• Title/Summary/Keyword: Robust calibration

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Integration Algorithm of GPS/SDINS/ST for a Space Navigation (우주항법을 위한 GPS/SDINS/ST 결합 알고리듬)

  • Yi, Chang-Yong;Cho, Kyeum-Rae;Lee, Dae-Woo;Cho, Yun-Cheol
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.24 no.2
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    • pp.1-10
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    • 2016
  • A GPS/SDINS/ST(Star Tracker) integrated sensor algorithm is more robust than the GPS/SDINS and the ST/SDINS systems on exploration of other planets. Most of the advanced studies shown that GPS/SDINS/ST integrated sensor with centralized Kalman filter was more accurate than those 2 integrated systems. The system, however, consist of a single filter, it is vulnerable to defects on failed data. To improve the problem, we work out a study using federated Kalman filter(No-Reset mode) and centralized Kalman filter with adaptive measurement fusion which known as robustness on fault. The simulation results show that the debasing influences are reduced and the computation is enable at least 100Hz. Further researches that the initial calibration in accordance with observability and applying the exploration trajectory are needed.

A Methodology of Dual Gate MOSFET Dosimeter with Compensated Temperature Sensitivity

  • Lho, Young-Hwan
    • Journal of IKEEE
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    • v.15 no.2
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    • pp.143-148
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    • 2011
  • MOS (Metal-Oxide Semconductor) devices among the most sensistive of all semiconductors to radiation, in particular ionizing radiation, showing much change even after a relatively low dose. The necessity of a radiation dosimeter robust enough for the working environment has increased in the fields of aerospace, radio-therapy, atomic power plant facilities, and other places where radiation exists. The power MOSFET (Metal-Oxide Semiconductor Field-Effect Transistor) has been tested for use as a gamma radiation dosimeter by measuring the variation of threshold voltage based on the quantity of dose, and a maximum total dose of 30 krad exposed to a $^{60}Co$ ${\gamma}$-radiation source, which is sensitive to environment parameters such as temperature. The gate oxide structures give the main influence on the changes in the electrical characteristics affected by irradiation. The variation of threshold voltage on the operating temperature has caused errors, and needs calibration. These effects can be overcome by adjusting gate oxide thickness and implanting impurity at the surface of well region in MOSFET.

Robust 2D Texture Map and 3D Model Based 2.5D Object Tracking and Camara Calibration (2D 텍스쳐맵과 3D 모델을 이용한 2.5D 물체 추적 및 카메라 캘리브레이션 알고리즘)

  • Hong, Hyun-Seok;Chung, Myung-Jin
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.1999-2000
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    • 2006
  • 기존 2D 추적기들은 영상에서 특정 평면 영역을 원근 투영하에서 만족할 만한 추적결과를 보여주었다. 하지만 2D 추적기는 2D 영역들로 이루어진 3D물체를 영상에서 추적하는 경우, 물체자신의 회전에 의해 가려지거나 새로 나타나는 영역에 대해 대응하지 못하여 추적에 실패하게 되지만, 3D 정보를 이용한다면 이러한 사라짐과 나타나는 영역을 예측하고 완벽하게 추적할 수 있게 된다. 본 연구에서는 일련의 영상으로부터 3D 모델과 2D 텍스쳐맵을 추출하고, 이를 이용하여 3D 물체의 회전과 평행이동 움직임을 추적한다. 또한 카메라의 줌 파라미터를 모델링하고 추적기 알고리즘에 추가하여, 물체의 3차원 파라미터의 추적과 동시에 카메라 줌 파라미터를 추적하였다.

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A Data Fitting Technique for Rational Function Models Using the LM Optimization Algorithm (LM 최적화 알고리즘을 이용한 유리함수 모델의 데이터 피팅)

  • Park, Jae-Han;Bae, Ji-Hun;Baeg, Moon-Hong
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.8
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    • pp.768-776
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    • 2011
  • This paper considers a data fitting problem for rational function models using the LM (Levenberg-Marquardt) optimization method. Rational function models have various merits on representing a wide range of shapes and modeling complicated structures by polynomials of low degrees in both the numerator and denominator. However, rational functions are nonlinear in the parameter vector, thereby requiring nonlinear optimization methods to solve the fitting problem. In this paper, we propose a data fitting method for rational function models based on the LM algorithm which is renowned as an effective nonlinear optimization technique. Simulations show that the fitting results are robust against the measurement noises and uncertainties. The effectiveness of the proposed method is further demonstrated by the real application to a 3D depth camera calibration problem.

In situ Measurement of Lateral Side-Necking of a Fracture Specimen Using a Stereo Vision and Digital Image Correlation (Stereo Vision과 디지털 화상상관법을 이용한 파괴시험편의 측면 함몰의 현장 측정)

  • Lee Jeong-Hyun;Kang Ki-Ju
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.10
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    • pp.154-161
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    • 2004
  • An experimental method for measuring side-necking deformation near a crack-tip is described. It is based on Stereoscopic Digital Speckle Photography and Digital Image Correlation, and it is simple and robust to mechanical vibration inherent to a hydraulic material test system. The validity and accuracy are evaluated through a calibration fur rigid body translation. A case study has been performed for a CT specimen made of a ductile steel and the three dimensional profiles of the side-necked region are presented as the load increases. Also, the details of the procedure and the surface treatment are discussed.

Measurement of Absorption Coefficient, Radiated and Absorbed Intensity on the Panels of a Vehicle Cabin using a Dual Layer Array with Integrated Position Measurement

  • Gade, S.;Morkholt, J.;Hald, J.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2010.05a
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    • pp.197-200
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    • 2010
  • In some cases it is important to be able to measure not only the total sound intensity on a panel surface in a vehicle cabin, but also the components of that intensity due to sound radiation and due to absorption from the incident field. For example, these intensity components may be needed for calibration of energy flow models of the cabin noise. A robust method based on surface absorption coefficient measurement is presented in his paper.

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Face Recognition using Regional Gabor Wavelet and Neural Networks (Gabor wavelet과 신경망의 영역별 적용을 통한 얼굴 인식)

  • 최용준;이상현;정종률;최병욱
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2020-2023
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    • 2003
  • In this paper, our proposed system uses the regional Gabor wavelet and Neural Network to implement face recognition similar to human face recognition system, because the Gator wavelet expresses visual recognition system of human mathematically and the regional Neural Network is robust to white noise and partial illumination. This system consists of two stages of building database and recognizing face. One is composed by using the supervised learning of Neural Network. At this time, the Neural Network is applied to the upper and the lower part of face images respectively. The Backpropagation algorithm is used to learn Neural Network. Another consists of calibration of slope of face image, measurement of illumination variant using deviation with average face image and similarity comparison using Euclidean distance measure.

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A Study on Intelligent Robot Bin-Picking System with CCD Camera and Laser Sensor (CCD카메라와 레이저 센서를 조합한 지능형 로봇 빈-피킹에 관한 연구)

  • Shin, Chan-Bai;Kim, Jin-Dae;Lee, Jeh-Won
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.231-233
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    • 2007
  • In this paper we present a new visual approach for the robust bin-picking in a two-step concept for a vision driven automatic handling robot. The technology described here is based on two types of sensors: 3D laser scanner and CCD video camera. The geometry and pose(position and orientation) information of bin contents was reconstructed from the camera and laser sensor. these information can be employed to guide the robotic arm. A new thinning algorithm and constrained hough transform method is also explained in this paper. Consequently, the developed bin-picking demonstrate the successful operation with 3D hole object.

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Segmentation-Based Depth Map Adjustment for Improved Grasping Pose Detection (물체 파지점 검출 향상을 위한 분할 기반 깊이 지도 조정)

  • Hyunsoo Shin;Muhammad Raheel Afzal;Sungon Lee
    • The Journal of Korea Robotics Society
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    • v.19 no.1
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    • pp.16-22
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    • 2024
  • Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.

Robust Semi-auto Calibration Method for Various Cameras and Illumination Changes (다양한 카메라와 조명의 변화에 강건한 반자동 카메라 캘리브레이션 방법)

  • Shin, Dong-Won;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.21 no.1
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    • pp.36-42
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    • 2016
  • Recently, many 3D contents have been produced through the multiview camera system. In this system, since a difference of the viewpoint between color and depth cameras is inevitable, the camera parameter plays the important role to adjust the viewpoint as a preprocessing step. The conventional camera calibration method is inconvenient to users since we need to choose pattern features manually after capturing a planar chessboard with various poses. Therefore, we propose a semi-auto camera calibration method using a circular sampling and an homography estimation. Firstly, The proposed method extracts the candidates of the pattern features from the images by FAST corner detector. Next, we reduce the amount of the candidates by the circular sampling and obtain the complete point cloud by the homography estimation. Lastly, we compute the accurate position having the sub-pixel accuracy of the pattern features by the approximation of the hyper parabola surface. We investigated which factor affects the result of the pattern feature detection at each step. Compared to the conventional method, we found the proposed method released the inconvenience of the manual operation but maintained the accuracy of the camera parameters.