• Title/Summary/Keyword: Unmanned Aerial Vehicles (UAV)

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Survey on Developing Path Planning for Unmanned Aerial Vehicles (무인비행체 경로계획 기술 동향)

  • Y.S. Kwon;J.H. Cha
    • Electronics and Telecommunications Trends
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    • v.39 no.4
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    • pp.10-20
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    • 2024
  • Recent advancements in autonomous flight technologies for Unmanned Aerial Vehicles (UAVs) have greatly expanded their applicability for various tasks, including delivery, agriculture, and rescue. This article presents a comprehensive survey of path planning techniques in autonomous navigation and exploration that are tailored for UAVs. The robotics literature has studied path and motion planning, from basic obstacle avoidance to sophisticated algorithms capable of dynamic decision-making in challenging environments. In this article, we introduce popular path and motion planning approaches such as grid-based, sampling-based, and optimization-based planners. We further describe the contributions from the state-of-the-art in exploration planning for UAVs, which have been derived from these well-studied planners. Recent research, including the method we are developing, has improved performance in terms of efficiency and scalability for exploration tasks in challenging environments without human intervention. On the basis of these research and development trends, this article discusses future directions in UAV path planning technologies, illustrating the potential for UAVs to perform complex tasks with increased autonomy and efficiency.

A Study on the Best Applicationsof Infra-Red(IR) Sensors Mounted on the Unmanned Aerial Vehicles(UAV) in Agricultural Crops Field (무인기 탑재 열화상(IR) 센서의 농작물 대상 최적 활용 방안 연구)

  • Ho-Woong Shon;Tae-Hoon Kim;Hee-Woo Lee
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_2
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    • pp.1073-1082
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    • 2023
  • Thermal sensors, also called thermal infrared wavelength sensors, measure temperature based on the intensity of infrared signals that reach the sensor. The infrared signals recognized by the sensor include infrared wavelength(0.7~3.0㎛) and radiant infrared wavelength(3.0~100㎛). Infrared(IR) wavelengths are divided into five bands: near infrared(NIR), shortwave infrared(SWIR), midwave infrared(MWIR), longwave infrared(LWIR), and far infrared(FIR). Most thermal sensors use the LWIR to capture images. Thermal sensors measure the temperature of the target in a non-contact manner, and the data can be affected by the sensor's viewing angle between the target and the sensor, the amount of atmospheric water vapor (humidity), air temperature, and ground conditions. In this study, the characteristics of three thermal imaging sensor models that are widely used for observation using unmanned aerial vehicles were evaluated, and the optimal application field was determined.

Comparative Accuracy of Terrestrial LiDAR and Unmanned Aerial Vehicles for 3D Modeling of Cultural Properties (문화재 3차원 모델링을 위한 지상 LiDAR와 UAV 정확도 비교 연구)

  • Lee, Ho-Jin;Cho, Gi-Sung
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.1
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    • pp.179-190
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    • 2017
  • A terrestrial LiDAR survey was conducted and unmanned aerial vehicle(UAV) images were taken for target cultural properties to present the utilization measures of terrestrial LiDAR and UAV in three-dimensional modeling of cultural properties for the identification of the status and restoration of cultural properties. Then the accuracy of the point clouds generated through this process was compared, an overlap analysis of the 3D model was conducted, and a convergence model was created. According to the results, the modeling with terrestrial LiDAR is more appropriate for precise survey because 3D modeling for the detection of displacement and deformation of cultural properties requires an accuracy of mm units. And UAV model has limitation as the impossibility of detailed expression of parts with sharp unevenness such as cracks of bricks. However, it is found that the UAV model has a wide range of modeling and has the advantage of modeling of real cultural properties. Finally, the convergence model created in this study using the advantages of the terrestrial LiDAR model and the UAV model could be efficiently utilized for the basic data development of cultural properties.

Research Trend Analysis of Unmanned Aerial Vehicle(UAV) Applications in Agriculture (농업분야 무인항공기(UAV) 활용 연구동향 분석)

  • Bae, Seoung-Hun;Lee, Jungwoo;Kang, Sang Kyu;Kim, Min-Kwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.2
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    • pp.126-136
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    • 2020
  • Recently, unmanned aerial vehicles (UAV, Drone) are highly regarded for their potential in the agricultural field, and research and development are actively conducted for various purposes. Therefore, in this study, to present a framework for tracking research trends in UAV use in the agricultural field, we secured a keyword search strategy and analyzed social network, a methodology used to analyze recent research trends or technological trends as an analysis model applied. This study consists of three stages. As a first step in data acquisition, search terms and search formulas were developed for experts in accordance with the Keyword Search Strategy. Data collection was conducted based on completed search terms and search expressions. As a second step, frequency analysis was conducted by country, academic field, and journal based on the number of thesis presentations. Finally, social network analysis was performed. The analysis used the open source programming language 'Python'. Thanks to the efficiency and convenience of unmanned aerial vehicles, this field is growing rapidly and China and the United States are leading global research. Korea ranked 18th, and bold investment in this field is needed to advance agriculture. The results of this study's analysis could be used as important information in government policy making.

A Study on the Improvement of Air Vehicle Test Equipment(AVTE) stop by UAV Engine noise (UAV 엔진 소음에 의한 비행체점검장비(AVTE) 정지 현상 개선방안 연구)

  • Kang, Ju Hwan;Lim, Da Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.90-96
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    • 2020
  • In this era, intelligence is considered a major factor in the defense sector. As a result, securing technology for weapons systems for monitoring and reconnaissance of companies has become inevitable. As a result, UAVs (Unmanned Aerial Vehicles) have been developed and are actively operating around the world if the flight operation of manned aircraft is restricted, such as in environments that are too dangerous, messy or boring for the military to perform directly. The system of unmanned aerial vehicles, which has been researched and developed in Korea, includes Air Vehicle Test Equipment(AVTE). AVTE is equipment that is connected to an UAV to check its status and allows the operator to check its flightability by issuing an operational command to the UAV and verifying that it follows the command values. This study conducts fault finding on the phenomenon where the AVTE has stopped operating due to engine noise during these operations and analyzes the cause in terms of software, hardware and external environment. Present improvement measures according to the cause are analyzed and the results of verifying that the proposed measures can prevent failure are addressed.

Evaluation of the Feasibility of Deep Learning for Vegetation Monitoring (딥러닝 기반의 식생 모니터링 가능성 평가)

  • Kim, Dong-woo;Son, Seung-Woo
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.26 no.6
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    • pp.85-96
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    • 2023
  • This study proposes a method for forest vegetation monitoring using high-resolution aerial imagery captured by unmanned aerial vehicles(UAV) and deep learning technology. The research site was selected in the forested area of Mountain Dogo, Asan City, Chungcheongnam-do, and the target species for monitoring included Pinus densiflora, Quercus mongolica, and Quercus acutissima. To classify vegetation species at the pixel level in UAV imagery based on characteristics such as leaf shape, size, and color, the study employed the semantic segmentation method using the prominent U-net deep learning model. The research results indicated that it was possible to visually distinguish Pinus densiflora Siebold & Zucc, Quercus mongolica Fisch. ex Ledeb, and Quercus acutissima Carruth in 135 aerial images captured by UAV. Out of these, 104 images were used as training data for the deep learning model, while 31 images were used for inference. The optimization of the deep learning model resulted in an overall average pixel accuracy of 92.60, with mIoU at 0.80 and FIoU at 0.82, demonstrating the successful construction of a reliable deep learning model. This study is significant as a pilot case for the application of UAV and deep learning to monitor and manage representative species among climate-vulnerable vegetation, including Pinus densiflora, Quercus mongolica, and Quercus acutissima. It is expected that in the future, UAV and deep learning models can be applied to a variety of vegetation species to better address forest management.

CNN based dual-channel sound enhancement in the MAV environment (MAV 환경에서의 CNN 기반 듀얼 채널 음향 향상 기법)

  • Kim, Young-Jin;Kim, Eun-Gyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.12
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    • pp.1506-1513
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    • 2019
  • Recently, as the industrial scope of multi-rotor unmanned aerial vehicles(UAV) is greatly expanded, the demands for data collection, processing, and analysis using UAV are also increasing. However, the acoustic data collected by using the UAV is greatly corrupted by the UAV's motor noise and wind noise, which makes it difficult to process and analyze the acoustic data. Therefore, we have studied a method to enhance the target sound from the acoustic signal received through microphones connected to UAV. In this paper, we have extended the densely connected dilated convolutional network, one of the existing single channel acoustic enhancement technique, to consider the inter-channel characteristics of the acoustic signal. As a result, the extended model performed better than the existed model in all evaluation measures such as SDR, PESQ, and STOI.

Development Technology Trends of Propulsion System in Unmanned Air Vehicles (무인기 추진시스템 개발 기술 동향)

  • Nak-Gon Baek;Juhyun Im
    • Journal of Aerospace System Engineering
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    • v.18 no.2
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    • pp.95-103
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    • 2024
  • The propulsion technology used in unmanned Aerial Vehicles (UAVs)—which represent one of the most important development directions in aviation—is significantly related to their flight performance. This review paper discusses the different types of propulsion technologies used in unmanned aerial vehicles, namely the internal combustion engine (reciprocating, rotary, and gas turbine engines), the hybrid system, and the pure electric system. In particular, this paper presents and discusses the classification, working principles, characteristics, and critical technologies of these types of propulsion systems. These findings are expected to be helpful in establishing a development framework, comprehensive views, and multiple comparisons of future UAV propulsion systems.

Coordinated Millimeter Wave Beam Selection Using Fingerprint for Cellular-Connected Unmanned Aerial Vehicle

  • Moon, Sangmi;Kim, Hyeonsung;You, Young-Hwan;Kim, Cheol Hong;Hwang, Intae
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1929-1943
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    • 2021
  • Millimeter wave (mmWave) communication based on the wide bandwidth of >28 GHz is one of the key technologies for cellular-connected unmanned aerial vehicles (UAVs). The selection of mmWave beams in such cellular-connected UAVs is challenging and critical, especially when downlink transmissions toward aerial user equipment (UE) suffer from poor signal-to-interference-plus-noise ratio (SINR) more often than their terrestrial counterparts. This study proposed a coordinated mmWave beam selection scheme using fingerprint for cellular-connected UAV. The scheme comprises fingerprint database configuration and coordinated beam selection. In the fingerprint database configuration, the best beam index from the serving cell and interference beam indexes from neighboring cells are stored. In the coordinated beam selection, the best and interference beams are determined using the fingerprint database information instead of performing an exhaustive search, and the coordinated beam transmission improves the SINR for aerial UEs. System-level simulations assess the UAV effect based on the third-generation partnership project-new radio mmWave and UAV channel models. Simulation results show that the proposed scheme can reduce the overhead of exhaustive search and improve the SINR and spectral efficiency.

Power Management of Fuel Cell Propulsion System for Unmanned Aerial Vehicles (무인기용 연료전지 추진 시스템의 동력 관리)

  • Kim, Tae-Gyu;Shim, Hyun-Chul;Kwon, Se-Jin
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2007.11a
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    • pp.13-16
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    • 2007
  • Fuel cell was used as a propulsion system for unmanned aerial vehicles (UAV) in the present study. Fuel cell propulsion system are an ideal alternative power source with high energy density for high-endurance UAV. Fuel cell power system provides UAV up to five times the energy densiη of existing batteries. Sodium borohydride, stored in liquid state, was selected as a hydrogen source. Hydrogen generation system consists of catalytic reactor, pump, fuel cartridge, and separator. Hybrid power management system (PMS) between fuel cell and lithium-polymer ba야ery was developed. Motor, pump, and fans, operated on battery power controlled by feedback signals of fuel cell system. Battery was recharged by surpuls powr of fuel cell.

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