• Title/Summary/Keyword: Multiple-UAV

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Implementation of Multilateral Control System for Small UAV Control-Focused on Design (소형 무인기 통제를 위한 다자간 방식 관제시스템 구축방안-설계 중심으로)

  • Choi, Hyun-Taek;Kim, Seok-Kwan;Ryu, Gab-Sang
    • Smart Media Journal
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    • v.6 no.4
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    • pp.65-71
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    • 2017
  • In this paper, we propose a design method for the construction of LTE-based small unmanned aerial vehicle control system to quickly and reliably collect multiple small unmanned aerial vehicle position information simultaneously flying all over the country. In particular, the main requirements are the network (N/W), hardware (H/ W), software(SW), Database(DB), development architecture, and business needs. To satisfy these requirements, N/W, H/W, SW, DB design, and architectural design plan were suggested regarding the design requirements of a small UAV system. To effectively control the small unmanned multi-party system in the system design, the architecture is divided into the front-end service area and the back-end service area according to the function and role of the unit system. In the front-end service area that grasps and controls the position and state of small unmanned aerial vehicles (UAVs), we have studied the design part that can be expanded to N through TCP/IP network by applying Client PC method.

A Study on the Possibility of Using the Aerial-Based Vehicle Detection System for Real-Time Traffic Data Collection (항공 기반 차량검지시스템의 실시간 교통자료 수집에의 활용 가능성에 관한 연구)

  • Baik, Nam Cheol;Lee, Sang Hyup
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.2D
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    • pp.129-136
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    • 2012
  • In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

Multi Point Cloud Integration based on Observation Vectors between Stereo Images (스테레오 영상 간 관측 벡터에 기반한 다중 포인트 클라우드 통합)

  • Yoon, Wansang;Kim, Han-gyeol;Rhee, Sooahm
    • Korean Journal of Remote Sensing
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    • v.35 no.5_1
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    • pp.727-736
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    • 2019
  • In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

Real Time Fault Diagnosis of UAV Engine Using IMM Filter and Generalized Likelihood Ratio Test (IMM 필터 및 GLRT를 이용한 무인기용 엔진의 실시간 결함 진단)

  • Han, Dong-Ju;Kim, Sang-Jo;Kim, Yu-Il;Lee, Soo-Chang
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.541-550
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    • 2022
  • An effective real time fault diagnosis approach for UAV engine is drawn from IMM filter and GLRT methods. For this purpose based on the linear diagnosis model derived from engine dynamic performance analysis the Kalman filter for residual estimation and each method are applied to the fault diagosis of the actuator for engine control sensors. From the process of the IMM filter application the effective FDI measure is obtained and the state responses due to actuator fault are estimated. Likewise from the GLRT method the fault magnitudes of actuator and sensors are estimated associated with some FDI functionings. The numerical simulations verify the effectiveness of the IMM filter for FDI and the GLRT in estimating the fault magnitudes of each fault mode.

Development of Autonomous Behavior Software based on BDI Architecture for UAV Autonomous Mission (무인기 자율임무를 위한 BDI 아키텍처 기반 자율행동 소프트웨어 개발)

  • Yang, Seung-Gu;Uhm, Taewon;Kim, Gyeong-Tae
    • Journal of Advanced Navigation Technology
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    • v.26 no.5
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    • pp.312-318
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    • 2022
  • Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

An Obstacle Avoidance Technique of Quadrotor Using Immune Algorithm (면역 알고리즘을 이용한 쿼드로터 장애물회피 기술)

  • Son, Byung-Rak;Han, Chang-Seup;Lee, Hyun;Lee, Dong-Ha
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.5
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    • pp.269-276
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    • 2014
  • In recent, autonomous navigation techniques to avoid obstacles have been studied by using unmanned aircraft vehicles(UAVs) since the increment of UAV's interest and utilization. Particularly, autonomous navigation based UAVs are utilized in several areas such as military, police, media, and so on. However, there are still some problems to avoid obstacle when UVAs perform autonomous navigation. For instance, the UAV can not forward in the corner of corridors even though it utilizes the improved vanish point algorithm that makes an autonomous navigation system. Therefore, in this paper, we propose an obstacle avoidance technique based on immune algorithm for autonomous navigation of Quadrotor. The proposed algorithm is consisted of two steps such as 1) single color discrimination and 2) multiple color discrimination. According to the result of experiments, we can solve the previous problem of the improved vanish point algorithm and improve the performance of autonomous navigation of Quadrotor.

Manhole Cover Detection from Natural Scene Based on Imaging Environment Perception

  • Liu, Haoting;Yan, Beibei;Wang, Wei;Li, Xin;Guo, Zhenhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5095-5111
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    • 2019
  • A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

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.

Beam Tracking Method Using Unscented Kalman Filter for UAV-Enabled NR MIMO-OFDM System with Hybrid Beamforming

  • Yuna, Sim;Seungseok, Sin;Jihun, Cho;Sangmi, Moon;Young-Hwan, You;Cheol Hong, Kim;Intae, Hwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.280-294
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    • 2023
  • Unmanned aerial vehicles (UAVs) and millimeter-wave frequencies play key roles in supporting 5G wireless communication systems. They expand the field of wireless communication by increasing the data capacities of communication systems and supporting high data rates. However, short wavelengths, owing to the high millimeter-wave frequencies can cause problems, such as signal attenuation and path loss. To address these limitations, research on high directional beamforming technologies continue to garner interest. Furthermore, owing to the mobility of the UAVs, it is essential to track the beam angle accurately to obtain full beamforming gain. This study presents a beam tracking method based on the unscented Kalman filter using hybrid beamforming. The simulation results reveal that the proposed beam tracking scheme improves the overall performance in terms of the mean-squared error and spectral efficiency. In addition, by expanding analog beamforming to hybrid beamforming, the proposed algorithm can be used even in multi-user and multi-stream environments to increase data capacity, thereby increasing utilization in new-radio multiple-input multiple-output orthogonal frequency-division multiplexing systems.

Virtual Force(VF)-based Disaster Monitoring Network Using Multiple UAVs (대규모 공중무인기를 이용한 가상력 기반 재난 감시 네트워크)

  • Chun, Jeongmyong;Yoon, Seokhoon;Kim, Daeyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.4
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    • pp.97-108
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    • 2016
  • In this paper, we consider a cooperative monitoring network, which consists of a large number of UAVs, in order to promptly detect event in a disaster area. A command center may not be able to control each UAV individually due to resource constraints. Therefore, UAVs need to autonomously construct a mobile monitoring network in order to maximize monitoring coverage and to adapt the network formation according to environment changes in the disaster area. To that end, we propose multiple UAVs-based cooperative monitoring schemes that uses virtual forces. In this monitoring scheme, an effective monitoring is enabled by extending monitoring coverage using each UAV's circle movements. The UAVs-based monitoring network can also be splitted or merged in order to increase the monitoring effectiveness. Through simulations, we show that the proposed scheme can effectively monitor a large area and achieve a high event detection ratio.