• Title/Summary/Keyword: Laser Vision

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Comparative study on displacement measurement sensors for high-speed railroad bridge

  • Cho, Soojin;Lee, Junhwa;Sim, Sung-Han
    • Smart Structures and Systems
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    • v.21 no.5
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    • pp.637-652
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    • 2018
  • This paper presents a comparative study of displacement measurement using four sensors that are being used in the field: they are a ring gauge, a laser Doppler vibrometer (LDV), a vision-based displacement measurement system (VDMS), and an optoelectronic displacement meter (ODM). The comparative study was carried out on a brand-new high-speed railroad bridge designed to produce displacements within a couple of millimeters under the loading of a high-speed train. The tests were carried out on a single-span steel plate girder bridge two times with different train loadings: KTX and HEMU. The measured displacement is compared as raw and further discussion was made on the measurement noise, peak displacement, and frequency response of four sensors. The comparisonsare summarized to show the pros and cons of the used sensors in measuring displacement at a typical high-speed railroad bridge.

Road Recognition based Extended Kalman Filter with Multi-Camera and LRF (다중카메라와 레이저스캐너를 이용한 확장칼만필터 기반의 노면인식방법)

  • Byun, Jae-Min;Cho, Yong-Suk;Kim, Sung-Hoon
    • The Journal of Korea Robotics Society
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    • v.6 no.2
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    • pp.182-188
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    • 2011
  • This paper describes a method of road tracking by using a vision and laser with extracting road boundary (road lane and curb) for navigation of intelligent transport robot in structured road environments. Road boundary information plays a major role in developing such intelligent robot. For global navigation, we use a global positioning system achieved by means of a global planner and local navigation accomplished with recognizing road lane and curb which is road boundary on the road and estimating the location of lane and curb from the current robot with EKF(Extended Kalman Filter) algorithm in the road assumed that it has prior information. The complete system has been tested on the electronic vehicles which is equipped with cameras, lasers, GPS. Experimental results are presented to demonstrate the effectiveness of the combined laser and vision system by our approach for detecting the curb of road and lane boundary detection.

An Application of Computer Vision and Laser Radar to a Collision Warning System (자동차 추돌경보 시스템 개발을 위한 컴퓨터 비젼과 레이저 레이다의 응용)

  • 이준웅
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.5
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    • pp.258-267
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    • 1999
  • An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

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Automatic Pipeline Welding System using Laser Vision Sensor (시각센서를 이용한 파이프라인 자동용접 시스템)

  • Mun, Hyeong-Sun;Kim, Hyeong-Sik;Kim, Jong-Cheol;Kim, Jong-Jun;Kim, Yong-Baek;Chu, Jeong-Bok;Choe, Seung-Myeon
    • Proceedings of the KWS Conference
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    • 2005.06a
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    • pp.324-325
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    • 2005
  • The primary aim of this paper is to develop an automated welding system capable of adapting to variation in the weld seam center in order to allow higher welding speeds and improved welding quality by using a laser vision sensor. The system is designed to compensate for production problems such as pipe ovality, variation in bevel geometry and track misalignment.

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A Study on the Sensor Fusion Method to Improve Localization of a Mobile Robot (이동로봇의 위치추정 성능개선을 위한 센서융합기법에 관한 연구)

  • Jang, Chul-Woong;Jung, Ki-Ho;Kong, Jung-Shik;Jang, Mun-Suk;Kwon, Oh-Sang;Lee, Eung-Hyuk
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.317-318
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    • 2007
  • One of the important factors of the autonomous mobile robot is to build a map for surround environment and estimate its localization. This paper suggests a sensor fusion method of laser range finder and monocular vision sensor for the simultaneous localization and map building. The robot observes the comer points in the environment as features using the laser range finder, and extracts the SIFT algorithm with the monocular vision sensor. We verify the improved localization performance of the mobile robot from the experiment.

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An Optoelectronical Flank Wear Monitoring Technique of Cutting Tools (절삭공구 플랭크 마모의 광전자학적 측정 시스템 개발)

  • Jeon, Jong-Up;Kim, Seung-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.4 no.3
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    • pp.60-68
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    • 1987
  • An optoelectronical method for in process monitoring of flank wear of cutting tools is presented. The method is based upon real-time vision technology in which the tool is illuminated by a beam of laser and then the image of wear zone is taken by a vidicon camera. The image is converted to a series of digital pixel data and processed through an algorithm specially developed for measurement of the wear land width. Detailed aspects of the prototype measurement system byilt for experiment are described, and test results are discussed. As conclusions, it is proved that the methods are effec- tive especially for-in situ application with a measuring accuracy of 0.01mm.

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