• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회A
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• pp.795-800
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• 2008

The paper presents research for the established experiment environment of multi vehicle robot, localization algorithm that is based on vehicle control, and path tracking. The established experiment environment consists of ultrasonic positioning system, vehicle robot, server and wireless module. Ultrasonic positioning system measures positioning for using ultrasonic sensor and generates many errors because of the influence of environment such as a reflection of wall. For a solution of this fact, localization algorithm is proposed to determine a location using vehicle kinematics and selection of a reliable location data. And path tracking algorithm is proposed to apply localization algorithm and LOS, finally, that algorithms are verified via simulation and experimental

• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.188-197
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• 2021

In military operations, an accurate localization system is required to navigate soldiers to their destinations, even in non-GPS environments. The global positioning system is a commonly used localization method, but it is difficult to maintain the robustness of GPS-based localization against jamming of signals. In addition, GPS-based localization cannot provide important terrain information such as obstacles. With the widespread use of embedded sensors, sensor-based pedestrian tracking schemes have become an attractive option. However, because of noisy sensor readings, pedestrian tracking systems using motion sensors have a major drawback in that errors in the estimated displacement accumulate over time. We present a group-based standalone system that creates terrain maps automatically while also locating soldiers in mountainous terrain. The system estimates landmarks using inertial sensors and utilizes split group information to improve the robustness of map construction. The evaluation shows that our system successfully corrected and combined the drift error of the system localization without infrastructure.

• Spatial Information Research
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• 제16권4호
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• pp.455-465
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• 2008

증강현실은 지리정보의 가시화 특히 현장에서의 직접적인 가시화에 있어 매우 높은 잠재력이 있다. 하지만 현재까지의 대부분의 이동형 증강현실 시스템은 사용자의 정확한 위치를 파악하기 위해 GPS 또는 범용적으로 쓰이는 마커를 현장에 붙이는 등의 방식을 사용되었다. 물론 최근의 연구에서 마커없는 환경을 지향하고 있으나 대부분 연구실 또는 제어 환경으로 사용이 제한되어 있다. 특히 실내의 경우 GPS를 사용할 수 없기 때문에 새로운 위치파악기술이 더욱 절실하다. 최근 활발히 활용되고 있는 무선(RF)기반의 실내 위치확인 및 내비게이션 기술 역시 대량의 센서와 인식기를 설치한다는 점에서 그 실용성이 의문이다. 본 연구에서는 단일카메라기반의 SLAM 알고리듬을 이용하여 특수한 하드웨어 없이 카메라만으로 실내 위치 확인 및 내비게이션이 가능한 알고리듬을 제시하였으며, 동시에 확인된 위치에서 증강현실을 통한 정보의 가시화가 가능하도록 구현 하였다. 향후 본 연구가 목표하고 있는 실내외 seamless 연동형 u-GIS 시스템의 기본 기능으로 활용 될 것이다.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.66-73
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• 2016

An Inertial Measurement Unit (IMU)-based Attitude and Heading Reference System (AHRS) can calculate attitude and heading information with long-term accuracy and stability by combining gyro, accelerometer, and magnetic compass signals. Motivated by this characteristic of the AHRS, this paper presents a Motion-Tracking and Localization (MTL) method for a person or walking robot using multi-AHRSs. Five AHRSs are attached to the two calves, two thighs, and waist of a person/walking robot. Joints, links, and coordinate frames are defined on the body. The outputs of the AHRSs are integrated with link data. In addition, a supporting foot is distinguished from a moving foot. With this information, the locations of the joints on the local coordinate frame are calculated. The experimental results show that the presented MTL method can track the motion of and localize a person/walking robot with long-term accuracy in an infra-less environment.

• Journal of information and communication convergence engineering
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• 제17권3호
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• pp.205-212
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• 2019

Motion tracking and localization devices are an important building block of motion tracking systems in a virtual reality (VR) environment. This study is about improving the accuracy of motion and location for enhancing user immersion in experience type VR environment to position tracking technique. In this study, we propose and test a design of such a device. The module data test of the attitude and heading reference system shows that the implementation with the MPU-9250 sensor is successful and adequate to be used with short operation time. We consider various sensor hardware dependencies of VR, and compare various correction methods and filtering methods to lower the motion to photon (MTP) time that user movement is fully reflected on the display using sensor devices. The Kalman filter is used to combine the accelerometer with the gyroscope in the sensing unit.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.767-773
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• 2008

This paper presents a localization system based on the use of electric compass and tracking IR light source. Digital RGB(Red, Green, Blue)signal of digital CMOS Camera is sent to CPLD which converts the color image to binary image at 30 frames per second. CMOS camera has IR filter and UV filter in front of CMOS cell. The filters cut off above 720nm light source. Binary output data of CPLD is sent to DSP that rapidly tracks the IR light source by moving Camera tilt DC motor. At a robot toward north, electric compass signals and IR light source angles which are used for calculating the data of the location system. Because geomagnetic field is linear in local position, this location system is possible. Finally, it is shown that position error is within ${\pm}1.3cm$ in this system.

• International Journal of Control, Automation, and Systems
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• 제5권1호
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• pp.61-69
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• 2007

In this paper, we developed not only a reliable sound localization system including a VAD(Voice Activity Detection) component using three microphones but also a face tracking system using a vision camera. Moreover, we proposed a way to integrate three systems in the human-robot interaction to compensate errors in the localization of a speaker and to reject unnecessary speech or noise signals entering from undesired directions effectively. For the purpose of verifying our system's performances, we installed the proposed audio-visual system in a prototype robot, called IROBAA(Intelligent ROBot for Active Audition), and demonstrated how to integrate the audio-visual system.

• 제어로봇시스템학회논문지
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• 제16권11호
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• pp.1117-1124
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• 2010

This paper presents a foot movement tracking system using ultrasonic sensors and inertial sensors, where the position and velocity of foot are computed using inertial sensors and ultrasonic sensors mounted on a shoe. A foot movement can be estimated using an inertial navigation algorithm only; however, the error tends to increase due to biases of gyroscopes and accelerometers. To reduce the error, a localization system using ultrasonic sensors is additionally used. In the localization system using ultrasonic sensors, the position is continuously calculated in the absolute coordinate. An indirect Kalman filter is used to combine inertial sensors and ultrasonic sensors. Through experiments, it is shown that the proposed system can track a foot movement.

• 한국게임학회 논문지
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• 제12권3호
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• pp.87-96
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• 2012

본 논문에서는 시퀀스 상에서 확장 칼만필터(Extended Kalman Filter) 기반의 SLAM(Simultaneous Localization And Mapping) 시스템의 안정적인 카메라 추적과 재위치(re-localization) 방법이 제안된다. SLAM으로 얻어진 3차원 특징점에 들로네(Delaunay) 삼각화를 적용하여 기준(reference) 평면을 설정하며, 평면상에 존재하는 특징점의 BRISK(Binary Robust Invariant Scalable Keypoints) 기술자(descriptor)를 생성한다. 기존 확장 칼만필터의 오차가 누적되는 경우를 판단하여 기준 평면의 호모그래피로부터 카메라 정보를 해석한다. 또한 카메라가 급격하게 이동해서 특징점 추적이 실패하면, 저장된 강건한 기술자 정보를 매칭하여 카메라의 위치를 다시 추정한다.