• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.249-260
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• 2009

The georeferencing accuracy of the sensory data acquired by an aerial monitoring system heavily depends on the performance of the GPS/IMU mounted on the system. The employment of a high performance but expensive GPS/IMU unit causes to increase the developmental cost of the overall system. In this study, we simulate the images and GPS/IMU data acquired by an UAV-based aerial monitoring system using an inexpensive integrated GPS/IMU of a MEMS type, and perform the image georeferencing by applying the aerial triangulation to the simulated sensory data without any GCP. The image georeferencing results are then analyzed to assess the accuracy of the estimated exterior orientation parameters of the images and ground points coordinates. The analysis indicates that the RMSEs of the exterior orientation parameters and ground point coordinates is significantly decreased by about 90% in comparison with those resulted from the direct georeferencing without the aerial triangulation. From this study, we confirmed the high possibility to develop a low-cost real-time aerial monitoring system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.664-667
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• 1996

This paper presents the error parameter estimation technique for IMU(Inertial Measurement Unit) which is core sensor of INS(Inertial Navigation System) and verifies it via laboratory test. Firstly the error characteristic of gyroscope and accelerometer which is contained in IMU is examined and the error modelling is executed. The error of IMU can be divided into deterministic and random part, and the deterministic error can be divided into static and dynamic part. This paper consider the random part as constant. Secondly the error parameter estimation technique and following procedure for laboratory test is explained. Thirdly according to the test procedure the IMU test for static error is executed using 2-axis rate table and estimation result is presented with discussion about its validity.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.937-943
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• 2016

Vertical velocity is critical in many areas, such as the control of unmanned aerial vehicles, fall detection, and virtual reality. Conventionally, the integration of GPS (Global Positioning System) with an IMU (Inertial Measurement Unit) was popular for the estimation of vertical components. However, GPS cannot work well indoors and, more importantly, has low accuracy in the vertical direction. In order to overcome these issues, IMU-barometer integration has been suggested instead of IMU-GPS integration. This paper proposes a new complementary filter for the estimation of vertical velocity based on IMU-barometer integration. The proposed complementary filter is designed to minimize drift error in the estimated velocity by adding PID control in addition to a zero velocity update technique.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.428-433
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• 1999

The errors of IMU(Inertial Measurement Unit) can be divided into deterministic and random errors. Since the required accuracy of the IMU is very high, the errors must be compensated by using an accurate error mode. In this paper, we present a method to get a more accurate error model in a laboratory test. This was done by considering the setting misalignment in the laboratory test in the IMU error model. We considered here the IMU which consits of DTG(dynamically tuned gyroscope) and pendulum type accelerometer. First, it was shown that the estimation result from the model which does not contain the setting misalignment gives considerable estimation error at the validation test. Second, a new model considering the setting misalignment was derived. Finally, by validation test using the estimation results from new model the validity of it was proved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.8
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• pp.663-673
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• 2013

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on IMU deployed in smart phone, we develop a hybrid positioning estimation framework with a combination of WPS. The developed approaches can strengthen the advantages of independent indoor applicability of IMU. The estimation of IMU is efficiently compensated by radio fingerprint based Wi-Fi Positioning System. We put a focus especially on the hybrid algorithmic framework. Compared on the existing approaches of WPS or IMU, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• The Journal of Korean Medicine
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• v.38 no.1
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• pp.56-71
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• 2017

Objectives: The purpose of this study was to review the article using an IMU(Inertial Measurement Unit) for measuring the cervical range of motion and to evaluate the feasibility of using an IMU for measuring the cervical range of motion. Method: Scopus was used to search for the articles relating to the inclusion criteria. Which is measuring the cervical range of motion using an IMU. A total of 15 articles were selected through discussion. Degree and the reliability of the cervical range of motion and the validity of the data within the articles were extracted. Results: The measurement of the cervical range of motion using an IMU were $92.25^{\circ}$ to $138.2^{\circ}$, $122.4^{\circ}$ to $154.9^{\circ}$, $73.75^{\circ}$ to $93.1^{\circ}$ on the sagittal plane, transverse plane, and coronal plane respectively. 38 of the 43 values showed good reliability. They were larger than 0.75. 5 of the 43 values showed reliability less than 0.75. They were measured by smart phone. 16 of the 21 values showed good validity. The remaining 5 were measured by smart phone. The lower reliability and validity of smart phone were related to the protocol. The IMU can measure the coupling motion and may be used in various situations. Conclusion: The IMU may become a gold standard for measuring the cervical range of motion. The IMU measured not only the cervical range of motion but also the coupling motion. Furthermore, IMU may be used in various situations. Therefore, IMU must be considered a valuable measurement device.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.1-9
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• 2007

3D data are in great demand for pedestrian navigation recently. For pedestrian navigation, we needs to reconstruct 3D model in detail from people's eye. In order to present spatial features in detail for pedestrian navigation, it is indispensable to develop 3D model not only in outdoor environment but also in indoor environment such as underground shopping complex. However, it is very difficult to acquire 3D data efficiently by mobile mapping without GPS. In this research, 3D shape was acquired by Laser scanner, and texture by CCD(Charge Coupled Device) sensor. Continuous changes position and attitude of sensors were measured by IMU(Inertial Measurement Unit). Moreover, IMU was corrected by relative orientation of CCD images without GPS(Global Positioning System). In conclusion, Reliable, quick, and handy method for acquiring 3D data for indoor environment is proposed by a combination of a digital camera and a laser scanner with IMU.

• Journal for History of Mathematics
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• v.26 no.1
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• pp.21-32
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• 2013

The outbreak of the First and the Second World Wars cast great shadow across the Europe including mathematical society. The IMU led by French mathematicians after the First World War ceased to exist because it was used politically. As Europe ran into the Second World War, all the international mathematical activities were ceased. Prominent mathematicians were put into camp by Nazi or moved to the United States of America. After the war, European mathematicians did not have capacity to represent the international mathematical society anymore. This led Stone and other American mathematicians to form the new IMU, which was independent of political ideology. This paper studies the birth process of the new IMU after the War and some major events that happened to ICM in 1950s.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.941-946
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• 2013

In this paper, an enhanced method for attitude determination is proposed for systems using an IMU (Inertial Measurement Unit). In attitude determination with IMU, it is generally assumed that the IMU can be located in the center of gravity on the vehicle. If the IMU is not located in the center of gravity, the accelerometers of the IMU are disturbed from additive accelerations such as centripetal acceleration and tangential acceleration. Additive accelerations are derived from the lever arm which is the distance between the center of gravity and the position of the IMU. The performance of estimation errors can be maintained in system with a non-zero lever arm, if the lever arm is estimated to remove the additive accelerations from the accelerometer's measurements. In this paper, an estimation using Kalman filter is proposed to include the lever arm in the state variables of the state space equation. For the Kalman filter, the process model and the measurement model for attitude determination are made up by using quaternion. In order to evaluate the proposed algorithm, both of the simulations and the experiments are performed for the simplified scenario of motion.