• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.115-126
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• 2016

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.11-16
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• 2023

The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.06a
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• pp.105-106
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• 2020

Recently, a method of deriving an efficient 2D floor plan has been attracting attention for remodeling of old buildings with inaccurate 2D floor plans, and thus, studies on reverse engineering of indoor Point Cloud Date(PCD) have been actively conducted. However, in the case of a indoor PCD, due to interference of indoor objects, available equipment is limited to Mobile Laser Scanner(MLS), which causes a efficiency reduction of data processing. Therefore, this study proposes an automatic derivation algorithm for 2D floor plan of indoor PCD based on pixelation. First, the scanned indoor PCD is projected on the XY coordinate plane. Second, a point distribution of each pixel in the projected PCD is derived using a pixelation. Lastly, 2 floor plan derivation based on the algorithm is performed.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.633-641
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• 2015

In this study, we proposed a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, a camera, and a turntable. For laser-camera calibration a new and simple method was proposed. 3D point cloud data of the surface of scanned object was fully collected by integrating extracted laser profiles, which were extracted from laser stripe images, corresponding to rotary angles of the rotary mechanism. The obscured laser profile problem was also solved by adding an addition camera at another viewpoint. From collected 3D point cloud data, the 3D model of the scanned object was reconstructed based on facet-representation. The reconstructed 3D models showed effectiveness and the applicability of the proposed 3D scanning system to 3D model-based applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.157-159
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• 2019

Hologram technology has been actively developed in terms of generation, transmission, and reproduction of 3D objects, but it is currently in a state of rest because of various limitations. Beyond VR and AR, the pseudo-hologram market is growing at an intermediate stage to meet the needs of new technologies. The key to the technology of hologram is to generate vast 3 dimensional data in the form of a point cloud, transmit the vast amount of data through the communication network in real time, and reproduce it like the original at the destination. In this paper, we propose a method to transmit massive 3 - D data in real - time and transmit the minutiae points of 3 - dimensional object information to reproduce the object as similar to original.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.77-86
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• 2015

It is difficult to extract small valve automatically in noisy 3D point cloud obtained from LIDAR because small object is affected by noise considerably. In this paper, we assume that the valve is a complex model consisting of torus, cylinder and plane represents handle, rib and center plane to extract a pose of the valve. And to extract the pose, we received additional input: center of the valve. We generated histogram of distance between the center and each points of point cloud, and obtain pose of valve by extracting parameters of handle, rib and center plane. Finally, the valve is reconstructed.

• Macromolecular Research
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• v.11 no.4
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• pp.231-235
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• 2003

Phase behavior information is necessary for accomplishing homogeneous copolymerization to obtain high yield of copolymers and prevent a fouling problem. Cloud-point data to $160^{\circ}C$ and 1,450 bar are presented for five $C_6$ hydrocarbon solvents, normal hexane, 2,2-dimethyl butane, 2,3-dimethyl butane, 2-methyl pentane, and 3-methyl pentane, with poly(ethylene-co-53 mol% norbornene) ($PEN_{53}$). The pressure-concentration isotherms measured for $PEN_{53}$/n-hexane have maximums that range between 5 and 12 wt% $PEN_{53}$. The cloud-point curves for $PEN_{53}$ all have negative slopes that decrease in pressure with temperatures. The single-phase region of $PEN_{53}$ in n-hexane is larger than the regions in 2,2-dimethyl butane, 2,3-dimethyl butane, 2-methyl pentane, and 3-methyl pentane. The cloud-point curve of $PEN_{53}$ in 2,2-dimethyl butane is located at higher temperatures and pressures than the curve in 2,3-dimethyl butane due to the reduced dispersion interactions with and limited access of 2,2-dimethyl butane to the copolymer. Similar cloud-point behavior is observed for $PEN_{53}$ in 2-methyl pentane and 3-methyl pentane.

• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.102-111
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• 2016

In this paper, we study the problem of computing smooth feature curves from CAD type point clouds models. The proposed method reconstructs feature curves from the intersections of developable strip pairs which approximate the regions along both sides of the features. The generation of developable surfaces is based on a linear approximation of the given point cloud through a variational shape approximation approach. A line segment sequencing algorithm is proposed for collecting feature line segments into different feature sequences as well as sequential groups of data points. A developable surface approximation procedure is employed to refine incident approximation planes of data points into developable strips. Some experimental results are included to demonstrate the performance of the proposed method.

• Journal of Industrial Technology
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• v.18
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• pp.277-287
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• 1998

In this work continuous thermodynamics was adopted for describing the influence of copolymer polydispersity on phase separations in random copolymer solutions. Continuous themodynamic frameworks were formulated using the Flory-Huggin's excess Gibbs free energy model in which the concentration- and temperature-depentent terms of interaction parameter x were modified. Cloud-point curves and coexistence curves of poly(ethylene-vinylactate)/methylacetate solutions and poly(ehtylene-vinylacetate)/ethylacetate solutions were measured, and experimental data were fitted with theoretical relations formulated in this work. Calculated could-point curves were more good ageeable with experimental data than the modified Flory-Huggins's relations. Coexistence curves which were evaluated by using parameters of x estimated from experimental cloud-point curves, were found to coincide with experimental data.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.37-46
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• 2024

Recently, 3D laser scanning technology, which can collect accurate and quick information on phenomena, has been attracting attention among smart construction technologies. 3D laser scanning technology can obtain information most similar to reality at construction sites. In this study, we would like to apply a new member identification method to an actual building and present the possibility of applying point cloud data, which can be collected using 3D laser scanning technology, to measuring progress at construction sites. In order to carry out the research, we collected location information for component identification from BIM, set a recognition margin for the collected location information, and proceeded to identify the components that make up the building from point cloud data. Research results We confirmed that the columns, beams, walls, and slabs that make up a building can be identified from point cloud data. The identification results can be used to confirm all the parts that have been completed in the actual building, and can be used in conjunction with the unit price of each part in the project BOQ for prefabricated calculations. In addition, the point cloud data obtained through research can be used as accurate data for quality control monitoring of construction sites and building maintenance management. The research results can contribute to improving the timeliness and accuracy of construction information used in future project applications.