DocumentCode :
250473
Title :
A robust and easy to implement method for IMU calibration without external equipments
Author :
Tedaldi, David ; Pretto, Alberto ; Menegatti, Emanuele
Author_Institution :
Dept. of Inf. Eng., Univ. of Padova, Padua, Italy
fYear :
2014
fDate :
May 31 2014-June 7 2014
Firstpage :
3042
Lastpage :
3049
Abstract :
Motion sensors as inertial measurement units (IMU) are widely used in robotics, for instance in the navigation and mapping tasks. Nowadays, many low cost micro electro mechanical systems (MEMS) based IMU are available off the shelf, while smartphones and similar devices are almost always equipped with low-cost embedded IMU sensors. Nevertheless, low cost IMUs are affected by systematic error given by imprecise scaling factors and axes misalignments that decrease accuracy in the position and attitudes estimation. In this paper, we propose a robust and easy to implement method to calibrate an IMU without any external equipment. The procedure is based on a multi-position scheme, providing scale and misalignments factors for both the accelerometers and gyroscopes triads, while estimating the sensor biases. Our method only requires the sensor to be moved by hand and placed in a set of different, static positions (attitudes). We describe a robust and quick calibration protocol that exploits an effective parameterless static filter to reliably detect the static intervals in the sensor measurements, where we assume local stability of the gravity´s magnitude and stable temperature. We first calibrate the accelerometers triad taking measurement samples in the static intervals. We then exploit these results to calibrate the gyroscopes, employing a robust numerical integration technique. The performances of the proposed calibration technique has been successfully evaluated via extensive simulations and real experiments with a commercial IMU provided with a calibration certificate as reference data.
Keywords :
accelerometers; calibration; gyroscopes; inertial systems; integration; micromechanical devices; IMU calibration; MEMS; accelerometers triad; attitudes estimation; axes misalignments; calibration certificate; calibration protocol; gyroscopes; imprecise scaling factors; inertial measurement units; mapping tasks; microelectro mechanical systems based IMU; motion sensors; navigation tasks; parameterless static filter; position estimation; robotics; robust numerical integration technique; sensor biases; static positions; Accelerometers; Accuracy; Calibration; Gravity; Gyroscopes; Sensors; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2014 IEEE International Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/ICRA.2014.6907297
Filename :
6907297
Link To Document :
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