• Title/Summary/Keyword: drone control

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Analysis of Surface Image Velocity Field without Ground Control Points using Drone Navigation Information (드론의 비행정보를 이용한 지상표정점 없는 표면유속장 분석)

  • Yu, Kwonkyu;Lee, Junhyeong
    • Ecology and Resilient Infrastructure
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    • v.9 no.3
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    • pp.154-162
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    • 2022
  • In this study, a technique for estimating water surface velocity fields in the Universal Transverse Mercator coordinate system using the GPS information of a propagating drone but not ground control points is developed. First, we determine the image direction in which the upper side of an image is directed based on the navigation information of the drone. Subsequently, we assign the start and end frames of the video used and determine the analysis range. Using these two frames, we segment the measurement cross-section into a few subsections at regular intervals. At these subsections, we analyze 30 frame images to create spatio-temporal volumes for calculating the velocity fields. The results of the developed method (propagating drone surface image velocimetry) are compared with those of the existing method (hovering drone surface image velocimetry), and relatively good agreement is indicated between both in terms of the velocity fields.

Drone Hovering using PID Control (PID 제어를 이용한 드론의 호버링)

  • Oh, Ji-Wan;Seol, Jae-Won;Gong, Youn-Hee;Han, Seung-Jae;Lee, Seung-Dae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.6
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    • pp.1269-1274
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    • 2018
  • In this paper, it covers technical aspect of drone by introducing the drone hovering. Arduino Uno and 3-axis attitude and azimuth sensor are the two main components of the drone. Arduino Uno is used as a main controller and 3-axis attitude and azimuth sensor are used to collect axial (X,Y,Z) data, which is massaged to determine the pitch (fore and aft tilt) and the bank (side to side tilt). Furthermore, drone stabilizes horizontal attitude by correcting these tilted angle through PID control.

Multi-Purpose Integrated Training Drone to Prevent Safety Accidents (안전사고방지를 위한 다목적 결속형 교육용 드론)

  • Son, Min-Woo;Ju, Yeong-Tae;Kim, Jong-Sil;Kim, Eung-Kon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.1
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    • pp.145-150
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    • 2021
  • Currently, as the interest in drones has increased and the use of drones has increased rapidly, the number of people trying to learn drones is increasing. However, drones are difficult to manipulate, and accidents are likely to occur if they are not learned accordingly, and drones are broken easily. In this study, we developed a multi-purpose drone that can bind the drone to a safety bar to prevent safety accidents and damage of the drone, and expand sensors and control devices through blocks.

Implementation of Intra-Partition Communication in Layered ARINC 653 for Drone Flight-Control Program (드론 비행제어 프로그램을 위한 계층적 ARINC 653의 파티션 내 통신 구현)

  • Park, Joo-Kwang;Kim, Jooho;Jo, Hyun-Chul;Jin, Hyun-Wook
    • Journal of KIISE
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    • v.44 no.7
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    • pp.649-657
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    • 2017
  • As the type and purpose of drones become diverse and the number of additional functions is increasing, the role of the corresponding software has increased. Through partitioning and an efficient solving of SWaP(size, weight and power) problems, ARINC 653 can provide reliable software reuse and consolidation regarding avionic systems. ARINC 653 can be more effectively applied to drones, a small unmanned aerial vehicle, in addition to its application with large-scale aircraft. In this paper, to exploit ARINC 653 for a drone flight-control program, an intra-partition communication system is implemented through an extension of the layered ARINC 653 and applied to a real drone system. The experiment results show that the overheads of the intra-partition communication are low, while the resources that are assigned to the drone flight-control program are guaranteed through the partitioning.

Design of Deep Learning-Based Automatic Drone Landing Technique Using Google Maps API (구글 맵 API를 이용한 딥러닝 기반의 드론 자동 착륙 기법 설계)

  • Lee, Ji-Eun;Mun, Hyung-Jin
    • Journal of Industrial Convergence
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    • v.18 no.1
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    • pp.79-85
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    • 2020
  • Recently, the RPAS(Remote Piloted Aircraft System), by remote control and autonomous navigation, has been increasing in interest and utilization in various industries and public organizations along with delivery drones, fire drones, ambulances, agricultural drones, and others. The problems of the stability of unmanned drones, which can be self-controlled, are also the biggest challenge to be solved along the development of the drone industry. drones should be able to fly in the specified path the autonomous flight control system sets, and perform automatically an accurate landing at the destination. This study proposes a technique to check arrival by landing point images and control landing at the correct point, compensating for errors in location data of the drone sensors and GPS. Receiving from the Google Map API and learning from the destination video, taking images of the landing point with a drone equipped with a NAVIO2 and Raspberry Pi, camera, sending them to the server, adjusting the location of the drone in line with threshold, Drones can automatically land at the landing point.

Development of an intuitive motion-based drone controller (직관적 제어가 가능한 드론과 컨트롤러 개발)

  • Seok, Jung-Hwan;Han, Jung-Hee;Baek, Jun-Hyuk;Chang, Won-Joo;Kim, Huhn
    • Design & Manufacturing
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    • v.11 no.3
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    • pp.41-45
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    • 2017
  • Drones can be manipulated in a variety of ways. One of the most common controller is joystick method. But joystick controller uses both hands and takes a long time to learn. Particularly, in the case of 8-character flight, it is necessary to use both front and rear flight (pitch), left and right flight (Roll), and body rotation (Yaw). Joystick controller has limitations to intuitively control it. In particular, when the main body rotates, the viewpoint of the forward direction is changed between the drones and the user, thereby causing a mental rotation problem in which the user must control the rotating state of the drones. Therefore, we developed a motion matching controller that matches the motion of the drones and the controller. That is, the movement of the drone and the movement of the controller are the same. In this study, we used a gyro sensor and an acceleration sensor to map the controller's forward / backward, left / right and body rotation movements to drone's forward / backward, left / right, and rotational flight motion. The motor output is controlled by the throttle dial at the center of the controller. As the motions coincide with each other, it is expected that the first drone operator will be able to control more intuitively than the joystick manipulator with less learning.

Mechanism Development and Heading Control of Catamaran-type Sail Drone

  • Man, Dong-Woo;Kim, Hyun-Sik
    • Journal of Ocean Engineering and Technology
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    • v.35 no.5
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    • pp.360-368
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    • 2021
  • The need for energy harvesting in marine environments is gradually increasing owing to the energy limitation of marine robots. To address this problem, a catamaran-type sail drone (CSD), which can harvest marine energies such as wind and solar, was proposed in a previous study. However, it was designed and manufactured without considering the stability, optimal hull-form, and maintenance. To resolve these problems, a CSD with two keels, a performance estimator, V-shape hulls, and modularized components is proposed and its mechanism is developed in this study. To verify the performance of the CSD, the performance estimation using smoothed-particle hydrodynamics (SPH) and the heading control using fuzzy logic controller (FLC) are performed. Simulation results show the attitude stability of the CSD and the experimental results show the straight path of the CSD according to wind conditions. Therefore, the CSD has potential applications as an energy harvesting system.

Gimbal System Control for Drone for 3D Image (입체영상 촬영을 위한 드론용 짐벌시스템 제어)

  • Kim, Min;Byun, Gi-Sig;Kim, Gwan-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.11
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    • pp.2107-2112
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    • 2016
  • This paper is designed to develop a Gimbal control stabilizer for drones Gimbal system control for drone for 3D image to make sure clean image in the shaking and wavering environments of drone system. The stabilizer is made of tools which support camera modules and IMU(Inertial Measurement Unit) sensor modules follow exact angles, which can brock vibrations outside of the camera modules. It is difficult for the camera modules to get clean image, because of irregular movements and various vibrations produced by flying drones. Moreover, a general PID controller used for the movements of rolling, pitching and yawing in order to control the various vibrations of various frequencies needs often to readjust PID control parameters. Therefore, this paper aims to conduct the Intelligent-PID controller as well as design the Gimbal control stabilizer to get clean images and to improve irregular movements and various vibrations problems referenced above.

Design of an Exploration Drone for Digital Twin based Building Control

  • Shin, Sang-Hoon;Park, Myeong-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.5
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    • pp.9-16
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    • 2021
  • In this paper, we propose a building exploration drone that can be used for a digital twin-based building control system. The existing building control system using a fixed position sensor box has a problem that a management blind spot occurs. And because people patrol themselves, it takes a lot of human resources. In this paper, a drone equipped with a temperature and humidity sensor and a gas leak detection sensor is used to search the internal path of the building centering on the control blind spot. It also aims to solve the problem of the building control system by transmitting information in real time along with the video. In addition, it has a stable hovering function using an optical floor sensor and can be applied to an existing digital twin-based building control system. The results of this study are believed to be of great help in improving the quality of digital twin control systems using drones.

Smart Glove Gimbal Control that Improves the Convenience of Drone Control (드론 제어의 편의성을 향상한 스마트 글러브 짐벌 제어)

  • Lee, Seung Ho;Shin, Soo Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.6
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    • pp.890-896
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    • 2022
  • In this paper, gimbal camera control through smart gloves was implemented to increase convenience and accessibility to the control of drones used in various fields. Smart gloves identify human gestures and transmit signals through Bluetooth. The received signal is converted into a signal suitable for the drone through a GCS (Gound Control Station). Signals from smart gloves are expressed in a quaternion method to prevent gimbal locks, but for gimbal cameras, conversion is required to use Roll, Pitch, and Yaw methods. The data conversion mission is performed in the GCS. The GCS transmits an input signal to the control board of the drone through Wi-Fi. The control board generates and outputs the transmitted signal in a PWM manner. The output signal is input to the gimbal camera through the SBUS method and controlled. The input signal of the smart glove averaged 0.093 s and up to 0.099 s to output to the gimbal camera, showing that there was no problem in real-time use.