Inertial Sensor-Based Attitude Estimation Combining a Kinematic Constraint for Elimination of Acceleration-Induced Inaccuracy

被引:0
|
作者
Choi, Mi Jin [1 ]
Lee, Jung Keun [1 ,2 ]
机构
[1] Hankyong Natl Univ, Dept Mech Engn, Anseong, South Korea
[2] Hankyong Natl Univ, Inst Machine Convergence Technol, Anseong, South Korea
关键词
Inertial Sensor; Attitude; Acceleration-Induced Inaccuracy; Kinematic Constraint; Kalman Filter;
D O I
10.3795/KSME-A.2018.42.3.263
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Regarding attitude estimation Kalman filter (KF) based on inertial sensor signals, one of the major issues that affect the estimation accuracy is the acceleration-induced inaccuracy associated with accelerometer signals. To deal with this issue, researchers have proposed various types of acceleration-compensating mechanisms. Because those mechanisms, however, are basically stochastic approaches, such as Markov chain models, they cannot thoroughly eliminate the acceleration-induced inaccuracy. Resultantly, improvement in estimation performance is limited. In this paper, the kinematic constraint associated with a ball joint is formulated to eliminate the acceleration-induced inaccuracy. Then, the constraint is augmented in a state-of-the-art attitude estimation KF. In our experimental results, the proposed KF with constraint was superior to the conventional KF by an average of 6.31 degrees and a maximum of 11.22 degrees.
引用
收藏
页码:263 / 269
页数:7
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