• Title/Summary/Keyword: Angular velocity sensor

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Performance Improvement of a Pedestrian Dead Reckoning System using a Low Cost IMU (저가형 관성센서를 이용한 보행자 관성항법 시스템의 성능 향상)

  • Kim, Yun-Ki;Park, Jae-Hyun;Kwak, Hwy-Kuen;Park, Sang-Hoon;Lee, ChoonWoo;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.6
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    • pp.569-575
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    • 2013
  • This paper proposes a method for PDR (Pedestrian Dead-Reckoning) using a low cost IMU. Generally, GPS has been widely used for localization of pedestrians. However, GPS is disabled in the indoor environment such as in buildings. To solve this problem, this research suggests the PDR scheme with an IMU attached to the pedestrian's waist. However, despite the fact many methods have been proposed to estimate the pedestrian's position, but their results are not sufficient. One of the most important factors to improve performance is, a new calibration method that has been proposed to obtain the reliable sensor data. In addition to this calibration, the PDR method is also proposed to detect steps, where estimation schemes of step length, attitude, and heading angles are developed. Peak and zero crossings are detected to count the steps from 3-axis acceleration values. For the estimation of step length, a nonlinear step model is adopted to take advantage of using one parameter. Complementary filter and zero angular velocity are utilized to estimate the attitude of the IMU module and to minimize the heading angle drift. To verify the effectiveness of this scheme, a real-time system is implemented and demonstrated. Experimental results show an accuracy of below 1% and below 3% in distance and position errors, respectively, which can be achievable using a high cost IMU.

Tutorial on the Principle of Borehole Deviation Survey - An Application of the Coordinate Transforms (시추공 공곡 측정의 원리 - 좌표계 변환의 응용)

  • Song, Yoonho
    • Geophysics and Geophysical Exploration
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    • v.23 no.4
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    • pp.243-252
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    • 2020
  • To share an understanding of trajectory measurement in surveys using borehole, this tutorial summarizes the relevant mathematical principles of the borehole deviation survey based on coordinate transform. For uncased or open holes, calculations of the azimuth-deviation-tool face rotation using three-component accelerometer and magnetometer measurements are summarized. For the steel-cased holes, calculations are based on the time-derivative formula of the coordinate transform matrix; yaw-pitch-roll angles through time are mathematically determined by integrating the threecomponent angular velocity measurements from the gyroscope while also removing the Earth's rotation effect. Sensor and data fusion to increase the accuracy of borehole deviation survey is explained with an example of the method. These principles of borehole deviation surveys can be adapted for attitude estimation in air-borne surveys or for positioning in tunnels where global positioning system (GPS) signals cannot be accessed. Information on the optimization filter that must be incorporated in sensor fusion is introduced to help future research.

Head motion during cone-beam computed tomography: Analysis of frequency and influence on image quality

  • Moratin, Julius;Berger, Moritz;Ruckschloss, Thomas;Metzger, Karl;Berger, Hannah;Gottsauner, Maximilian;Engel, Michael;Hoffmann, Jurgen;Freudlsperger, Christian;Ristow, Oliver
    • Imaging Science in Dentistry
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    • v.50 no.3
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    • pp.227-236
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    • 2020
  • Purpose: Image artifacts caused by patient motion cause problems in cone-beam computed tomography (CBCT) because they lead to distortion of the 3-dimensional reconstruction. This prospective study was performed to quantify patient movement during CBCT acquisition and its influence on image quality. Materials and Methods: In total, 412 patients receiving CBCT imaging were equipped with a wireless head sensor system that detected inertial, gyroscopic, and magnetometric movements with 6 dimensions of freedom. The type and amplitude of movements during CBCT acquisition were evaluated and image quality was rated in 7 different anatomical regions of interest. For continuous variables, significance was calculated using the Student t-test. A linear regression model was applied to identify associations of the type and extent of motion with image quality scores. Kappa statistics were used to assess intra- and inter-rater agreement. Chi-square testing was used to analyze the impact of age and sex on head movement. Results: All CBCT images were acquired in a 10-month period. In 24% of the investigations, movement was recorded (acceleration: >0.10 [m/s2]; angular velocity: >0.018 [°/s]). In all examined regions of interest, head motion during CBCT acquisition resulted in significant impairment of image quality (P<0.001). Movement in the horizontal and vertical axes was most relevant for image quality (R2>0.7). Conclusion: Relevant head motions during CBCT imaging were frequently detected, leading to image quality loss and potentially impairing diagnosis and therapy planning. The presented data illustrate the need for digital correction algorithms and hardware to minimize motion artefacts in CBCT imaging.