• Proceedings of the KSR Conference
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• 1999.11a
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• pp.574-581
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• 1999

비선형 임계속도를 주행시험대를 이용하여 측정하였으며 비선형 임계속도가 관성에 의한 과도 현상이 아님을 확인하기 위하여 주행속도를 연속 그리고 불연속적으로 감가속 하면서 선형 및 비선형 임계속도를 측정하였다. 또한 차량의 안정성을 간편하게 예측할 때 대차모델만을 사용하던 종래의 방법이 타당한지 확인하였으며 차량의 임계속도와 응답주파수를 예측하기 위하여 산업체에서 사용되던 간편 식들의 정확성을 검토한 결과 다음의 결과를 도출할 수 있었다. (중략)

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.43-55
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• 2012

Bicycle is an environment-friendly transport mode contributing to a more sustainable transportation systems. To innovatively increase the use of bicycle as a significant transport mode, bicycle-friendly roadway environment should be provided. This study proposes a method to evaluate cycling environment based on the analysis of data collected from an specially equipped probe bicycle. The inertial measurement unit(IMU) consisting of a gyro sensor, accelerometer, and a global positioning systems(GPS) receiver was installed on the probe bicycle. Cycling stability index(CSI) and bicycle speed data were used as inputs of the proposed evaluation framework adopting the Fault Tree Analysis, which is a well-known technique for the risk analysis. The outcomes of this study will serve as an intelligent assesment tool for cycling environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.814-819
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• 2010

This paper is presented to study the error minimization of angular velocity for AGV(autonomous ground vehicle). The error minimization of angular velocity is related to localization technique which is the most important technique for autonomous vehicle. Accelerometer, yaw gyro and electronic compass have been used to measure angular velocity. And methods for error minimization of angular velocity have been actively studied through probabilistic methods and sensor fusion for AGVs. However, those sensors still occure accumulated error by mathematical error, system characters of each sensor, and computational cost are increased greatly when several sensor are used to correct accumulated error. Therefore, this paper studies about error minimization of angular velocity that just uses encoder and gyro. To experiment, we use autonomous vehicle which is made by ourselves. In experimental result, we verified that the localization error of proposed method has even less than the localization errors which we just used encoder and gyro respectively.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1942-1943
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• 2011

차량의 무인화에 대한 관심이 증대하면서 자율 주행 문제의 중요성이 부각되고 있다. 현재 전역적인 차량 위치는 GPS에 도움을 받고 있지만 도심 고층 빌딩 밀집 지역에서 GPS 신호가 불안해지는 멀티 패스 페이딩 현상에 대한 대안 및 터널을 통과할 때 GPS 신호가 단절되는 구간에 대한 대안이 필요하다. 본 연구에서는 MEMS 기반의 관성 센서를 제작하고 이를 이용하여 차량의 주행 모드를 자동으로 판별한 뒤 각 상황에 알맞은 칼만 필터를 설계하여 차량 위치를 파악하는 알고리즘을 제안한다. 제안한 알고리즘은 실제 임베디드 시스템에 이식되어 10Hz로 동작함을 확인하였고 GPS 음영 지역에서 3분 이내에는 GPS 오차 범위 내에서 차량 위치를 파악할 수 있음을 실험을 통해 확인하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.139-144
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• 2016

This paper provides an overview of recent trends in sensor fusion technologies for vehicle positioning. The GNSS by itself cannot satisfy precision and reliability required by autonomous driving. We survey sensor fusion techniques that combine the outputs from the GNSS and the inertial navigation sensors such as an odometer and a gyroscope. Moreover, we overview landmark-based positioning that matches landmarks detected by a lidar or a stereo vision to high-precision digital maps.

• Aerospace Engineering and Technology
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• v.9 no.1
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• pp.50-59
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• 2010

In this paper, the alignment and navigation results by INGU(Inertial Navigation and Guidance Unit) onboard software and by Inertial Explorer which is a post-processing software specialized for IMU(Inertial Measurement Unit) are compared for identification of inertial sensor error models and estimation of alignment and navigation errors for KSLV-I INGU. For verification of the IMU error estimated by Kalman Filter of Inertial Explorer, the covariance parameters of inertial sensor error model state are identified by using stochastic error model of inertial sensors estimated by Allan variance and the alignment and navigation test with static condition and the land navigation test with dynamic condition are carried out. The validity of inertial sensor model for KSLV-I INGU is verified by comparison the alignment and navigation results of INGU on-board software and Inertial Explorer.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.495-496
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• 2008

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.6
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• pp.491-499
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• 1999

This paper is on the high perfonnance propulsion IGBT VVVF inverter adopted new technique for railways. To prove the high performance and stabilit~r of traction, running tests are carried out under the simulated condition alike real field. The tests are perfonned on not only a steady states but also a transient states such a as input voltage variation using inertia load equivalent to 160tons train. The vector control technique is a adopted to improve traction for 4 motors. The low switching synchronous PW1\l method based on a space v voltage vector modulation is pro\XlSed as the optimal method for propulsion system railway. The output voltage l is controlled continuously to six step by prolxlsed ovennodu]ation technique without sudden torque variation.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.85-86
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• 2008

로봇은 오도메터리 정보를 이용해 위치추정을 할 수 있다. 그러나 주행하는 동안 발생되는 슬립현상에 의해 오도메터러 정보만으로는 로봇의 정확한 위치추정을 할 수 없다. 정확한 위치추정을 위해서 관성센서를 이용하여 오도메터리 정보를 보정한 위치추정 방법이 있다. 실내 이동로봇에 적용하려면 관성센서는 소형이어야 하는데, 그에 따라 노이즈는 심해지고, 정확성도 낮아지는 문제가 있나. 그래서 현재까지는 이런 문제를 갖고 있는 관성센서를 실내 이동로봇의 위치추정의 정확성을 높이기 위해 비관성센서 또는 카메라 영상을 조합하는 연구들을 하고 있다. 그러나 이러한 연구들은 대부분 관성센서 성능 실험과 시뮬레이션에 결론을 내리고 있어 실제 실험에 따른 정확성을 확인할 수 없다. 또한 최근 영상 SIFT 알고리즘을 적용한 SLAM 연구에서도 나타나는 문제는 이동로봇의 위치추정의 부정확성이다. 따라서 본 논문은 SLAM에서 문제가 되는 위치추정의 부정확성을 최소화하기 위해 자이로와 가속도계를 이용하여 정학한 위치추정을 하고자 한다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1515-1520
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• 2011

Structural analysis and evaluation for the 300ton Goliath Crane were conducted with an FEM tool. The Golliath Crane has a 300 ton hoisting weight, a 110 m span and a 50 m lift. All loads such as the self weight, crane traveling load, trolley traveling load, wind load, and earthquake force, etc., that are indicat in the reference standards, were inputted as various severe conditions affecting the crane. The deformation and equivalent stress (von Mises stress) were evaluated for the crane structures.