• 제어로봇시스템학회논문지
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• 제17권2호
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• pp.183-189
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• 2011

An alignment algorithm for strapdown inertial navigation systems is proposed, in which the psi angle error model is utilized. The proposed alignment algorithm is derived from the Psi angle error model which has been widely used in real-time navigation systems. The equation for expecting steady state alignment error is also derived. The proposed algorithm was verified through real-time experiments. Experimental results show that the proposed algorithm can be used in the inertial navigation system and GNSS/INS integrated navigation system to get an initial attitude of the vehicle.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 추계학술대회 논문집
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• pp.47-52
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• 2005

This paper describes how a relatively compensate the error of position by using low cost Inertial Measurement Unit (IMU) has been evaluated and compared with the well established method based on a Kalman Filter(KF). The compensation algorithm by using IMU have been applied to the problem of integrating information from an Inertial Navigation System (INS). The KF is to estimate and compensate the errors of an INS by using the integrated INS velocity and position. We verify the proposed algorithm by simulation results.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.613-620
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• 2013

A new remote control algorithm for a mobile robot is proposed, where a remote controller consists of a camera and inertial sensors. Initially the relative position and orientation of a robot is estimated by capturing four circle landmarks on the plate of the robot. When the remote controller moves to point to the destination, the camera pointing trajectory is estimated using an inertial navigation algorithm. The destination is transmitted wirelessly to the robot and then the robot is controlled to move to the destination. A quick movement of the remote controller is possible since the destination is estimated using inertial sensors. Also unlike the vision only control, the robot can be out of camera's range of view.

• 한국정밀공학회지
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• 제15권1호
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• pp.101-108
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• 1998

This paper concerns the navigation algorithm of motion reference unit (MRU) for autonomous underwater vehicle (AUV) We apply the strapdown navigation system using middle level inertial sensors. But, because the MRU consists of inertial sensors, the values of AUV motion calculated by navigation computer are increased by drift property of inertial sensors. Therefore, we propose the attitude algorithm using switching method according to the motion of AUV From this algorithm, the drift terms are eliminated effectively for roll and pitch. But, another device is required for yaw angle.

• 한국항공우주학회지
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• 제35권7호
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• pp.627-632
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• 2007

근래에 들어 관성항법 알고리즘의 성능 향상에 이체 쿼터니언(dual quaternion)이 새로이 적용되기 시작하였다. 이체 쿼터니언은 선형 미분방정식으로 계산하는 쿼터니언을 회전운동과 병진운동을 동시에 취급하는 이체수(dual number) 체계로 확장한 형태이다. 본 논문에서는 기존의 관성항법 알고리즘과 근래에 소개된 이체 쿼터니언 알고리즘을 분석하여 두 알고리즘의 장점을 결합한 새로운 형태의 정밀 이체 쿼터니언 알고리즘을 제안하였다. 제안된 혼합 알고리즘은 기존 알고리즘과 유사한 수치적 연산량으로 이체 쿼터니언의 알고리즘과 유사한 정확도 향상을 얻을 수 있다. 시뮬레이션을 통하여 제안된 혼합 알고리즘의 연산량 및 정확도를 평가하였다.

• 전기학회논문지
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• 제68권1호
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• pp.189-198
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• 2019

In recent years, visual-inertial odometry(VIO) algorithms have been extensively studied for the indoor/urban environments because it is more robust to dynamic scenes and environment changes. In this paper, we propose loosely coupled(LC) VIO algorithm that utilizes the velocity vectors from both visual odometry(VO) and inertial measurement unit(IMU) as a filter measurement of Extended Kalman filter. Our approach improves the estimation performance of a filter without adding extra sensors while maintaining simple integration framework, which treats VO as a black box. For the VO algorithm, we employed a fundamental part of the ORB-SLAM, which uses ORB features. We performed an outdoor experiment using an RGB-D camera to evaluate the accuracy of the presented algorithm. Also, we evaluated our algorithm with the public dataset to compare with other visual navigation systems.

• 전기학회논문지
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• 제58권5호
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• pp.1010-1018
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• 2009

An inertial navigation system for pedestrian position tracking is proposed, where the position is computed using inertial sensors mounted on shoes. Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it needs to reset errors frequently. During normal walking, there is an almost periodic zero velocity instance when a foot touches the floor. Using this fact, estimation errors are reduced and this method is called the zero velocity updating algorithm. When implementing this zero velocity updating algorithm, it is important to know when is the zero velocity interval. The gait states are modeled as a Markov process and each state is estimated using the hidden Markov model smoother. With this gait estimation, the zero or nearly zero velocity interval is more accurately estimated, which helps to reduce the position estimation error.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.672-675
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• 1996

This paper presents algorithm including Kalman filter for transfer alignment of velocity and quaternion matching method, when master inertial navigation system is a gimbled type and slave inertial navigation system is a strapdown type on a cruising ship which is naturally in motion of horizontal axis attitude. And relative attitudes are considered on a measurement equation for quaternion matching between master INS and slave INS.

• 한국항행학회논문지
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• 제23권3호
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• pp.245-250
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• 2019

관성항법장치는 시간 경과에 따라 관성센서 및 초기정렬 오차로 인해 항법 오차가 발생한다. 이를 보상하기 위한 방법으로 위성항법시스템 및 속도계 등을 이용하여 보정항법을 수행한다. 수중 환경에서는 GNSS 신호가 통하지 않기 때문에, 수중운동체에 탑재한 관성항법장치는 주로 속도계 보조센서를 이용하여 보정항법을 수행한다. 속도계 보조센서는 DVL, EM-Log, RPM이 있으며, 시스템 환경에 따라서 센서 종류가 적용된다. 본 논문은 고속 및 심해 환경에서 운용되는 관성항법장치의 RPM 속도보정항법을 설계하였다. 또한 직진 방향의 성분을 갖는 RPM 속도계의 한계를 보완하며, 해조류 속도 오차를 보상하는 알고리즘을 제안하였다. 제안한 알고리즘은 몬테카를로 시뮬레이션 결과를 통해 성능을 입증하였다.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.291-297
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• 2000

This paper presents an attitude determination algorithm for the local level strapdown inertial navigation where the body the earth and the transport rate can be calculated separately using a DCM computation scheme, Also presented is a velocity determination algorithm taking into account the attitude variation caused by he change of the navigation frame. The proposed algorithm are implemented using three samples of the velocity and the angle within the integration interval.