• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.21-29
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• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.774-779
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• 2004

This paper describes the fault detection and failsafe logic to be used in the Electronic Stability Program (ESP). The Aim of this paper is prevention of erroneous control in the ESP. This paper introduces the fault detection logic and evaluation of residual signals. Failsafe logic consist of four redundant sub-models and they can be used for the detection of faults in each sensor (yaw rate, lateral acceleration, steering wheel angle). We presents two mathematical residual generation method ; one is the method by the average value, and the other is the method by the minimum value of the each residual. We verify a failsafe logic using vehicle test results, also we compare vehicle model based simulation results with test vehicle results.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.2
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• pp.137-144
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• 2015

In this paper, we present an inertial sensor-based gait analysis system to measure and analyze lower-limb movements. We developed an integral AHRS(Attitude Heading Reference System) using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE(Root Mean Square Error) of 1.08 and 1.72 degree in yaw and pitch angle. In order to evaluate the performance of our the gait analysis system, we compared the joint angle for the hip, knee and ankle with those provided by Vicon system. The result shows that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limb or gait analysis during the post-stroke recovery.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.3
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• pp.138-144
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• 2013

New experimental devices and methods to measure shaft forces of ships are proposed in this paper. The strain gauge type six-component load cell was newly designed and installed to the end of the propeller shaft. The signals generated from the sensor in the propeller rotating are transferred to the new data amplifying and processing board on the shaft and the data is transmitted to the self-made wireless receiver. To find out the characteristics of shaft forces during port and starboard turning motions in sea trial, oblique and combined yaw maneuvering tests at straight, transient, maximum yaw rate, steady conditions were performed with the model ship installed the shaft forces measuring device using circular motion tester of Samsung Ship Model Basin. Characteristics of the measured shaft forces in model tests show quantitatively good agreement with the computed values obtained by the CFD programs using the measured wake data in oblique towing conditions. In the near future, It is hoped that the estimated shaft forces for a ship from this experimental method could be validated through comparison with directly measured values of a ship.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.261-270
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• 2017

Bad sitting postures are known to cause for a variety of diseases or physical deformation. However, it is not easy to fit right sitting posture for long periods of time. Therefore, methods of distinguishing and inducing good sitting posture have been constantly proposed. Proposed methods were image processing, using pressure sensor attached to the chair, and using the IMU (Internal Measurement Unit). The method of using IMU has advantages of simple hardware configuration and free of various constraints in measurement. In this paper, we researched on distinguishing sitting postures with a small amount of data using just one IMU. Feature extraction method was used to find data which contribution is the least for classification. Machine learning algorithms were used to find the best position to classify and we found best machine learning algorithm. Used feature extraction method was PCA(Principal Component Analysis). Used Machine learning models were five : SVM(Support Vector Machine), KNN(K Nearest Neighbor), K-means (K-means Algorithm) GMM (Gaussian Mixture Model), and HMM (Hidden Marcov Model). As a result of research, back neck is suitable position for classification because classification rate of it was highest in every model. It was confirmed that Yaw data which is one of the IMU data has the smallest contribution to classification rate using PCA and there was no changes in classification rate after removal it. SVM, KNN are suitable for classification because their classification rate are higher than the others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.1 no.2
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• pp.209-220
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• 1997

DBS offers actual services to mass-media and communication system of very broad region in information society. Especially, the DBS is the only system to access TV broadcasting service on a sailing ship. But the ship's DBS receiver is required a complex antenna tracking system because ships are under complex moving such as pitch, roll, and yaw etc. This study is motivated to develop a tracking antenna system to receive the koreasat on small silo ship. Therefore, this system is researched to small size, light weight, simple operation, and low cost of the product. The mount structure have been a compact size and easy operation to the Az/El 2-axis type which is operated by step motor. And it is very useful on a ship in the around sea of korean peninsula. The antenna has a plate type of micro-strip array, and is a domestic production. The vibration sensor is selected to gyro sensor of ultra-sonic rate type for ship's moving control. Tracking method is used the step-tracking algorithm, and the ship's moving compensation is adapted to the closed loop control method by ship's moving detection of gyro sensor. Tracking test is operated by the ship's moving simulator, we examined the actual receiving state on sailing shipboard in the near sea of korean peninsular.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.173-180
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• 1996

This paper briefly describes the KITSAT-1 and KITSAT-2 spacecrafts and presents the functions, calibration procedures and in-orbit results of the KITSAT-2 analog sun sensors have been flown as an experimental payload for the future mission. We have two constraints in their design: small size and very low power consumption due to the tight mass and power budget of the spacecraft. Two one-dimensional analog sun sensors are mounted on the top facet of the KITSAT-2 spaceraft. Each has $\pm$60 degrees of view angle and they cover 210 degree field of view in total as the 30 degree view angles are overlapped. Only the relative sun angle around the Z-axis (yaw-axis) and the spin rate of the spacecraft can be achieved as the one dimensional sun sensors are used and they are aligned with the Z-axis. The calibration formulae are obtained using the fifth order line fitting algorithm for each sun sensor on the ground and they are applied to the obtained in-orbit data. ASS-1 with silicon solar cells has maximum error of 1.5 degree and ASS-2 with silicon photocells manufactured at KAIST has maximum error of 0.5 degree except near 0 degree of sun ray incident anagle where random reflection of incident sun ray is maximum in orbit. The results are presented in chapter 4. The performance of each sun sensor and the possible mounting errors are stated in chapter 5.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.1
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• pp.14-19
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• 2012

On-line and real-time information of the longitudinal velocity is the essential factor for the Advanced Vehicle Control Systems such as ABS(Anti-lock Brake System), TCS(Traction Control System), ESC (Electronic Stability Control) etc. However, the longitudinal velocity cannot be easily measured or calculated during braking maneuvering. A new algorithm is presented for the estimation of the longitudinal velocity with the measurements of the vehicle longitudinal/lateral acceleration, steering angle and yaw rate. The algorithm is designed utilizing the Extended Kalman Filter based on the 3 degree of freedom vehicle model. In order to compensate for the biased sensor signal on the inclined road, the inclined angle is also estimated. The performance of the proposed estimation algorithm is evaluated in field tests.