• 한국정보통신학회논문지
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• 제12권10호
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• pp.1822-1829
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• 2008

항체가 정밀한 항법 정보를 얻기 위해서는 관성 센서의 초기 오차에 대한 보정이 매우 중요하다. 본 논문에서는 레이트 테이블과 고성능 센서를 기준 센서로 사용하여, 저급 MEMS 관성 센서 오차 보정에 따르는 비용과 효율성의 어려움을 극복하는 방법을 제안하였다. 초기 오차 보정 과정에서 기준 센서와 타겟 센서에 같은 동적 입력을 인가한 후 결과를 분석하였다. 실험 결과를 통해 제안된 초기 오차 보정 방법이 실제로 매우 효율적이며 유용함을 확인할 수 있었다.

• 한국항행학회논문지
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• 제23권3호
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• pp.228-236
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• 2019

최근 도심지, 터널, 지하도 등과 같이 위성항법시스템 (GPS; global positioning system) 신호 수신이 어려운 환경에서 안정적으로 정확한 위치 해를 획득하기 위한 다중센서 결합 기법들이 활발하게 연구되고 있다. GPS 음영 지역에서의 위치 정확도를 개선하기 위하여 본 논문에서는 초음파의 전파 특성을 활용하여 동체의 전방 속도를 추정할 수 있는 저가의 초음파 속도계(ultrasonic-speedometer)를 설계하였고, 이를 활용하여 관성항법시스템 (INS; inertial navigation system)과 효율적으로 결합하는 INS/초음파 속도계 결합 항법 시스템을 제안하였다. 제안된 시스템의 성능을 분석하기 위해 차량 탑재 실험을 수행하였다. 실험결과에 의하면 저가의 MEMS IMU (micro electro mechanical systems inertial measurement unit)를 활용하고 GPS 신호가 10초 이상 가용하지 않는 경우에도 제안된 INS/ 초음파 속도계 결합 항법 시스템은 위치 정보 정확도의 열화를 효과적으로 제한할 수 있음을 확인하였다.

• 제어로봇시스템학회논문지
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• 제12권10호
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• pp.982-988
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• 2006

The errors of INS (Inertial Navigation System) are known to grow in time. To compensate the accumulated errors, measurements of external or onboard sensors are extensively utilized to form an integrated navigation system. Recently, INS/GPS integrated navigation systems have become popular since exact position and velocity information can be utilized by low cost GPS receivers. Unfortunately, this configuration cannot be trusted at all times especially when there are intentional or unexpected jammings and interruptions. To aid INS irrespectively of these cases, an INS/Image sensor integrated navigation system configuration is designed only based on the information of image sensor gimble angles. The performance of the INS/Image sensor integrated navigation system is evaluated by Monte Carlo simulation.

• 제어로봇시스템학회논문지
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• 제14권2호
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• pp.133-140
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• 2008

In this paper, a small and effective attitude estimation system for a humanoid robot was developed. Four small inertial sensors were packed and used for inertial measurements(3D accelerometer and three 1D gyroscopes.) An effective 3D pose estimation algorithm for low cost DSP using an extended Kalman filter was developed and evaluated. The 3D pose estimation algorithm has a very simple structure composed by 3 modules of a linear acceleration estimator, an external acceleration detector and an pseudo-accelerometer output estimator. The algorithm also has an effective switching structure based on probability and simple feedback loop for the extended Kalman filter. A special test equipment using linear motor for the testing of the 3D pose sensor was developed and the experimental results showed its very fast convergence to real values and effective responses. Popular DSP of TMS320F2812 was used to calculate robot's 3D attitude and translated acceleration, and the whole system were packed in a small size for humanoids robots. The output of the 3D sensors(pitch, roll, 3D linear acceleration, and 3D angular rate) can be transmitted to a humanoid robot at 200Hz frequency.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.141.6-141
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• 2001

This paper presents the attitude algorithm using Fuzzy technique to mix gyro information with accelerometer. The attitude angle calculated by the low-cost gyros only increases its error with time rapidly because of the integration process of the algorithm and large sensor error. It is known that the accelerometer output includes the attitude information of a vehicle and its information is more effective during low dynamic maneuver. Therefore it is needed to combine two information appropriately for obtaining the attitude information from low-cost MEMS inertial sensors. Because Fuzzy logic is very effective to make a decision of maneuvering state, it is applied to the mixed algorithm. It is shown by experiment ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1001-1006
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• 2003

This paper presents the pedestrian navigation algorithm and the error compensation filter. The pedestrian navigation system (PNS) consists of the MEMS inertial sensors, the fluxgate, and the small-size GPS receiver. PNS calculates the navigational information using the signal patterns of the accelerometers. And the navigational information is completed by integration of the patterns, the fluxgate, and the GPS information. In general, PNS can provide the better solution than the low-cost inertial navigation system.

• Journal of Positioning, Navigation, and Timing
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• 제3권2호
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• pp.53-62
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• 2014

In the guided missile and unmanned vehicle system, the navigation system is one of the most important components. Recently, low-cost effective smart projectiles and guided bomb are being developed using MEMS based navigation system which has high-G, low-cost and small size. In this paper, locally developed MEMS based GPS/INS integrated navigation system will be introduced in comparison with the state of the art of MEMS based navigation system. And technical design and development method is described to satisfy the required performance of GPS receiver, MEMS inertial sensor assembly, navigation computer and software.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.881-885
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• 2008

To calculate the attitude in ARS(Attitude Reference System) using 3 gyros and 3 accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error. Kalman filter is most popular method to integrate those two sensor outputs. In this paper, new Kalman filtering method is proposed for roll and pitch attitude estimation. New states are defined to make linear equation and algorithm for changing Kalman filter parameters is proposed to ignore disturbances of acceleration. This algorithm can be easily applied to low cost ARS.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.632-637
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• 2012

This paper introduces a simple and efficient calibration method for three-axis accelerometers and three-axis gyroscopes using three-axis motion rate table. Usually, the performance of low cost MEMS-based inertial sensors is affected by scale and bias errors significantly. The calibration of these errors is a bothersome problem, but the previous calibration methods cannot propose simple and efficient method to calibrate the errors of three-axis inertial sensors. This paper introduces a new simple and efficient method for the calibration of accelerometer and gyroscope. By using a three-axis motion rate table, this method can calibrate the accelerometer and gyroscope simultaneously and simply. Experimental results confirm the performance of the proposed method.

• 예술인문사회 융합 멀티미디어 논문지
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• 제7권1호
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• pp.177-186
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• 2017

최근 무인자동차가 큰 관심을 받고 있다. 세계 최대 규모의 온라인 쇼핑 서비스업체인 아마존은 드론을 활용한 배송시스템을 개발하고 있다. 이러한 플랫폼의 항법을 위해서는 정확한 자세정보가 필요하다. 본 논문에서는 저가형 관성센서를 활용한 AHRS 구조 설계를 제안하였다. 쿼터니언기반의 운동방정식, 바이어스가 제거된 자이로 측정치, MEMS 가속도계와 지자기 센서를 이용하여 자세를 추정하는 칼만 filter를 설계하였다. MEMS 자이로의 바이어스를 제거하기 위하여 자이로 측정치와 자세 추정치를 이용하는 자이로 바이어스 제거용 칼만 filter를 추가하였다. 구현한 AHRS의 성능을 고가의 상용 Microstrain사의 3DM-GX3-25 AHRS와 비교 실험을 통하여 칼만 filter가 자이로의 바이어스 오차를 0.0001[deg/s]이하로 추정함을 볼 수 있었다. 또한 최종적으로 구해진 자세에서 롤각과 피치각은 0.2, 0.3[deg]이내의 오차를 보여주었다. 요 각은 6[deg] 이하의 오차가 발생하였다.