Title :
Automatic calibration for inertial measurement unit
Author :
Chi Ming Cheuk ; Tak Kit Lau ; Kai Wun Lin ; Yunhui Liu
Author_Institution :
Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Shatin, China
Abstract :
The nine degrees-of-freedom (DOF) inertial measurement units (IMU) are generally composed of three kinds of sensor: accelerometer, gyroscope and magnetometer. The calibration of these sensor suites not only requires turn-table or purpose-built fixture, but also entails a complex and laborious procedure in data sampling. In this paper, we propose a method to calibrate a 9-DOF IMU by using a set of casually sampled raw sensor measurement. Our sampling procedure allows the sensor suite to move by hand and only requires about six minutes of fast and slow arbitrary rotations with intermittent pauses. It requires neither the specially-designed fixture and equipment, nor the strict sequences of sampling steps. At the core of our method are the techniques of data filtering and a hierarchical scheme for calibration. All the raw sensor measurements are preprocessed by a series of band-pass filters before use. And our calibration scheme makes use of the gravity and the ambient magnetic field as references, and hierarchically calibrates the sensor model parameters towards the minimization of the mis-alignment, scaling and bias errors. Moreover, the calibration steps are formulated as a series of function optimization problems and are solved by an evolutionary algorithm. Finally, the performance of our method is experimentally evaluated. The results show that our method can effectively calibrate the sensor model parameters from one set of raw sensor measurement, and yield consistent calibration results.
Keywords :
accelerometers; band-pass filters; calibration; computerised instrumentation; control engineering computing; evolutionary computation; gyroscopes; magnetometers; motion control; path planning; robots; sampling methods; 9-DOF IMU calibration; accelerometer; ambient magnetic field; band-pass filter; bias error; data filtering technique; data sampling; degrees-of-freedom; evolutionary algorithm; function optimization problem; gravity; gyroscope; hierarchical scheme; inertial measurement unit; magnetometer; misalignment error; motion control; purpose-built fixture; raw sensor measurement; robotics; sampling step; scaling error; sensor; trajectory planning; turn-table; Accelerometers; Calibration; Gravity; Gyroscopes; Magnetometers; Robot sensing systems; Vectors;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
DOI :
10.1109/ICARCV.2012.6485340