• Title/Summary/Keyword: mobile vision system

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Inch-Worm Robot with Automatic Pipe Tracking Capability for the Feeder Pipe Inspection of a PHWR (중수형 원자로 급수 배관 검사용 자율 주행형 자벌레 로봇)

  • Choi, Chang-Hwan;Park, Byung-Suk;Jung, Hyun-Kyu;Jung, Seung-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.2
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    • pp.125-132
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    • 2008
  • This paper describes a mobile inspection robot with an automatic pipe tracking system for a feeder pipe inspection in a PHWR. The robot is composed of two inch worm mechanisms. One is for a longitudinal motion along a pipe, and the other is for a rotational motion in a circumferential direction to access all of the outer surfaces of a pipe. The proposed mechanism has a stable gripping capability and is easy to install. An automatic pipe tracking system is proposed based on machine vision techniques to make the mobile robot follow an exact outer circumference of a curved feeder pipe as closely as possible, which is one of the requirements of a thickness measurement system for a feeder pipe. The proposed sensing technique is analyzed to attain its feasibility and to develop a calibration method for an accurate measurement. A mobile robot and control system are developed, and the automatic pipe tracking system is tested in a mockup of a feeder pipe.

Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.

A Study on Detection of Lane and Situation of Obstacle for AGV using Vision System (비전 시스템을 이용한 AGV의 차선인식 및 장애물 위치 검출에 관한 연구)

  • 이진우;이영진;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2000.11a
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    • pp.207-217
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    • 2000
  • In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

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Visual Navigation by Neural Network Learning (신경망 학습에 의한 영상처리 네비게이션)

  • Shin, Suk-Young;Hoon Kang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.263-266
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    • 2001
  • It has been integrated into several navigation systems. This paper shows that system recognizes difficult indoor roads and open area without any specific mark such as painted guide line or tape. In this method, Robot navigates with visual sensors, which uses visual information to navigate itself along the road. An Artificial Neural Network System was used to decide where to move. It is designed with USB web camera as visual sensor.

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Autofocusing System for Mobile Camera Phone (카메라폰의 신뢰성과 고정밀도를 높이는 자동포커스 렌즈시스템 구현)

  • Korea Optical Industry Association
    • The Optical Journal
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    • s.102
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    • pp.65-69
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    • 2006
  • VGA급에서 1.3메가, 그리고 2메가급의 휴대폰용 카메라제품이 속속 등장함에 따라 작업자의 육안검사에 의존하던 카메라모듈의 초점검사공정에서 다양한 Vision 및 소프트웨어를 이용한 자동화 설비의 개발 수요가 급증하고 있다. 당사에서는 이미 약 2년 전부터 이와 같은 시장의 추세를 예측하여 별도 변환렌즈를 통한 자동포커스 조절 시스템의 구현을 통해 메가급 이상의 다양한 휴대폰용 카메라모듈의 변화에도 유연성 있게 대처할 수 있는 Autofocusing System을 자체 개발한바 있다. 따라서 본 고에서는 이 시스템 구현을 통해 실제 양산에 적용 가능한 제품을 소개하고자 한다.

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3D Omni-directional Vision SLAM using a Fisheye Lens Laser Scanner (어안 렌즈와 레이저 스캐너를 이용한 3차원 전방향 영상 SLAM)

  • Choi, Yun Won;Choi, Jeong Won;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.7
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    • pp.634-640
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    • 2015
  • This paper proposes a novel three-dimensional mapping algorithm in Omni-Directional Vision SLAM based on a fisheye image and laser scanner data. The performance of SLAM has been improved by various estimation methods, sensors with multiple functions, or sensor fusion. Conventional 3D SLAM approaches which mainly employed RGB-D cameras to obtain depth information are not suitable for mobile robot applications because RGB-D camera system with multiple cameras have a greater size and slow processing time for the calculation of the depth information for omni-directional images. In this paper, we used a fisheye camera installed facing downwards and a two-dimensional laser scanner separate from the camera at a constant distance. We calculated fusion points from the plane coordinates of obstacles obtained by the information of the two-dimensional laser scanner and the outline of obstacles obtained by the omni-directional image sensor that can acquire surround view at the same time. The effectiveness of the proposed method is confirmed through comparison between maps obtained using the proposed algorithm and real maps.

Visual Cell OOK Modulation : A Case Study of MIMO CamCom (시각 셀 OOK 변조 : MIMO CamCom 연구 사례)

  • Le, Nam-Tuan;Jang, Yeong Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.9
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    • pp.781-786
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    • 2013
  • Multiplexing information over parallel data channels based on RF MIMO concept is possible to achieve considerable data rates over large transmission ranges with just a single transmitting element. Visual multiplexing MIMO techniques will send independent streams of bits using the multiple elements of the light transmitter array and recording over a group of camera pixels can further enhance the data rates. The proposed system is a combination of the reliance on computer vision algorithms for tracking and OOK cell frame modulation. LED array are controlled to transmit message in the form of digital information using ON-OFF signaling with ON-OFF pulses (ON = bit 1, OFF = bit 0). A camera captures image frames of the array which are then individually processed and sequentially decoded to retrieve data. To demodulated data transmission, a motion tracking algorithm is implemented in OpenCV (Open source Computer Vision library) to classify the transmission pattern. One of the most advantages of proposed architecture is Computer Vision (CV) based image analysis techniques which can be used to spatially separate signals and remove interferences from ambient light. It will be the future challenges and opportunities for mobile communication networking research.

Automated Data Collection and Intelligent Management System for Construction Site Disaster Prevention

  • Chang-Yong Yi;Young-Jun Park;Tae-Yong Go;Jin-Young Park;Hyung-Keun Park;Dong-Eun Lee
    • International conference on construction engineering and project management
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    • 2024.07a
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    • pp.731-737
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    • 2024
  • The accident rate in the South Korean construction industry has increased by 50% over the past ten years, reaching seven times the average growth rate of the entire industry. However, the number of management personnel at construction sites is decreasing, making it increasingly difficult to establish a safety monitoring system through professional personnel. This study aims to develop an intelligent control system to address the problem of insufficient management personnel and support the establishment of a continuous safety monitoring system. This system consists of a mobile information collection robot (S-BOT) and an intelligent algorithm. The visual information collected by S-BOT can be analyzed in real-time using computer vision-based intelligent algorithms to detect unsafe situations. The results of this study will contribute to preventing unnecessary social and economic losses by maximizing safety management efficiency and supporting timely decision-making through the sharing of information provided by the intelligent control system.

The Obstacle Avoidance Algorithm of Mobile Robot using Line Histogram Intensity (Line Histogram Intensity를 이용한 이동로봇의 장애물 회피 알고리즘)

  • 류한성;최중경;구본민;박무열;윤경섭;윤석영
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.331-334
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    • 2002
  • In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance. This is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until recognize obstacle from input image that preprocessed by edge detection, converting, thresholding. And it could avoid the obstacle when recognize obstacle by line histogram intensity. Host PC measurement wave from various line histogram each 20 Pixel. This histogram Is ( x , y ) value of pixel. For example, first line histogram intensity wave from ( 0, 0 ) to ( 0, 197 ) and last wave from ( 280, 0 ) to ( 280, 197 ). So we find uniform wave region and nonuniform wave region. The period of uniform wave is obstacle region. we guess that algorithm is very useful about moving robot for obstacle avoidance.

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Monovision Charging Terminal Docking Method for Unmanned Automatic Charging of Autonomous Mobile Robots (자율이동로봇의 무인 자동 충전을 위한 모노비전 방식의 충전단자 도킹 방법)

  • Keunho Park;Juhwan Choi;Seonhyeong Kim;Dongkil Kang;Haeseong Jo;Joonsoo Bae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.47 no.3
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    • pp.95-103
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    • 2024
  • The diversity of smart EV(electric vehicle)-related industries is increasing due to the growth of battery-based eco-friendly electric vehicle component material technology, and labor-intensive industries such as logistics, manufacturing, food, agriculture, and service have invested in and studied automation for a long time. Accordingly, various types of robots such as autonomous mobile robots and collaborative robots are being utilized for each process to improve industrial engineering such as optimization, productivity management, and work management. The technology that should accompany this unmanned automobile industry is unmanned automatic charging technology, and if autonomous mobile robots are manually charged, the utility of autonomous mobile robots will not be maximized. In this paper, we conducted a study on the technology of unmanned charging of autonomous mobile robots using charging terminal docking and undocking technology using an unmanned charging system composed of hardware such as a monocular camera, multi-joint robot, gripper, and server. In an experiment to evaluate the performance of the system, the average charging terminal recognition rate was 98%, and the average charging terminal recognition speed was 0.0099 seconds. In addition, an experiment was conducted to evaluate the docking and undocking success rate of the charging terminal, and the experimental results showed an average success rate of 99%.