.Research on applications of as-built data in the civil engineering field is reviewed.State-of-the-art and other developments in as-built data analysis are surveyed.Unsolved problems and challenges for future improvements in this field are discussed. The collection and analysis of data on the three-dimensional (3D) as-built status of large-scale civil infrastructure - whether under construction, newly put into service, or in operation - has been receiving increasing attention on the part of researchers and practitioners in the civil engineering field. Such collection and analysis of data is essential for the active monitoring of production during the construction phase of a project and for the automatic 3D layout of built assets during their service lives. This review outlines recent research efforts in this field and technological developments that aim to facilitate the analysis of 3D data acquired from as-built civil infrastructure and applications of such data, not only to the construction process per se but also to facility management - in particular, to production monitoring and automated layout. This review also considers prospects for improvement and addresses challenges that can be expected in future research and development. It is hoped that the suggestions and recommendations made in this review will serve as a basis for future work and as motivation for ongoing research and development.

Haarlet-based hand gesture recognition for 3D interaction

This paper presents a system to manipulate 3D objects or navigate through 3D models by detecting the gestures and the movements of the hands of a user in front of a camera mounted on top of a screen. This paper more particularly introduces an improved skin color segmentation algorithm which combines an online and an offline model; and a Haarlet-based hand gesture recognition system, where the Haarlets are trained based on Average Neighborhood Margin Maximization (ANMM). The result is a real-time marker-less interaction system which is applied to two applications, one for manipulating 3D objects, and the other for navigating through a 3D model.

Musculoskeletal disorders in construction: A review and a novel system for activity tracking with body area network

Human body motions have been analysed for decades with a view on enhancing occupational well-being and performance of workers. On-going progresses in miniaturised wearable sensors are set to revolutionise biomechanical analysis by providing accurate and real-time quantitative motion data. The construction industry has a poor record of occupational health, in particular with regard to work-related musculoskeletal disorders (WMSDs). In this article, we therefore focus on the study of human body motions that could cause WMSDs in construction-related activities. We first present an in-depth review of existing assessment frameworks used in practice for the evaluation of human body motion. Subsequently different methods for measuring working postures and motions are reviewed and compared, pointing out the technological developments, limitations and gaps; Inertial Measurement Units (IMUs) are particularly investigated. Finally, we introduce a new system to detect and characterise unsafe postures of construction workers based on the measurement of motion data from wearable wireless IMUs integrated in a body area network. The potential of this system is demonstrated through experiments conducts in a laboratory as well as in a college with actual construction trade trainees.

Markerless Vision-Based Augmented Reality for Urban Planning

Augmented Reality (AR) is a rapidly develop- ing field with numerous potential applications. For ex- ample, building developers, public authorities, and other construction industry stakeholders need to visually as- sess potential new developments with regard to aesthet- ics, health and safety, and other criteria. Current state-of- the-art visualization technologies are mainly fully virtual, while AR has the potential to enhance those visualiza- tions by observing proposed designs directly within the real environment. A novel AR system is presented, that is most appropriate for urban applications. It is based on monocular vision, is markerless, and does not rely on beacon-based local- ization technologies (like GPS) or inertial sensors. Addi- tionally, the system automatically calculates occlusions of the built environment on the augmenting virtual objects. Three datasets from real environments presenting dif- ferent levels of complexity (geometrical complexity, tex- tures, occlusions) are used to demonstrate the perfor- mance of the proposed system. Videos augmented with our system are shown to provide realistic and valuable visualizations of proposed changes of the urban environ- ∗ To whom correspondence should be addressed. E-mail: f.n.bosche@

Tracking of secondary and temporary objects in structural concrete work

Purpose – Previous research has shown that “Scan-vs-BIM” object recognition systems, which fuse three dimensional (3D) point clouds from terrestrial laser scanning (TLS) or digital photogrammetry with 4D project building information models (BIM), provide valuable information for tracking construction works. However, until now, the potential of these systems has been demonstrated for tracking progress of permanent structural works only; no work has been reported yet on tracking secondary or temporary structures. For structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. Together, they constitute most of the earned value in concrete work. The impact of tracking secondary and temporary objects would thus be added veracity and detail to earned value calculations, and subsequently better project control and performance. The paper aims to discuss these issues. Design/methodology/approach – Two techniques for recognizing concrete constr...

Tracking secondary and temporary concrete construction objects using 3D imaging technologies

Recent research efforts to improve construction progress tracking has focused on employing emerging technologies such as three dimensional (3D) imaging, including digital photogrammetry and 3D Terrestrial Laser Scanning (TLS). Previous research has shown that “Scan-vs-BIM” object recognition systems, which fuse 3D TLS and 4D project BIM, provide valuable information for tracking structural works. However, until now these systems have focused on tracking progress for permanent structures only; none of them has considered progress of secondary or temporary structures. In the context of structural concrete work, temporary structures include formwork, scaffolding and shoring, while secondary components include rebar. The value of tracking temporary and secondary elements is that it would add veracity and detail to the progress tracking process, and consequently to billing. This paper presents two different techniques for detecting concrete construction secondary and temporary objects in TLS point clouds, one of which is based on a Scan-vs-BIM object recognition system. Both techniques are tested using real-life data collected from a reinforced concrete building construction site. The preliminary experimental results show that it is feasible to detect and track secondary and temporary objects in 3D TLS point clouds with high accuracy. This will help to improve progress estimation and tracking.