• Title/Summary/Keyword: unmanned vehicle

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Development of an Unmanned Vehicle Driving system By the MR Sensor (MR센서를 이용한 무인 주행 시스템 설계)

  • 김창섭;박기선;이영진;이만형
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.05a
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    • pp.587-590
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    • 2000
  • By using the information obtained from output of the MR(Magneto Resistive) sensor for an unmanned vehicle system which is used in the Local Position System. We develop an algorithm that decides the distance and directions between the guideline made by magnets and vehicle, and make an unmanned vehicle driving system that is steered by PD controller and MR sensor

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H$\infty$ Steering Control of an Unmanned Vehicle Driving System by the MR sensors (MR 센서를 이용한 무인 자동 시스템의 H$\infty$ 조향 제어)

  • 박기선;김창섭;이영진;윤강섭;배종일;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.6-6
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    • 2000
  • By using the information obtained from the outputs of MR(MagnetoResistive) sensors for an Unmanned Vehicle Driving System, we develop an algorithm that decides the distance and direction between vehicle and the guideline which is made by the magnet. To improve the robust tracking properties of the closed loop system, we introduce H$\infty$ controller and its application for the Unmanned Vehicle Driving System.

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Research of the Unmanned Vehicle Control and Modeling for Lane Tracking and Obstacle Avoidance

  • Kim, Sang-Gyum;Lee, Woon-Sung;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.932-937
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    • 2003
  • In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

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Design and Development of Multi-rotorcraft-based Unmanned Prototypes of Personal Aerial Vehicle

  • Muljowidodo, Muljowidodo;Budiyono, Agus
    • International Journal of Aeronautical and Space Sciences
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    • v.10 no.2
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    • pp.140-147
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    • 2009
  • The paper presents the design, development and testing activities of the multi-rotorcraft-based unmanned aerial vehicle at the Center for Unmanned System Studies, Institut Teknologi Bandung (ITB), Indonesia. The multi-rotor system was selected as the design stepping stone for future development of personal aerial vehicle prototypes. A step-by-step design program is conducted to study the technology building blocks and critical issues associated with the design, development and operation of personal aerial vehicles. A number of multi-rotor configurations have been investigated providing basic guidelines for developing a stable unmanned aerial platform. The benefit of the presently selected configuration is highlighted and some preliminary testing results are presented.

Development of Ubuntu-based Raspberry Pi 3 of the image recognition system (우분투 기반 라즈베리 파이3의 영상 인식 시스템 개발)

  • Kim, Gyu-Hyun;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.868-871
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    • 2016
  • Recently, Unmanned vehicle and Wearable Technology using iot research is being carried out. The unmanned vehicle is the result of it technology. Robots, autonomous navigation vehicle and obstacle avoidance, data communications, power, and image processing, technology integration of a unmanned vehicle or an unmanned robot. The final goal of the unmanned vehicle manual not autonomous by destination safely and quickly reaching. This paper managed to cover One of the key skills of unmanned vehicle is to image processing. Currently battery technology of unmanned vehicle can drive for up to 1 hours. Therefore, we use the Raspberry Pi 3 to reduce power consumption to a minimum. Using the Raspberry Pi 3 and to develop an image recognition system. The goal is to propose a system that recognizes all the objects in the image received from the camera.

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A Study on Requirement Analysis of Unmanned Combat Vehicles: Focusing on Remote-Controlled and Autonomous Driving Aspect (무인전투차량 요구사항분석 연구: 원격통제 및 자율주행 중심으로)

  • Dong Woo, Kim;In Ho, Choi
    • Journal of the Korean Society of Systems Engineering
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    • v.18 no.2
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    • pp.40-49
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    • 2022
  • Remote-controlled and autonomous driving based on artificial intelligence are key elements required for unmanned combat vehicles. The required capability of such an unmanned combat vehicle should be expressed in reasonable required operational capability(ROC). To this end, in this paper, the requirements of an unmanned combat vehicle operated under a manned-unmanned teaming were analyzed. The functional requirements are remote operation and control, communication, sensor-based situational awareness, field environment recognition, autonomous return, vehicle tracking, collision prevention, fault diagnosis, and simultaneous localization and mapping. Remote-controlled and autonomous driving of unmanned combat vehicles could be achieved through the combination of these functional requirements. It is expected that the requirement analysis results presented in this study will be utilized to satisfy the military operational concept and provide reasonable technical indicators in the system development stage.

Development of an Intelligent Unmanned Vehicle Control System (지능형 무인자동차 제어시스템 개발)

  • Kim, Yoon-Gu;Lee, Ki-Dong
    • IEMEK Journal of Embedded Systems and Applications
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    • v.3 no.3
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    • pp.126-135
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    • 2008
  • The development of an unmanned vehicle basically requires the robust and reliable performance of major functions which include global localization, lane detection, obstacle avoidance, path planning, etc. The implementation of major functional subsystems are possible by integrating and fusing data acquired from various sensory systems such as GPS, vision, ultrasonic sensor, encoder, and electric compass. This paper focuses on implementing the functional subsystems, which are designed and developed by a graphical programming tool, NI LabVIEW, and also verifying the autonomous navigation and remote control of the unmanned vehicle.

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Development of Steering Actuator for Unmanned Vehicle Based on Magnetic Marker (자계기반 무인차량을 위한 조향장치의 개발)

  • Im, Dae-Yeong;Ryoo, Young-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.375-380
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    • 2009
  • In this paper, a steering actuator is designed and developed for an unmanned vehicle based on magnetic marker. One of the most important component of an unmanned vehicle is a steering actuator to follow magnetic road. Thus, we develop a steering actuator using a stepping motor and adopt to a new frequency control method depended on speed of the vehicle. In order to verify the usability of the developed system, the setup of unmanned vehicle installed the designed steering actuator is tested on magnetic road.

The Development of Obstacle Avoidance Algorithm for Unmanned Vehicle Using Ultrasonic Sensor

  • Yu, Whan-Sin;Lee, Woon-Sung;Kim, Jung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.408-412
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    • 2003
  • Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.

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UNMANNED VEHICLE CONTROL AND MODELING FOR OBSTACLE AVOIDANCE

  • Kim, S.-G.;Kim, J.-H.
    • International Journal of Automotive Technology
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    • v.4 no.4
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    • pp.173-180
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    • 2003
  • Obstacle avoidance is considered as one of the key technologies in an unmanned vehicle system. In this paper, we propose a method of obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. Obstacle avoidance consists of two parts: one longitudinal control system for acceleration; and deceleration and a lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. The method proposed for vehicle control, modeling, and obstacle avoidance has been confirmed through vehicle tests.