• 제어로봇시스템학회논문지
• /
• 제19권11호
• /
• pp.1053-1059
• /
• 2013

Heading bias effects in PNS using IMUs attached to shoes are analyzed in this paper. The navigation algorithms of a single foot PNS where one IMU is attached to a foot and dual foot PNSs where two IMUs are attached to each foot are derived. Two navigation algorithms are proposed for the dual foot PNS: 1) the positions from the independent right and left foot PNSs are averaged to provide the final position, 2) the right and left foot PNSs are correlated and it provides positions of each foot. Furthermore, it is proven that two methods are equal. Using the derived navigation algorithms the effect of heading bias caused by a misalignment of the moving direction and IMU is analyzed. The analysis explains the position error of a single foot PNS is diverged while the heading bias is effectively compensated in dual foot PNSs because of the symmetry of heading biases. The experimental results confirm the analysis.

• 제어로봇시스템학회논문지
• /
• 제22권6호
• /
• pp.470-476
• /
• 2016

This paper proposes a practical algorithm for the reduction of measurement errors due to drift in a micro-electromechanical system (MEMS) gyros that are used for a mobile robot. Any drift in a MEMS gyro will cause an unbounded growth of errors in the estimation of heading, which makes it nearly useless in applications that require high accuracy over a long operating time. In proposed method, maneuvers of a cleaning robot are observed through encoders' measurement process and a decision to correct bias drift will be made if necessary. The method used in this paper is called the "heading estimation filter". To evaluate the accuracy of the proposed method, a comparison was made between the estimation of the heading of the cleaning robot and one from a motion capture system.

• 로봇학회논문지
• /
• 제6권4호
• /
• pp.334-343
• /
• 2011

This paper presents a new approach for mobile robot heading detection using MEMS Gyro north finding method in the indoor environment. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, a single axis MEMS gyroscope to sense the angle between the robot heading direction and the north is used. To reach enough estimation accuracy and reduce detection time, the least square method (LSM) for the signal fitting and parameter estimation is applied. Through a turn-table, we setup a carouseling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.

• Journal of Hydrospace Technology
• /
• 제1권1호
• /
• pp.75-88
• /
• 1995

Auto-Pilot System uses heading angle information via the position sensor and the rudder device to control the ship's direction. Most of the control logics are composed of the state estimation and control algorithms assuming that the measurement device and the actuator have no fault except the measurement noise. But such asumptions could bring the danger in real situation. For example, if the heading angle measuring device is out of order the control action based on those false position information could bring serious safety problem. In this study, the control system including improved method for processing the position information is applied to the Auto-Pilot System. To show the difference between general state estimator and F.D.F., BJDFs for the sensor and the actuator failure detection are designed and the performance are tested. And it is shown that bias error in sensor could be detected by state-augmented estimator. So the residual confined in the 2-dimension in the presence of the sensor failure could be unidirectional in output space and bias sensor error is much easier to be detected.

• 한국군사과학기술학회지
• /
• 제12권3호
• /
• pp.368-377
• /
• 2009

In this paper we study the gyro bias calibration method of SDINS(Strap-Down Inertial Navigation System). Generally, SDINS's calibration is performed in 2-axis(or 3-axis) rate table with chamber for varying ambient temperature. We assumed that the majority of calibration-parameter except for gyro bias is knowned. During gyrobias calibration procedure, it can be induced some disturbances(accelerometer's short-term error induced rate table rotation and anti-vibration mount's rotation). In these cases, old gyro-bias calibration methods(using velocity error or attitude error) have an error, because these disturbances are not detectable at the same time. So that, we propose a new gyro-bias calibration method(heading error minimizing using equivalent linear transformation) that can detect anti-vibration mount's rotation. And we confirm efficiency of the new gyro-bias calibration method by simulation.

• 한국해양공학회지
• /
• 제31권2호
• /
• pp.177-182
• /
• 2017

This paper describes an unscented Kalman filter approach to estimate the bias in magnetic field measurements. A microelectromechanical systems attitude heading reference system (MEMS AHRS) was used to measure the magnetic field, together with the acceleration and angular rate. A magnetic field is usually used for yaw detection, while the acceleration serves to detect the roll and pitch. Magnetic field measurements are vulnerable to distortion due to hard-iron effect and soft-iron effect. The bias in the measurement accounts for the hard-iron effect, and this paper focuses on an approach to estimate this bias. The proposed method is compared with other methods through experiments that implement the navigation of an underwater robot using an AHRS and Doppler velocity log. The results verify that the compensation of the bias by the proposed method improves the navigation performance more than or comparable to the compensation by other methods.

• 한국해양공학회지
• /
• 제31권1호
• /
• pp.28-35
• /
• 2017

This paper introduces a GPS-aided dead reckoning algorithm that asymptotically estimates the heading bias error of a magnetic compass based on geodetic north, improves the position error accumulated by dead reckoning, and helps the estimated position of an AUV to represent a position in the NED coordinate system, by receiving GPS position information when surfaced. Based on the results of a simulation, the locational error was bounded with a modest distance, after estimating the AUV position and heading bias error of the magnetic compass when surfaced. In other words, it was verified that proposed algorithm improves the position error in the NED coordinate system.

• 대한조선학회논문집
• /
• 제30권4호
• /
• pp.8-16
• /
• 1993

자동항법장치(Auto-Pilot System)에 의한 방향제어는 방위계측센서에 의해 계측된 위치 정보와 선미조타장치를 바탕으로 이루어진다. 대부분의 제어시스템들은 센서 잡음을 제외하고는 고장이 없는 계측장비와 고장없는 actuator를 가정하여 상태추정 빛 제어알고리듬을 구현하고 있다. 그러나 실제 상황에서는 이러한 가정이 위험한 경우가 많다. 즉, 방위 계측장비가 고장인 난 경우, 이 잘못된 위치 정보에 기초한 제어기능은 심각한 안전상의 문제까지도 야기시킬 수 있는 것이다. 본 연구에서는 개선된 위치정보처리 방법을 포함시킨 제어시스템을 Auto-Pilot 시스템에 적용하여 보았다. 그 방법으로 센서 고장 진단 및 actuator 고장 진단용 BJDF(Beard-Jones Detection Filter)를 설계하여 그 기능을 파악하였고 일반적인 상태변수추정기와의 차이점을 보였다. 특히 센서의 Bias Error의 경우 상태변수 확장기법을 이용하여 actuator 고장진단의 모형으로 모형화 할 수 있음을 보였다. 이로 인하여 센서 고장의 경우 2차원 평면에 국한된 residual이 일정 방향의 residual로 되므로 고장진단이 용이함을 알 수 있었다.

• 한국전자통신학회논문지
• /
• 제14권1호
• /
• pp.265-274
• /
• 2019

본 논문은 저가형 AHRS(: Attitude Heading Reference System)센서를 이용하여 무인 운송체(Unmanned vehicle)의 자세를 무향 칼만 필터 (Unscented Kalman filter)통해 추정하는 방법을 제안한다. 측정된 가속도와 지구자기장 값을 이용하여 UKF의 보정 단계에서 사용될 자세를 계산한다. 롤 (roll)과 피치 (pitch)는 가속도로부터 구해지며 요 (yaw)는 지구 자기장을 이용하여 연산한다. 이때 사용되는 지구자기장 측정값은 강철 효과(hard-iron effect)와 연철 효과(soft-iron effect)에 의해 쉽게 왜곡되기 때문에 계산된 요의 불확실성이 롤이나 피치의 불확실성에 비하여 크다. 본 논문은 이러한 불확실성을 줄이기 위하여 측정된 지구자기장에 포함된 편차성분을 추정하고 보정하여 더 정밀한 요값을 구한다. 제안된 방법을 수조에서의 무인 운송체 항법 실험을 통하여 검증하였다. 실험결과, 자세 추정 성능이 개선되고 이에 따라 위치 추정 성능도 개선됨을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.34-39
• /
• 1993

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.