Authors:
Andrejs Zujevs
;
Valters Vecins
and
Aleksandrs Korsunovs
Affiliation:
Riga Technical University, Kalku iela 1, Riga and Latvia
Keyword(s):
IMU, MEMS, Calibration, Static Detector.
Related
Ontology
Subjects/Areas/Topics:
Computer and Microprocessor-Based Control
;
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Robotics and Automation
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
An Inertial Measuring Unit (IMU) is used for measuring linear accelerations and angular velocities in 3D/2D space. IMU devices are usually designed as micro-electro-mechanical systems (MEMS), which are produced in small form factor and are widely used in robotics, mobile phones and drones. Depending on the quality of the device, they can be divided into low-cost and high-cost IMUs. The main difference between them is the accuracy of measurements and IMUs mechanical alignment on the printed circuit board. The high-cost IMUs are well calibrated and have a relatively small error and noise level for different kinds of parameters. In contrast, the low-cost IMUs have a larger error component, where body frame axes are non-orthogonal for both the accelerometer and gyroscope due to weak factory calibration, high noise and high sensitivity dependence from the temperature, misalignment of body frame due to packaging and assembly processes. This paper provides a new method for the IMU static an
d dynamic interval detection within the IMU calibration procedure, which is designed by other authors for the case of IMU calibration without any external equipment. This procedure uses a sequence of alternating static and dynamic intervals for accelerometer calibration and then gyroscope calibration. The accuracy of the IMU calibration procedure depends strongly on how precisely static and dynamic intervals have been detected. Otherwise, the calibration results are unsuitable. The new method for static and dynamic interval detection provides more robust and less noisy results, requires a significantly smaller number of operations and is easy to implement. The paper provides comparative results for both methods and refers to the source code for the new method.
(More)