• 제목/요약/키워드: Laser Point Sensor

검색결과 111건 처리시간 0.027초

레이저 비전을 이용한 2단 가변밸브 리프트 모듈의 3D 조립검사에 대한 연구 (Study on the 3D Assembly Inspection of Two-Step Variable Valve Lift Modules Using Laser-Vision Technology)

  • 웬후쿠옹;김도중;이병룡
    • 대한기계학회논문집A
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    • 제41권10호
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    • pp.949-957
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    • 2017
  • 본 논문에서는 2단 가변 밸브 리프트 모듈의 조립불량 검사를 수행하기 위하여, 레이저 비전 기반의 높이 측정 시스템을 개발하였다. 측정방식은 레이저 비전 센서 모듈을 이용하여 삼각 측량법의 원리에 기초하여 3차원 점군집(point cloud) 데이터를 수집하고, 이를 바탕으로 밸브 위치의 높이 차이를 계산하였다. 본 논문에서는 먼저, 측정 시스템의 구성과 제안된 높이 측정 알고리즘을 설명하였다. 그리고, 레이저 비전 기반의 3차원 측정을 위한 실험장치를 구성하였다. 마지막으로, 실험장치의 정확성과 반복성을 검증하기 위해서, 2단 가변 밸브 리프트 모듈에서의 래쉬조정기 및 밸브간의 고저 차이를 측정하는 실험들을 여러 번 수행하였다. 실험 수행결과, 제안된 레이저 비전 기반의 높이 측정 시스템은 2단 가변밸브 리프트 모듈 조립 검사에 대한 높은 정확성, 반복성 및 안정성을 확보하고 있음을 확인할 수 있었다.

특징 점 기반의 ICP 알고리즘을 이용한 2차원 격자지도 보정 (2D Grid Map Compensation Using ICP Algorithm based on Feature Points)

  • 황요섭;이동주;유호윤;이장명
    • 제어로봇시스템학회논문지
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    • 제21권10호
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    • pp.965-971
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    • 2015
  • This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.

도로시설물 관리를 위한 교통안전표지 인식 및 자동위치 취득 방법 연구 (The Road Traffic Sign Recognition and Automatic Positioning for Road Facility Management)

  • 이준석;윤덕근
    • 한국도로학회논문집
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    • 제15권1호
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    • pp.155-161
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    • 2013
  • PURPOSES: This study is to develop a road traffic sign recognition and automatic positioning for road facility management. METHODS: In this study, we installed the GPS, IMU, DMI, camera, laser sensor on the van and surveyed the car position, fore-sight image, point cloud of traffic signs. To insert automatic position of traffic sign, the automatic traffic sign recognition S/W developed and it can log the traffic sign type and approximate position, this study suggests a methodology to transform the laser point-cloud to the map coordinate system with the 3D axis rotation algorithm. RESULTS: Result show that on a clear day, traffic sign recognition ratio is 92.98%, and on cloudy day recognition ratio is 80.58%. To insert exact traffic sign position. This study examined the point difference with the road surveying results. The result RMSE is 0.227m and average is 1.51m which is the GPS positioning error. Including these error we can insert the traffic sign position within 1.51m CONCLUSIONS: As a result of this study, we can automatically survey the traffic sign type, position data of the traffic sign position error and analysis the road safety, speed limit consistency, which can be used in traffic sign DB.

초정밀 이송테이블의 5 자유도 운동오차 측정 (Measurement of Five DOF Motion Errors in the Ultra Precision Feed Tables)

  • 오윤진;박천홍;황주호;이득우
    • 한국정밀공학회지
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    • 제22권11호
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    • pp.135-141
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    • 2005
  • Measurement of five DOF motion errors in a ultra precision feed table was attempted in this study. Yaw and pitch error were measured by using a laser interferometer and roll error was measured by using the reversal method. Linear motion errors in the vertical and horizontal directions were measured by using the sequential two point method. In this case, influence of angular motion errors was compensated by using the previously measured ones by the laser interferometer and the reversal method. The capacitive type sensors and an optical straight edge were used in the reversal method and the sequential two point method. Influence of thermal deformation on sensor jig was investgated and minimized by the periodic measurement according to the variation of room temperature. Deviation of gain between sensors was also compensated using the step response data. 5 DOF motion errors of a hydrostatic table driven by the linear motor werer tested using the measurement method. In the horizontal direction, measuring accuracies for the linear and angular motion were within ${\pm}0.02\;{\mu}m$ and ${\pm}0.04$ arcsec, respectively. In the vertical direction, they were within ${\pm}0.02{\mu}m$ and ${\pm}0.05$ arcsec. From these results, it was found that the introduced measurement method was very effective to measure 5 DOF motion errors of the ultra precision feed tables.

역동역학에 의한 병진운동 탄성 Arm 선단의 위치제어 (The End-Point Position Control of a Translational Flexible Arm by Inverse Dynamics)

  • 이성철;방두열
    • 한국정밀공학회지
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    • 제9권4호
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    • pp.136-146
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    • 1992
  • This paper provides the end-point positioning of a single-link flexible robot arm by inverse dynamics. The system is composed of a flexible arm, the mobile ballscrew stage as an arm base, a DC servomotor as an actuator, and a computer. Actuator voltages required for the model of a flexible arm to follow a given tip trajectory are formulated on the basis of the Bermoullie-Euler beam theory and solved by applying the Laplace transform method, and computed by the numerical inversion method proposed by Weeks. The mobile stage as the arm base is shifted so that the end-point follows the desired trajectories. Then the trajectory of end-point is measured by the laser displacement sensor. Here, two kinds of functions are chosen for the given tip trajectories. One is what is called the bang-bang acceleration profile and the other is the Gaussian velocity profile.

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분포온도 계측을 위한 광파이버 온도센서 시스템에 관한 연구 (The study on the fiber optic sensor for the distributed temperature measurement)

  • 이광진;최성구;노도환
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1746-1749
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    • 1997
  • A distributed optical fiber temperature sensor can continually monitor the measurand at every point along of its fiber length. It is based on OTDR technics which used extreamlly weak backward scattered light called Raman scattering. When the Pulsed high intensity laser light injected into the optical fiber there are several kind of backscattered light such as Rayleigh, Stokes, and anti-Stokes, etc. caused by impurities molecular vibrations. The temperature distribution is derived form the intensity ratio Raman scatted light-Stokes versus anti-Stokes-and the time function between light injection and signal detection. It is shown that the priniciple of distributed sensing, the system desing, and the result of experiments.

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비접촉식 센서를 이용한 초장축 롤러 측정 장치 개발에 관한 연구 (A Study on the Development of Measuring System for Extra Long Roller Using Non-contact Sensor)

  • 김웅;이춘만;이문재;박성진
    • 한국정밀공학회지
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    • 제27권4호
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    • pp.33-39
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    • 2010
  • Manufacturing accuracy of a precision instrument was essential to stability and efficiency of the product. Accordingly, geometrically accuracy management of precision instrument was very becoming the technique in order to design and manufacturing for machine. In this study, Measuring System is developed for extra long roller using non-contact sensor. Futhermore, It's studied by Geometric Tolerance. Exact roundness is obtained to Least Squares method from the reference circle of measured data. Measuring System is analyzed point of measurement and straightness of extra long roller is evaluated by FEM.

지향각이 넓은 저가의 초음파센서를 이용한 이동로봇의 장애물 회피 (Obstacle Avoidance of a Mobile Robot Using Low-Cost Ultrasonic Sensors with Wide Beam Angle)

  • 최윤규;최우수;송재복
    • 제어로봇시스템학회논문지
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    • 제15권11호
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    • pp.1102-1107
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    • 2009
  • An ultrasonic sensor has been widely used as a range sensor for its low cost and capability of detecting some obstacles, such as glasses and black surfaces, which are not well detected by a laser scanner and an IR sensor. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to obstacle avoidance using low-cost anisotropic ultrasonic sensors with wide beam angle. In this paper, obstacles can be detected by the proposed sensor configuration which consists of one transmitter and three receivers. Because even wide obstacles are represented by a point, which corresponds to the intersection of range data from each receiver of the anisotropic sensor, a robot cannot avoid wide obstacles successfully. This paper exploits the probabilistic mapping technique to avoid collision with various types of obstacles. The experimental results show that the proposed method can robustly avoid obstacles in most indoor environments.

센서 융합 시스템을 이용한 심층 컨벌루션 신경망 기반 6자유도 위치 재인식 (A Deep Convolutional Neural Network Based 6-DOF Relocalization with Sensor Fusion System)

  • 조형기;조해민;이성원;김은태
    • 로봇학회논문지
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    • 제14권2호
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    • pp.87-93
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    • 2019
  • This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

Land cover classification using LiDAR intensity data and neural network

  • Minh, Nguyen Quang;Hien, La Phu
    • 한국측량학회지
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    • 제29권4호
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    • pp.429-438
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    • 2011
  • LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.