Abstract:
Inertial sensors such as Gyroscope and Accelerometer show various systematic as well as random errors in the measurement. Additionally, double integration method shows ac...Show MoreMetadata
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.
Date of Conference: 21-25 June 2011
Date Added to IEEE Xplore: 01 August 2011
ISBN Information: