• Title/Summary/Keyword: 농업용 UAV

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Implementation of Agricultural Multi-UAV System with Distributed Swarm Control Algorithm into a Simulator (분산군집제어 알고리즘 기반 농업용 멀티 UAV 시스템의 시뮬레이터 구현)

  • Ju, Chanyoung;Park, Sungjun;Son, Hyoung Il
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2017.04a
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    • pp.37-38
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    • 2017
  • 최근 방제 및 예찰과 같은 농작업에 단일 UAV(Unmanned Aerial Vehicle)시스템이 적용되고 있지만, 가반하중과 체공시간 등 기존시스템의 문제가 점차 대두되면서 작업 시간을 보다 단축시키고 작업 효율을 극대화 할 수 있는 농업용 멀티 UAV시스템의 필요성이 증대되고 있다. 본 논문에서는 작업자가 다수의 농업용 UAV를 효과적으로 제어할 수 있는 분산군집제어 알고리즘을 제안하며 알고리즘 검증 및 평가를 위한 시뮬레이터를 소개한다. 분산군집제어는 UAV 제어 계층, VP(Virtual Point) 제어 계층, 원격제어 계층으로 이루어진 3계층 제어구조를 가진다. UAV 제어 계층에서 각 UAV는 point mass로 모델링 되는 VP의 이상적인 경로를 추종하도록 제어한다. VP 제어 계층에서 각 VP는 입력 $p_i(t)=u^c_i+u^o_i+u^{co}_i+u^h_i$-(1)을 받아 제어되는데 여기서, $u^c_i{\in}{\mathbb{R}}^3$는 VP 사이의 충돌방지제어, $u^o_i{\in}{\mathbb{R}}^3$는 장애물과의 충돌방지제어, $u^{co}_i{\in}{\mathbb{R}}^3$는 UAV 상호간의 협조제어, $u^h_i{\in}{\mathbb{R}}^3$는 작업자로부터의 원격제어명령이다. (1)의 제어입력에서 충돌방지제어는 각 $u^i_c:=-{\sum\limits_{j{\in}{\eta}_i}}{\frac {{\partial}{\phi}_{ij}^c({\parallel}p_i-p_j{\parallel})^T}{{\partial}p_i}}$-(2), $u^o_c:=-{\sum\limits_{r{\in}O_i}}{\frac {{\partial}{\phi}_{ir}^o({\parallel}p_i-p^o_r{\parallel})^T}{{\partial}p_i}}$-(3)로 정의되면 ${\phi}^c_{ij}$${\phi}^o_{ir}$는 포텐셜 함수를 나타낸다. 원격제어 계층에서 작업자는 햅틱 인터페이스를 통해 VP의 속도를 제어하게 된다. 이때 스케일변수 ${\lambda}$에 대하여 VP의 원격제어명령은 $u^t_i(t)={\lambda}q(t)$로 정의한다. UAV 시뮬레이터는 리눅스 환경에서 ROS(Robot Operating Systems)를 기반한 3차원 시뮬레이터인 Gazebo상에 구축하였으며, 마스터와 슬레이브 간의 제어 명령은 TCPROS를 통해 서로 주고받는다. UAV는 PX4 기반의 3DR Solo 모델을 사용하였으며 MAVROS를 통해 MAVLink 통신 프로토콜에 접속하여 UAV의 고도, 속도 및 가속도 등의 상태정보를 받을 수 있다. 현재 멀티 드론 시스템을 Gazebo 환경에 구축하였으며, 추후 시뮬레이터 상에 분산군집제어 알고리즘을 구현하여 검증 및 평가를 진행하고자 한다.

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Susceptibility of Myzus persicae on Potato field and Riptortus clavatus on Soybean field to Insecticides treated by Multi-copter (농업용 멀티콥터를 활용한 감자의 복숭아혹진딧물과 콩의 톱다리개미허리노린재의 약제방제 효율)

  • Park, Bueyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.231-236
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    • 2021
  • The Aphid, Myzus persicae, and the bean bug, Riptortus clavatus, are major insects in crops. This study examined the insecticide susceptibility and phytotoxicity of insecticides dispersed using an Unmanned Aerial Vehicle (UAV, multi-copter) against the insects. Sulfoxaflor suspension concentrate (SC, 16X) on potato fields and etofenprox, methoxyfenzide suspo-emulsion(SE, 8X) on soybean fields were dispersed after deploying water-sensitive paper within the field to measure the distribution pattern and coverage index of the falling insecticide. Both insecticides showed a controlled mortality of 76.4% against aphids and 97.5% and 94.4% against the 2nd nymphal, and 5th nymphal stage of the bugs, respectively. The droplet distribution was less than 0.5mm, and coverage analysis revealed an inside and outside coverage of 3.1 and 1.6, respectively. The surrounding area was affected by insecticide spraying using a multi-copter. This study is expected to help expand UAV control and use it safely in the future.

Autonomous landing of drones using deep learning GPS-denied environments (GPS 음영지역에서 딥러닝을 활용한 드론 자율 착륙)

  • Chae-Hui Park;Sung-Mahn Ahn
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.15-18
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    • 2023
  • UAV는 군사용을 처음 시작으로 근래에 취미용 드론의 급격한 성장과 더불어 최근 기후변화, 교통혼잡, 범죄 예방 등 여러 사회 문제 해결을 위한 드론의 필요성이 증가함에 따라 건설, 교통, 농업, 에너지, 엔터테인먼트 등 다양한 산업과 여러 사회 서비스로 그 필요성이 확대되고 있다. 본 연구는 이러한 사회적 흐름에 따라 인공지능 기술을 통한 드론의 활용성을 확대하고 GPS 수신이 안 되는 환경에서 딥러닝 객체 탐지 모델을 활용한 자율 착륙을 연구를 목표로 한다. GPS 신호는 실내와 같은 환경 혹은 지하, 교량 아래, 산속 등과 같은 곳에서는 수신이 어렵다. 이를 극복하고자 GPS 신호수신이 어려운 지역에서 GPS 수신기를 통해 받는 위치 정보 대신 드론에 장착된 카메라를 통해 전달받는 영상에서 착륙할 지점을 인식하고 카메라를 통해 받는 영상 정보만 이용하여 목표지점으로 하강하는 방식으로 자율 착륙을 유도한다. 딥러닝 중 경량화 모델을 활용하여 소형 드론에서 실시간으로 착륙 지점을 감지하기 위해 최적화 과정을 진행해 실시간 자율 착륙이 가능하게 하였다. 본 연구를 통해 드론의 착륙에 있어 GPS 수신기와 사람의 조종에 대한 의존도를 낮출 수 있을 것으로 기대한다.

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Comparison of Each Commercial Nozzle on the Application Pattern of Pesticide for Unmanned Aerial Vehicles (UAV) (농업용 멀티콥터를 활용한 무인항공기용 작물보호제 살포양상에 대한 상용노즐별 차이)

  • Park, Bueyong;Jeong, In-Hong;Kim, Sun Woo;Kim, Gil-Hah
    • Korean journal of applied entomology
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    • v.60 no.2
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    • pp.229-234
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    • 2021
  • This study investigated spray patterns and coverage generated by three types of commercial nozzles for spraying pesticides with Unmanned Aerial Vehicles (UAVs) using a multi-copter. Flufenoxuron+metaflumizone SC and bifenthrin EC were sprayed. The falling particles of the spraying agent were measured using WSP (Water and oil Sensitive Paper) and the coverage was determined. The results showed that the uniformity of falling particles was different according to the difference in wind strength, and there was no difference for different formulations. The injection amount for each nozzle was found to be different from the official information provided by the manufacturers. These results could be used to establish guidelines for the control of UAVs and pesticide registration testing.

Estimation of Break Outflow from the Goeyeon Reservoir Using DAMBRK Model (DAMBRK 모형을 이용한 괴연저수지 붕괴유출량 추정)

  • Lee, Jin Young;Park, Dong Hyeok;Kim, Seong-Joon;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.37 no.2
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    • pp.459-466
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    • 2017
  • Several reservoirs that were managed by local governments and the Korea Rural Community Corporation have recently collapsed. One of them is the Goeyeon reservoir in Yeongcheon-si, Gyeongsangbuk-do that collapsed mainly around the spillway due to heavy rain at 9 O'clock, on 21 August 2014. The Goeyeon reservoir was an aging agricultural reservoir over 70 years since it was built. In this study, the collapse situation of the reservoir was reproduced through the DAMBRK model. Flood inundation maps were reconstructed for the breach outflow of the dam analyzed by the DAMBRK model. We estimated the breach duration and outflow of the reservoir as compared with the inundation image taken by the Unmanned Aerial Vehicle (UAV) at the time when the Goeyeon reservoir collapsed. The results of this study are expected to be useful for predicting damage in the downstream inundation area when a reservoir collapses.

A Study on Efficient Methods of Pesticide Control Using Agricultural Unmanned Aerial Vehicles (농업용 무인항공기를 활용한 농약방제 효율성 방안에 관한 연구)

  • Jeong, Ga-Young;Cho, Yong-Yoon
    • Journal of Internet of Things and Convergence
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    • v.8 no.2
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    • pp.35-40
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    • 2022
  • In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

A Study on the Effective Military Use of Drones (드론의 효과적인 군사분야 활용에 관한 연구)

  • Lee, Young Uk
    • Convergence Security Journal
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    • v.20 no.4
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    • pp.61-70
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    • 2020
  • The unmanned aerial vehicle that emerged with the 4th Industrial Revolution attracts attention not only from Korea but also from around the world, and its utilization and market size are gradually expanding. For the first time, it was used for military purposes, but it is currently used for transportation, investigation, surveillance, and agriculture. China, along with the US and Europe, is emerging as a leader in the commercial unmanned aerial vehicle market, and Korea, which has the world's seventh-largest technology in related fields, is striving to promote various technology development policies and system improvement related to unmanned aerial vehicles. Military drones will revolutionize the means of war by using a means of war called an unmanned system based on theories such as network-oriented warfare and effect-oriented warfare. Mobile equipment, including drones, is greatly affected by environmental factors such as terrain and weather, as well as technological developments and interests in the field. Now, drones are being used actively in many fields, and especially in the military field, the use of advanced drones is expected to create a new defense environment and provide a new paradigm for war.

Multi-resolution SAR Image-based Agricultural Reservoir Monitoring (농업용 저수지 모니터링을 위한 다해상도 SAR 영상의 활용)

  • Lee, Seulchan;Jeong, Jaehwan;Oh, Seungcheol;Jeong, Hagyu;Choi, Minha
    • Korean Journal of Remote Sensing
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    • v.38 no.5_1
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    • pp.497-510
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    • 2022
  • Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.