Kyoung-Hun Kim;Byungsun Hwang;Joonho Seon;Soo-Hyun Kim;Jin-Young Kim
The Journal of the Institute of Internet, Broadcasting and Communication
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v.24
no.3
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pp.15-20
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2024
Path planning for unmanned aerial vehicles (UAV) is crucial in avoiding collisions with obstacles in complex environments that include both static and dynamic obstacles. Path planning algorithms like RRT and A* are effectively handle static obstacle avoidance but have limitations with increasing computational complexity in high-dimensional environments. Reinforcement learning-based algorithms can accommodate complex environments, but like traditional path planning algorithms, they struggle with training complexity and convergence in higher-dimensional environment. In this paper, we proposed a reinforcement learning model utilizing a cell decomposition algorithm. The proposed model reduces the complexity of the environment by decomposing the learning environment in detail, and improves the obstacle avoidance performance by establishing the valid action of the agent. This solves the exploration problem of reinforcement learning and improves the convergence of learning. Simulation results show that the proposed model improves learning speed and efficient path planning compared to reinforcement learning models in general environments.
Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.
Floods are among the most common natural hazards in urban areas. To mitigate the problems caused by flooding, unstructured data such as images and videos collected from closed circuit televisions (CCTVs) or unmanned aerial vehicles (UAVs) have been examined for flood management (FM). Many computer vision (CV) techniques have been widely adopted to analyze imagery data. Although some papers have reviewed recent CV approaches that utilize UAV images or remote sensing data, less effort has been devoted to studies that have focused on CCTV data. In addition, few studies have distinguished between the main research objectives of CV techniques (e.g., flood depth and flooded area) for a comprehensive understanding of the current status and trends of CV applications for each FM research topic. Thus, this paper provides a comprehensive review of the literature that proposes CV techniques for aspects of FM using ground camera (e.g., CCTV) data. Research topics are classified into four categories: flood depth, flood detection, flooded area, and surface water velocity. These application areas are subdivided into three types: urban, river and stream, and experimental. The adopted CV techniques are summarized for each research topic and application area. The primary goal of this review is to provide guidance for researchers who plan to design a CV model for specific purposes such as flood-depth estimation. Researchers should be able to draw on this review to construct an appropriate CV model for any FM purpose.
Journal of Satellite, Information and Communications
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v.4
no.1
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pp.1-7
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2009
As the information age comes out, the aspect of future war brings about the many changes in terms of war-fighting environment. Accordingly, information superiority and intelligence-centric warfare have been important and new war-fighting concept such as NCW(network centric warfare) have been turned up. This paper proposed all-weather core-strategy communications systems guaranteeing not only the real-time transmission of the information collected in a battlefield and expansion, automation, and rapidity of a battlefield but also broadband, mobility, survivability, and flexibility. The proposed military satellite communications system is classified into wideband mass capacity link, survivability, and the system supporting OTM(on the move) communication for the real-time transmission of battlefield information. This paper analyzed the essential operation concepts and core schemes of the U.S. Army's next generation system, TSAT(Transformational Satellite Communication System). Base on the analysis results, this paper proposed that the architecture of next generation military satellite communications systems for NCW have to provide the data rate, anti-jamming capability, network control and management capability which are optimally adaptable for the wireless channel environments such as jamming and interference and to support the variety of platforms like high-speed mobile vehicles, micromini devices, super-high speed unmanned aerial vehicles. Finally, this paper also proposed that next generation military satellite communications systems need the technologies such as the adaptable multi-antenna, laser link, and next-generation anti-jamming waveform.
Carbon fiber reinforced polymer (CFRP) is one of the composite materials, which has a unique property that is lightweight but strong. The CFRPs are widely used in various industries where their unique characteristics are required. In particular, electric and unmanned aerial vehicles critically need lightweight parts and bodies with sufficient mechanical strengths. Vehicles using the battery as a power source should simultaneously meet two requirements that the battery has to be safely protected. The vehicle should be light of increasing the mileage. The CFRP has considered as the one that satisfies the requirements and is widely used as battery housing and other vehicle parts. On the other hand, in the battery area, carbon fibers are intensively tested as battery components such as electrodes and/or current collectors. Furthermore, using carbon fibers as both structure reinforcements and battery components to build a structural battery is intensively investigated in Sweden and the USA. This mini-review encompasses recent research trends that cover the classification of structural batteries in terms of functionality of carbon fibers and issues and efforts in the battery and discusses the prospect of structural batteries.
Journal of the Korean Association of Geographic Information Studies
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v.24
no.2
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pp.78-90
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2021
In order to construct a precision geoid, it has been diversified into land, sea, aviation, and satellite gravity measurement methods, and measurement technology has developed, making it possible to secure high-resolution, high-precision gravity data. The construction of precision geoids can be fast and conveniently decided through GNSS surveys without separate leveling, and since 2014, the National Geographic Information Institute has been developing a hybrid geoid model to improve the accuracy of height surveying based on GNSS. In this study, the results of the GNSS height measurement were compared and analyzed choosing existing public reference points to verify the GNSS height measurement of public surveys. Experiments are conducted with GNSS height measurements and analyzed precision for public reference points on coastal, border, and mountainous terrain presented as low-precision areas or expected-to-be low-precision in research reports. To verify the GNSS height measurement, the GNSS ellipsoid height of the surrounding integrated datum to be used as a base point for the GNSS height measurement at the public datum. Based on the checked integrated datum, the GNSS ellipsoid of the public datum was calculated, and the elevation was calculated using the KNGeoid18 model and compared with the results of the direct level measurement elevation. The analysis showed that the results of GNSS height measurement at public reference points in the coastal, border, and mountainous areas were satisfied with the accuracy of public level measurement in grades 3 and 4. Through this study, GNSS level measurement can be used more efficiently than existing direct level measurements depending on the height accuracy required by users, and KNGeoids 18 can also be used in various fields such as autonomous vehicles and unmanned aerial vehicles.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.4
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pp.63-68
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2018
The establishment of Ground Control Points (GCPs) in UAV-Photogrammetry is a working process that requires the most time and expenditure. Recently, the rapid developments of navigation sensors and communication technologies have enabled Unmanned Aerial Vehicles (UAVs) to conduct photogrammetric mapping without using GCP because of the availability of new methods such as RTK (Real Time Kinematic) and PPK (Post Processed Kinematic) technology. In this study, an experiment was conducted to evaluate the potential of RTK-UAV mapping with no GCPs compared to that of non RTK-UAV mapping. The positioning accuracy results produced by images obtained simultaneously from the two different types of UAVs were compared and analyzed. One was a RTK-UAV without GCPs and the other was a non RTK-UAV with different numbers of GCPs. The images were taken with a Canon IXUS 127 camera (focal length 4.3mm, pixel size $1.3{\mu}m$) at a flying height of approximately 160m, corresponding to a nominal GSD of approximately 4.7cm. As a result, the RMSE (planimetric/vertical) of positional accuracy according to the number of GCPs by the non-RTK method was 4.8cm/8.2cm with 5 GCPs, 5.4cm/10.3cm with 4 GCPs, and 6.2cm/12.0cm with 3 GCPs. In the case of non RTK-UAV photogrammetry with no GCP, the positioning accuracy was decreased greatly to approximately 112.9 cm and 204.6 cm in the horizontal and vertical coordinates, respectively. On the other hand, in the case of the RTK method with no ground control point, the errors in the planimetric and vertical position coordinates were reduced remarkably to 13.1cm and 15.7cm, respectively, compared to the non-RTK method. Overall, UAV photogrammetry supported by RTK-GPS technology, enabling precise positioning without a control point, is expected to be useful in the field of spatial information in the future.
The purpose of this study is to present a reasonable and concrete standard for the Korean aviation insurance compulsory subscription system. Through this, we aim to improve the current revision of laws and regulations, and ultimately create an environment in which the safety and property of the Korean people who use aircraft with appropriate aviation insurance can be secured. In particular, by reviewing the aviation business law and its new laws and regulations enacted in 2017, the legislative improvement direction of aviation insurance will be proposed. In order to maintain the continuous growth of the air transportation industry and to make amicable compensation for the victims, considering the characteristics of the total accident, instantness, and giganticness of air accidents in which a lot of people and property are lost in the event of an accident, adequate insurance coverage is essential. In this respect, the compulsory insurance to amend the principle of freedom of contract, which is the great principle of the modern judicial system, will be persuasive. However, in comparison with foreign legislation, the legal provisions on Korea's obligation to comply with aviation insurance need to be revised around the following issues: First, it is reasonable to enforce the regulation of the mandatory aviation insurance by legislation from the Congress not by administrative regulations. Because it will force the monetary obligations of the individual such as common air carriers. Second, our law regulations respond to various kinds of air damages by using the phrase "limit of liability stipulated in international conventions". However, as we have seen in the text, the range of compensation are various according to the use of legal instruments in international conventions such as the Montreal Convention, which governs the compensation of passengers for damages to passengers today. Third, in countries with narrow territories, such as Korea, there are big differences in flying time and insurable risk between domestic and international transportation. Therefore, it is necessary to divide domestic transportation and international transportation even in the obligation to join the insurance. This dual discipline has the advantage for rookies in air carrier market who mainly start their business from domestic service. Fourth, according to Korean law, the regulations of automobile loss insurance is applicable to the aviation mandatory insurance of unmanned aerial vehicle accident which is lack of persuasion. In the future, it will be appropriate to discipline insurance for unmanned aerial vehicles with unlimited potential for development from a long-term perspective.
Journal of the Korean Society for Aeronautical & Space Sciences
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v.48
no.5
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pp.363-372
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2020
Dynamic compressive material properties at high strain rates is essential for improving the reliability of finite element analysis in dynamic environments, such as high-speed collisions and high-speed forming. In general, the dynamic compressive material properties for high strain rates can be obtained through SHPB equipment. In this study, SHPB equipment was used to acquire the dynamic compressive material properties to cope with the collision analysis of Woven tpye CFRP material, which is being recently applied to unmanned aerial vehicles. It is also used as a pulse shaper to secure a constant strain rate for materials with elastic-brittle properties and to improve the reliability of experimental data. In the case of CFRP material, since the anisotropic material has different mechanical properties for each direction, experiments were carried out by fabricating thickness and in-plane specimens. As a result of the SHPB test, in-plane specimens had difficulty in securing data reproducibility and reliability due to fracture of the specimens before reaching a constant strain rate region, whereas in the thickness specimens, the stress consistency of the specimens was excellent. The data reliability is high and a constant strain rate range can be obtained. Through finite element analysis using LS-dyna, it was confirmed that the data measured from the pressure rod were excessively predicted by the deformation of the specimen and the pressure rod.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.8
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pp.355-360
/
2017
Recently, with the development of autonomous vehicle technology, the importance of precise road maps is increasing. A precise road map is a digital map with lane information, regulations, safety information, and various road facilities. Conventional precise road maps have been tested and developed based on the mobile mapping system (MMS). But they have not been activated due to high introduction costs. However, in the case of unmanned aerial vehicles (UAVs), the application field is continuously increasing. This study tries to extract information through classification of high-resolution UAV images for autonomous driving. Autonomous vehicle test roads were selected as study sites, and high-resolution orthoimages were produced using UAVs. In addition, the utilization of high-resolution orthoimages has been proposed by effectively extracting data for precise road map construction, such as road lines, guards, and machines through image classification. If additional experimentation and verification are performed, the field of UAV image use will be expanded, providing the data to automobile manufacturers and related public and private organizations, and venture companies will contribute to the development of domestic autonomous vehicle technology.
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