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Journal ArticleDOI

Performance Improvement of Attitude Estimation Using Modified Euler Angle Based Kalman Filter

01 Jan 2008-Journal of Institute of Control Robotics and Systems (Institute of Control, Robotics and Systems)-Vol. 14, Iss: 9, pp 881-885
TL;DR: In this article, a new Kalman filter method is proposed for roll and pitch attitude estimation in ARS using three gyros and three accelerometers, gyro drift must be compensated with accelerometer to avoid divergence of attitude error.
Abstract: 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.

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Citations
More filters
Proceedings ArticleDOI
26 Aug 2009
TL;DR: A Kalman filter model with a modified state is presented and an adaptive algorithm is used to make the filter more robust regarding acceleration disturbances and the performance of the proposed algorithm is shown.
Abstract: This paper introduces the attitude estimation method of humanoid robot using an extended Kalman filter with a fuzzy logic based tuning algorithm. A humanoid robot which uses inertial sensors such as gyros and accelerometers to calculate its attitude is considered. It is known that the attitude update using gyros are prone to diverge and hence the attitude error needs to be compensated using accelerometers. In this paper, a Kalman filter model with a modified state is presented and an adaptive algorithm is used to make the filter more robust regarding acceleration disturbances. If the accelerometer measures any disturbances caused by movement of the vehicle, the characteristics of the filter must be changed to ensure confidence of the outputs of the gyros. The performance of the proposed algorithm is shown by the experiments.

55 citations

Journal ArticleDOI
민형기, 김지훈, 윤주한, 정은태, 권성하 
TL;DR: In this paper, a complementary filter is used to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot and linearize that dynamics for using LQR method.
Abstract: This paper shows to stabilize a balancing robot. We derive the dynamics of a balancing robot and design its controller using LQR method. For stabilizing balancing robot, we introduce a method to detect an angle using inertial sensors. In this study, we use a complementary filter to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot. The filter coefficients are obtained by least square to minimize error in angle-detecting filter design. And then, after we derive a dynamics of balancing robot using Lagrange method, we linearize that dynamics for using LQR method.

11 citations


Additional excerpts

  • ...[8] C....

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  • ...그 중 일반 적으로 각도 추정에서 많이 사용하는 것은 각속도를 검출 하는 자이로 센서와 가속도 성분을 검출하는 가속도 센서 를 이용하는 방법이 많이 사용되고 있다[7-11]....

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01 Mar 2013
TL;DR: In this article, the attitude control for a two-rotor system with 3DOF (degree-of-freedom) with two DC motors equipped at the two ends of a rectangular beam to generate lift force and the relation between motor voltage and lift force is found experimentally.
Abstract: This paper presents experimental results of the attitude control for a two-rotor system with 3-DOF(degree-of-freedom). Two DC motors are equipped at the two ends of a rectangular beam to generate lift force and the relation between motor voltage and lift force is found experimentally. And inertial sensors are mounted at the center of the beam to measure the roll angle and a complementary filter is designed to get the angle during DC motors driving. A controller with nonlinear compensation, integrator and state feedback to achieve asymptotic tracking for a step input and reject input disturbance is designed and experimented.

11 citations

Journal ArticleDOI
TL;DR: To avoid singularity of Euler angle, a new heading estimation parameter is introduced and a filter mode switching algorithm is proposed that performed better than a quaternion algorithm based on magnetometer disturbance and was immune to the singularity problem.

9 citations

Journal ArticleDOI
TL;DR: An attitude estimation algorithm which integrates gyroscope and vision measurements using an adaptive complementary filter and fuzzy interpolator is applied in order to make the filter more tolerant to vision measurement fault and more robust to system dynamics.
Abstract: An attitude estimation algorithm which integrates gyroscope and vision measurements using an adaptive complementary filter is proposed in this paper. In order to make the filter more tolerant to vision measurement fault and more robust to system dynamics, fuzzy interpolator is applied. For recognizing the dynamic condition of the system and vision measurement fault, the cut-off frequency of the complementary filter is determined adaptively by using the fuzzy logic with designed membership functions. The performance of the proposed algorithm is evaluated by experiments and it is confirmed that proposed algorithm works well in the static or dynamic condition.

6 citations


Cites methods from "Performance Improvement of Attitude..."

  • ...In general case, data fusion algorithms are implemented to integrate two information sources from the gyroscope and accelerometer, respectively by using extended Kalman filter [4, 5] or complementary filter [6, 7, 8]....

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References
More filters
Book
23 Jun 2006
TL;DR: With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory.
Abstract: A bottom-up approach that enables readers to master and apply the latest techniques in state estimationThis book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering.While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering.Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. A solutions manual is available for instructors.With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.A solutions manual is available upon request from the Wiley editorial board.

2,711 citations


Additional excerpts

  • ...[9] D....

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  • ...Q 와 R은 (14)와 같다[9]....

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Journal ArticleDOI
12 Sep 2005
TL;DR: A complementary Kalman filter design to estimate orientation of human body segments by fusing gyroscope, accelerometer, and magnetometer signals from miniature sensors shows accurate and drift-free orientation estimates.
Abstract: This paper describes a complementary Kalman filter design to estimate orientation of human body segments by fusing gyroscope, accelerometer, and magnetometer signals from miniature sensors. Ferromagnetic materials or other magnetic fields near the sensor module disturb the local earth magnetic field and, therefore, the orientation estimation, which impedes many (ambulatory) applications. In the filter, the gyroscope bias error, orientation error, and magnetic disturbance error are estimated. The filter was tested under quasi-static and dynamic conditions with ferromagnetic materials close to the sensor module. The quasi-static experiments implied static positions and rotations around the three axes. In the dynamic experiments, three-dimensional rotations were performed near a metal tool case. The orientation estimated by the filter was compared with the orientation obtained with an optical reference system Vicon. Results show accurate and drift-free orientation estimates. The compensation results in a significant difference (p<0.01) between the orientation estimates with compensation of magnetic disturbances in comparison to no compensation or only gyroscopes. The average static error was 1.4/spl deg/ (standard deviation 0.4) in the magnetically disturbed experiments. The dynamic error was 2.6/spl deg/ root means square.

551 citations

Proceedings ArticleDOI
30 Mar 1996
TL;DR: The design of a Kalman filter is described to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.
Abstract: Current virtual environment and teleoperator applications are hampered by the need for an accurate, quick-responding head-tracking system with a large working volume. Gyroscopic orientation sensors can overcome problems with jitter, latency, interference, line-of-sight obscurations and limited range, but suffer from slow drift. Gravimetric inclinometers can detect attitude without drifting, but are slow and sensitive to transverse accelerations. This paper describes the design of a Kalman filter to integrate the data from these two types of sensors in order to achieve the excellent dynamic response of an inertial system without drift, and without the acceleration sensitivity of inclinometers.

457 citations


Additional excerpts

  • ...[2] E....

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  • ...기존 연구에서는 자이로 출력을 이용하 여 계산된 자세와 가속도계 출력을 이용하여 계산된 자세를 서로 비교하여 자이로의 오차와 자세 오차를 추정하여 다시 추정된 자세를 계산하는 방식의 칼만필터를 구성하였다[1-3]....

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  • ...(8)의 형태로 정의된 상태 변수를 도입함으로써 기존 연구[1-3,6,8]에서의 복잡한 시스템 방정식을 선형화된 간단한 형태로 대체할 수 있다....

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30 Oct 2002
TL;DR: In this paper, the authors proposed a method to solve the problem of 2.3.83-approximation, 2.2.83, and 2.1.83
Abstract: 83

237 citations


Additional excerpts

  • ...기존 연구에서는 자이로 출력을 이용하 여 계산된 자세와 가속도계 출력을 이용하여 계산된 자세를 서로 비교하여 자이로의 오차와 자세 오차를 추정하여 다시 추정된 자세를 계산하는 방식의 칼만필터를 구성하였다[1-3]....

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  • ...(8)의 형태로 정의된 상태 변수를 도입함으로써 기존 연구[1-3,6,8]에서의 복잡한 시스템 방정식을 선형화된 간단한 형태로 대체할 수 있다....

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  • ...185-194, 1996 [3] H....

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Proceedings ArticleDOI
08 Nov 1999
TL;DR: This paper describes the design, implementation, and preliminary testing of an inertial tracking system using a "complementary" filter based upon quaternions that is capable of tracking a rigid body through all orientations and is more efficient than those based on Euler angles.
Abstract: Joint angle determination for robots with flexible links can be difficult. Inertial orientation tracking combined with RF positioning provides an accurate method for determining end effector orientation and location. The same technology could also be used to determine human posture for the purpose of inserting humans in synthetic environments. Orientation filters based upon Euler angles suffer from singularities. This paper describes the design, implementation, and preliminary testing of an inertial tracking system using a "complementary" filter based upon quaternions. This filter is capable of tracking a rigid body through all orientations and is more efficient than those based on Euler angles. Results of qualitative tests of a prototype inertial angle tracking device are presented.

171 citations


Additional excerpts

  • ...[4] E....

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  • ...또한 쿼터니언 계산방식을 적용하여 자세를 보정하는 연구 도 진행되었으나 동체가 정지한 상황만을 고려하므로 실제 운행 중에 있는 로봇이나 차량에 적용하기 힘들다는 단점이 존재했다[4,5]....

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