• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1309-1320
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• 2023

The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

• Tunnel and Underground Space
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• v.22 no.4
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• pp.266-275
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• 2012

In this study, a method is devised to implement a supercritical $CO_2$ ($scCO_2$) injection environment on a laboratory scale and to investigate the effects of $scCO_2$ on the properties of rock specimens. Specimens of shale and sandstone normally constituting the cap rock and reservoir rock, respectively, were kept in a laboratory reactor chamber with $scCO_2$ for two weeks. From this stage, a chemical reaction between rock surface and the $scCO_2$ was induced. The effect of saline water was also investigated by comparing three conditions ($scCO_2$-rock, $scCO_2-H_2O$-rock and $scCO_2$-brine(1M)-rock). Finally, we checked the changes in the properties before and after the reaction by destructive and nondestructive testing procedures. The swelling of shale was a main concern in this case. The experimental results suggested that $scCO_2$ has a greater effect on the swelling of the shale than pure water and brine. It was also observed that the largest swelling displacement of shale occurred after a reaction with the $H_2O-scCO_2$ solution. The results of a series of the destructive and nondestructive tests indicate that although each of the property changes of the rock differed depending on the reaction conditions, the $H_2O-scCO_2$ solution had the greatest effect. In this study, shale was highly sensitive to the reaction conditions. These results provide fundamental information pertaining to the stability of $CO_2$ storage sites due to physical and chemical reactions between the rocks in these sites and $scCO_2$.