Title :
Evaluation of solid state accelerometer sensor for effective position estimation
Author :
Lele, Meenal A. ; Gu, Jason
Author_Institution :
Electron. & Inf. Eng. Coll., Henan Univ. of Sci. & Technol., Luoyang, China
Abstract :
Inertial sensors such as Gyroscope and Accelerometer show various systematic as well as random errors in the measurement. Additionally, double integration method shows accumulation of error in position estimation due to inherent accelerometer bias drift. This paper describes the evaluation of acceleration sensor errors for better position estimation using acceleration bias drift error model. The fitted model was validated by using regression analysis. The proposed calibration system consists of a rotary wheel carrying accelerometer sensor and data acquisition board. In this paper we are presenting the proposed mechanical design for the calibration and testing of the accelerometer sensor, using Kalman filter smoothing algorithm. This study showed that the accelerometer may be used for short distance mobile robot position estimation in absence of external sensor. This research paper would also help to establish a generalized test procedure for the evaluation of accelerometer in terms of sensitivity, accuracy and data reliability.
Keywords :
Kalman filters; accelerometers; calibration; data acquisition; navigation; regression analysis; smoothing methods; Kalman filter smoothing algorithm; acceleration bias drift error model; acceleration sensor error; calibration system; data acquisition board; position estimation; regression analysis; rotary wheel carrying accelerometer sensor; solid state accelerometer sensor; Acceleration; Accelerometers; Equations; Kalman filters; Mathematical model; Robot sensing systems; Wheels; Calibration; Kalman Filter; Sensor Fusion; bias drift; solid state accelerometer;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2011 9th World Congress on
Conference_Location :
Taipei
Print_ISBN :
978-1-61284-698-9
DOI :
10.1109/WCICA.2011.5970658