• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.54-61
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• 2012

In this paper, the pose estimation method for the satellite GTB (Ground Test Bed) using vision/MEMS IMU (Inertial Measurement Unit) integrated system is presented. The GTB for verifying a satellite system on the ground is similar to the mobile robot having thrusters and a reaction wheel as actuators and floating on the floor by compressed air. The EKF (Extended Kalman Filter) is also used for fusion of MEMS IMU and vision system that consists of a single camera and infrared LEDs that is ceiling landmarks. The fusion filter generally utilizes the position of feature points from the image as measurement. However, this method can cause position error due to the bias of MEMS IMU when the camera image is not obtained if the bias is not properly estimated through the filter. Therefore, it is proposed that the fusion method which uses the position of feature points and the velocity of the camera determined from optical flow of feature points. It is verified by experiments that the performance of the proposed method is robust to the bias of IMU compared to the method that uses only the position of feature points.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.74.1-74.1
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• 2016

미국 텍사스 주 맥도날드 천문대에 위치한 2.1m 망원경에 부착된 SQUEAN (SED Camera for QUasars in EArly uNiverse)은 2010년부터 운용되고 있는 CQUEAN을 바탕으로 개발된 적외선 영역 광학기기이다. 20개의 필터 장착이 가능한 필터 휠 제어 시스템을 가지고 있는 SQUEAN 시스템은 SMOP (SQUEAN Main Observation software package), KFC82 (KHU Filter wheel Control software package for McDonald 82 inch Telescope), KAP82 (KHU Auto-guiding software Package for McDonald 82 inch Telescope) 등으로 구성되어 있다. 그러나 대형 필터 휠을 제어하는 모터의 토크부족과 감속기의 백래시(Backlash)의 영향으로 오프셋의 오차가 커서 초기위치의 재설정 없이 하룻밤 이상 관측을 지속하는데 어려움이 있었다. 토크가 크고 인코더가 장착된 모터 교체와 제어 프로그램 등을 변경하고, 백래시의 영향을 최소화할 수 있도록 소프트웨어로 보정하였다. 또한, SMOP로부터 네트워크 통신을 통해 초기화용 필터 마스크(Initial Filter Mask:IFM)를 제작하여 돔 플랫 이미지에서 정확한 필터의 위치를 측정하는 기능을 도입하였다. 이 발표에서는, 개선된 하드웨어 및 소프트웨어의 내용과 테스트한 결과에 대해 보여준다.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.51.4-52
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• 2015

From 2010 to 2014, CQUEAN (Camera for QUasars in EArly uNiverse) has been operated for the observation at the 82 inch Otto Struve Telescope of the McDonald Observatory, US. This camera is optimized at wavelength range of 0.7 - 1.1 um with seven (g', r', I', z', Y, Iz and Is) broad-band filters for the survey of high redshift (z > 5) quasars in the early universe. We are upgrading this system to identify more details of SED (Spectral Energy Distribution) of quasar candidates and other astronomical sources. The SQUEAN is comprised of a focal reducer, a CCD camera, a new filter wheel, new auto guiding system and new control software. The new filter wheel consists of interchangeable cartridges for various wavelength and size of filters. 50 nm medium bandwidth filters from 600 - 1050 nm, seven SDSS (Sloan Digital Sky Survey) filters and Johnson-Cousin BVRI filters are installed for now. We also have a plan to use narrow band interference filters to classify high redshift quasars or to obtain SEDs of interesting astronomical sources in details more efficiently. We also developed KAP82 (Kyung Hee University Auto guiding Package for 82 inch telescope) for auto guiding software. CQUEAN and SQUEAN have been developed by CEOU (Center for the Exploration of the Origin of the Universe).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.49-56
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• 2007

In this paper, the development of excitation light source is proposed for excitation light of the photodynamic therapy of cancer. Since the selection of the wavelength band of excitation light has an interrelation with fluorescence generation according to the selection of a photosensitizer. This study aims at designing and evaluating light source that can stably generate light with various kinds of wavelengths in order to make possible photodynamic diagnosis using a photosensitizer and diagnosis using auto-fluorescence. The light source device was a Xenon lamp and filter wheel, composed of an optical output control through iris and filters with several wavelength bands. It also makes the inducement of auto-fluorescence possible because it is designed to generate a wavelength band of 380-420nm, 430-480nm, 480-560nm. The transmission part of the light source was developed to enhance the efficiency of light transmission. To evaluate this light source device by KFDA#s technical reference, the characteristics of the light output and wavelength band were found.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.11-16
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• 2014

In this paper, the two-wheels robot using a predictive controller to maintain the balance of the posture control in real time have been examined. A reaction wheel pendulum control method is adopted to maintain the balance while the bicycle robot is driving. The objective of this research was to design and implement a self-balancing algorithm using the dsPIC30F4013 embedded processor. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this study, the disturbance of the posture for the asymmetrical propose to overcome the predictive controller which was a problem in the control of a remote system by introducing the two wheels of the robot controller and the linear prediction of the system controller combines the simulation was performed. Also, the robust characteristic for realizing the goal of designing a loop filter too robust controller is designed so that satisfactory stability of the control system to improve stability of the system to minimize degradation of performance was confirmed.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.597-599
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• 2005

To make the autonomous mobile robot move in the unknown space, we have to know the information of current location of the robot. So far, the location information that was obtained using Encoder always includes Dead Reckoning Error, which is accumulated continuously and gets bigger as the distance of movement increases. In this paper, we analyse the effect of the size of the two wheels of the mobile robot and the wheel track of them among the factors of Dead Reckoning Error. And after this, we compensate this Dead Reckoning Error by Kalman filter using Gyro Sensors. To accomplish this, we develop the controller to analyse the error components of Gyro Sensor and to minimize the error values. We employ the numerical approach to analyse the error components by linearizing them because each error component is nonlinear. And we compare the improved result through simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.594-600
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• 2012

Accurate localization is very important to stable navigation of a mobile robot. This paper deals with local localization of a mobile robot especially for outdoor environments. The GPS information is the easiest way to obtain the outdoor position information. However, the GPS accuracy can be severely affected by environmental conditions. To deal with this problem, the GPS and wheel odometry can be combined using an EKF (Extended Kalman Filter). However, this is not enough for safe navigation of a mobile robot in outdoor environments. This paper proposes a novel method using lane features from the road image. The pose data of a mobile robot can be corrected by analyzing the detected lane features. This can improve the accuracy of the localization process substantially.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.3
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• pp.330-338
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• 2011

Odometry is the critical factor to estimate the location of the robot. In the mobile robot with wheels, odometry can be performed using the information from the encoder. However, the information of location in the encoder is inaccurate because of the errors caused by the wheel's alignment or slip. In general, visual odometer has been used to compensate for the kinetic errors of robot. In case of using the visual odometry under some robot system, the kinetic analysis is required for compensation of errors, which means that the conventional visual odometry cannot be easily applied to the implementation of the other type of the robot system. In this paper, the novel visual odometry, which employs only the single camera toward the ground, is proposed. The camera is mounted at the center of the bottom of the mobile robot. Feature points of the ground image are extracted by using median filter and color contrast filter. In addition, the linear and angular vectors of the mobile robot are calculated with feature points matching, and the visual odometry is performed by using these linear and angular vectors. The proposed odometry is verified through the experimental results of driving tests using the encoder and the new visual odometry.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.706-711
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• 2008

This paper is presented an accurate localization scheme for mobile robots based on the fusion of ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve enough accuracy less than 100 mm. The INS consist of a yaw gyro, two wheel-encoders. And the U-SAT consist of four transmitters, a receiver. Besides the localization method in this paper fuse these in an extended Kalman filter. The performance of the localization is verified by simulation and two actual data(straight, curve) gathered from about 0.5 m/s of driving actual driving data. localization methods used are general sensor fusion and sensor fusion through Kalman filter using data from INS. Through the simulation and actual data studies, the experiment show the effectiveness of the proposed method for autonomous mobile robots.