Automatic interpretation of unordered point cloud data for UAV navigation in construction

Phung, Manh Duong; Quach, Cong Hoang; Chu, Dong-Hun; Nguyen, Nhu; Dinh, Tran Hiep; Ha, Q.P.

doi:10.1109/icarcv.2016.7838683

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…The point cloud refers to a set of data points obtained from data sources (e.g., a laser scanner) in a 3D coordinate system, which are used to represent the external surfaces of an object [64]. A laser scanner carried on an unmanned aerial vehicle (UAV) has been reported to be effective for obtaining panoramic data of a construction site in real time [65,66]. However, the 3D surface model only presents the surface shape of the components but does not contain their other attributes.…”

Section: H 3-d Reconstructionmentioning

confidence: 99%

Integration of Industry 4.0 Related Technologies in Construction Industry: A Framework of Cyber-Physical System

2020

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The Fourth Industrial Revolution (Industry 4.0) is reshaping the construction industry and bringing it into an intelligent construction era. Emerging technologies, such as the Building Information Modelling, Internet of Things, big data, cloud computing, and artificial intelligence, have penetrated into all stages of the building life cycle and play a significant role. However, the major issue of intelligent construction is integrating multiple technologies to create more potential opportunities rather than their fragmented application. Considering the various special characteristics of the construction industry and the high heterogeneity of these technologies, their integration in the construction industry is challenging and requires in-depth investigations. This paper summarizes the Industry 4.0-related technologies involved in the construction industry based on an analysis of the characteristics of the industry. Further, this study presents a framework of a cyber-physical system to integrate these technologies and improve the overall capabilities of construction organization and management. A case study of the Xiong'an citizen service center is introduced to verify the technological feasibility and preliminary implementation effect of the proposed framework. As forward-looking research, the significance of this paper may also to inspire more efforts in this field.

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Section: H 3-d Reconstructionmentioning

confidence: 99%

Integration of Industry 4.0 Related Technologies in Construction Industry: A Framework of Cyber-Physical System

2020

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“…The goal of data collection is to acquire adequate geometric and surface information of the object to be used in post processing for detecting potential cracks, and also for navigation of the UAV itself [19].…”

Section: Data Collection Using Uavmentioning

confidence: 99%

Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

Phung¹,

Hoang²,

Dinh³

et al. 2017

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

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-This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.

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“…The control signals u φ , u θ and u ψ in (12) are used to control the three angles {φ, θ, ψ} to reach the reference value…”

Section: Control Designmentioning

confidence: 99%

“…T denote the sum of ∆P and P. Since the disturbance d and uncertain parameter ∆I are bounded, from ( 22) and ( 23) it can be seen that Ξ is also bounded, i.e., |Ξ i | ≤ Ξ M,i , i = 1, 2, 3. Consider system (12) with the sliding variable σ(ω, t) as in (13). From assumptions A1-A6, the sliding motion on the manifold is achieved by the controller (16) if we can select the gain α i such that [15]:…”

Section: Qcsm Control Design and Problem Formulationmentioning

confidence: 99%

“…Quadcopters have found many applications in civil engineering automation due to its flexibility in operational space and ability in vertical take off and landing. These include the use of UAVs in automatic 3D reconstruction for building condition assessment [2], securing superstructures of high-rise buildings [3], or monitoring and inspection of civil infrastructure [6,12]. In those applications, it is critical to maintain robustness and resilience of the control system to cope with the highly non-linear dynamics of quadcopters and system uncertainties, sensor noise and coupling effects between the rotational and translational motions, or disturbances from aerodynamics and other external factors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Second-Order Sliding Mode Control of UAVs for Civil Applications

Hoang¹,

Singh²,

Phung³

et al. 2017

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

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-Quadcopters, as unmanned aerial vehicles (UAVs), have great potential in civil applications such as surveying, building monitoring, and infrastructure condition assessment. Quadcopters, however, are relatively sensitive to noises and disturbances so that their performance may be quickly downgraded in the case of inadequate control, system uncertainties and/or external disturbances. In this study, we deal with the quadrotor low-level control by proposing a robust scheme named the adaptive second-order quasi-continuous sliding mode control (adaptive 2-QCSM). The ultimate objective is for robust attitude control of the UAV in monitoring and inspection of built infrastructure. First, the mathematical model of the quadcopter is derived considering nonlinearity, strong coupling, uncertain dynamics and external disturbances. The control design includes the selection of the sliding manifold and the development of quasi-continuous second-order sliding mode controller with an adaptive gain. Stability of the overall control system is analysed by using a global Lyapunov function for convergence of both the sliding dynamics and adaptation scheme. Extensive simulations have been carried out for evaluation. Results show that the proposed controller can achieve robustness against disturbances or parameter variations and has better tracking performance in comparison with experimental responses of a UAV in a real-time monitoring task.

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Automatic interpretation of unordered point cloud data for UAV navigation in construction

Cited by 7 publications

References 11 publications

Integration of Industry 4.0 Related Technologies in Construction Industry: A Framework of Cyber-Physical System

Integration of Industry 4.0 Related Technologies in Construction Industry: A Framework of Cyber-Physical System

Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

Adaptive Second-Order Sliding Mode Control of UAVs for Civil Applications

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