• Title/Summary/Keyword: multiple UAVs

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Genetic algorithm based multi-UAV mission planning method considering temporal constraints (시간 제한 조건을 고려한 유전 알고리즘 기반 다수 무인기 임무계획기법)

  • Byeong-Min Jeong;Dae-Sung Jang;Nam-Eung Hwang;Joon-Won Kim;Han-Lim Choi
    • Journal of Aerospace System Engineering
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    • v.17 no.2
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    • pp.78-85
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    • 2023
  • For Multi-UAV systems, a task allocation could be a key factor to determine the capability to perform a task. In this paper, we proposed a task allocation method based on genetic algorithm for minimizing makespan and satisfying various constraints. To obtain the optimal solution of the task allocation problem, a huge calculation effort is necessary. Therefore, a genetic algorithm-based method could be an alternative to get the answer. Many types of UAVs, tasks, and constraints in real worlds are introduced and considered when tasks are assigned. The proposed method can build the task sequence of each UAV and calculate waiting time before beginning tasks related to constraints. After initial task allocation with a genetic algorithm, waiting time is added to satisfy constraints. Multiple numerical simulation results validated the performance of this mission planning method with minimized makespan.

Simulation Approach for the Tracing the Marine Pollution Using Multi-Remote Sensing Data (다중 원격탐사 자료를 활용한 해양 오염 추적 모의 실험 방안에 대한 연구)

  • Kim, Keunyong;Kim, Euihyun;Choi, Jun Myoung;Shin, Jisun;Kim, Wonkook;Lee, Kwang-Jae;Son, Young Baek;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.249-261
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    • 2020
  • Coastal monitoring using multiple platforms/sensors is a very important tools for accurately understanding the changes in offshore marine environment and disaster with high temporal and spatial resolutions. However, integrated observation studies using multiple platforms and sensors are insufficient, and none of them have been evaluated for efficiency and limitation of convergence. In this study, we aimed to suggest an integrated observation method with multi-remote sensing platform and sensors, and to diagnose the utility and limitation. Integrated in situ surveys were conducted using Rhodamine WT fluorescent dye to simulate various marine disasters. In September 2019, the distribution and movement of RWT dye patches were detected using satellite (Kompsat-2/3/3A, Landsat-8 OLI, Sentinel-3 OLCI and GOCI), unmanned aircraft (Mavic 2 pro and Inspire 2), and manned aircraft platforms after injecting fluorescent dye into the waters of the South Sea-Yeosu Sea. The initial patch size of the RWT dye was 2,600 ㎡ and spread to 62,000 ㎡ about 138 minutes later. The RWT patches gradually moved southwestward from the point where they were first released,similar to the pattern of tidal current flowing southwest as the tides gradually decreased. Unmanned Aerial Vehicles (UAVs) image showed highest resolution in terms of spatial and time resolution, but the coverage area was the narrowest. In the case of satellite images, the coverage area was wide, but there were some limitations compared to other platforms in terms of operability due to the long cycle of revisiting. For Sentinel-3 OLCI and GOCI, the spectral resolution and signal-to-noise ratio (SNR) were the highest, but small fluorescent dye detection was limited in terms of spatial resolution. In the case of hyperspectral sensor mounted on manned aircraft, the spectral resolution was the highest, but this was also somewhat limited in terms of operability. From this simulation approach, multi-platform integrated observation was able to confirm that time,space and spectral resolution could be significantly improved. In the future, if this study results are linked to coastal numerical models, it will be possible to predict the transport and diffusion of contaminants, and it is expected that it can contribute to improving model accuracy by using them as input and verification data of the numerical models.

Physical Offset of UAVs Calibration Method for Multi-sensor Fusion (다중 센서 융합을 위한 무인항공기 물리 오프셋 검보정 방법)

  • Kim, Cheolwook;Lim, Pyeong-chae;Chi, Junhwa;Kim, Taejung;Rhee, Sooahm
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1125-1139
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    • 2022
  • In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

Design of C-Band Frequency Up-Converter in Communication System for Unmanned Aerial Vehicle (무인 항공기의 통신 시스템에 사용되는 C-대역 주파수 상향 변환기 설계)

  • Lee, Duck-Hyung;Oh, Hyun-Seok;Jeong, Hae-Chang;Yeom, Kyung-Whan
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.20 no.9
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    • pp.843-852
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    • 2009
  • In this paper, we present design, fabrication, and measured results for a frequency upconverter for a wireless communication system of UAV(Unmanned Aerial Vehicle). The specifications of such wireless communication system requires the special features of maximum range of communication as well as deployment in UAV and repairing. The frequency upconverter operating at $5.25{\sim}5.45\;GHz$ in C-band was designed and fabricated considering such special features. The AGC function was included because the required output power should be constant for optimal system operation. The fabricated upconverter showed a constant output power of $+2{\pm}0.5\;dBm$ for the $-15{\sim}-10\;dBm$ input. Spuriouses were below -60 dBc and the adjacent leakage power was below -40 dBc. In addition, LO sources in the upconverter was implemented using the frequency synthesizer with step 1 MHz. This is for the application to the situation where multiple UAVs employed and the possible change of the permitted frequency band. The synthesizer showed a phase noise of -100 dBc/Hz at the 100 kHz frequency offset.

Development of relational river data model based on river network for multi-dimensional river information system (다차원 하천정보체계 구축을 위한 하천네트워크 기반 관계형 하천 데이터 모델 개발)

  • Choi, Seungsoo;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.51 no.4
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    • pp.335-346
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    • 2018
  • A vast amount of riverine spatial dataset have recently become available, which include hydrodynamic and morphological survey data by advanced instrumentations such as ADCP (Acoustic Doppler Current Profiler), transect measurements obtained through building various river basic plans, riverine environmental and ecological data, optical images using UAVs, river facilities like multi-purposed weir and hydrophilic sectors. In this regard, a standardized data model has been subsequently required in order to efficiently store, manage, and share riverine spatial dataset. Given that riverine spatial dataset such as river facility, transect measurement, time-varying observed data should be synthetically managed along specified river network, conventional data model showed a tendency to maintain them individually in a form of separate layer corresponding to each theme, which can miss their spatial relationship, thereby resulting in inefficiency to derive synthetic information. Moreover, the data model had to be significantly modified to ingest newly produced data and hampered efficient searches for specific conditions. To avoid such drawbacks for layer-based data model, this research proposed a relational data model in conjunction with river network which could be a backbone to relate additional spatial dataset such as flowline, river facility, transect measurement and surveyed dataset. The new data model contains flexibility to minimize changes of its structure when it deals with any multi-dimensional river data, and assigned reach code for multiple river segments delineated from a river. To realize the newly developed data model, Seom river was applied, where geographic informations related with national and local rivers are available.

Operational Ship Monitoring Based on Multi-platforms (Satellite, UAV, HF Radar, AIS) (다중 플랫폼(위성, 무인기, AIS, HF 레이더)에 기반한 시나리오별 선박탐지 모니터링)

  • Kim, Sang-Wan;Kim, Donghan;Lee, Yoon-Kyung;Lee, Impyeong;Lee, Sangho;Kim, Junghoon;Kim, Keunyong;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.36 no.2_2
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    • pp.379-399
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    • 2020
  • The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.