The main goal of this article is to fully explore the capability of the 'No Motion No Integration' (NMNI) technique for the optimization of the Euler angles in orientation tracking. The gyroscope is the critical component in the inertial measurement unit for angle detection in Industry 4.0. An upgraded NMNI model is introduced to remove the drift of the gyroscope significantly for the advanced measurement approach for roll, pitch, and yaw. A model of threshold update is implemented into the NMNI algorithm to compensate for the increased offset of temperature. This preprocessing method is applied to the Madgwick filter and Mahony filter to acquire the optimal performance. The experiments were carried out by using a low-cost platform equipped with microelectromechanical system sensors. A pan-tilt unit with high accurate positioning was used to move the sensors and obtain a reference angle during both static and dynamic experiments. A substantial improvement was clearly demonstrated after the optimization process. The measurements of the Euler angles have minimized noise and tracks around the reference points properly. The results show strong competition from both fusion filters where the fused Mahony accomplishes more stable less variation in roll and pitch, but the fused Madgwick shows more precision in heading/yaw estimation.

Measurement Optimization for Orientation Tracking Based on No Motion No Integration Technique

Hoang M. L.;Paciello V.
;
Pietrosanto A.
2021-01-01

Abstract

The main goal of this article is to fully explore the capability of the 'No Motion No Integration' (NMNI) technique for the optimization of the Euler angles in orientation tracking. The gyroscope is the critical component in the inertial measurement unit for angle detection in Industry 4.0. An upgraded NMNI model is introduced to remove the drift of the gyroscope significantly for the advanced measurement approach for roll, pitch, and yaw. A model of threshold update is implemented into the NMNI algorithm to compensate for the increased offset of temperature. This preprocessing method is applied to the Madgwick filter and Mahony filter to acquire the optimal performance. The experiments were carried out by using a low-cost platform equipped with microelectromechanical system sensors. A pan-tilt unit with high accurate positioning was used to move the sensors and obtain a reference angle during both static and dynamic experiments. A substantial improvement was clearly demonstrated after the optimization process. The measurements of the Euler angles have minimized noise and tracks around the reference points properly. The results show strong competition from both fusion filters where the fused Mahony accomplishes more stable less variation in roll and pitch, but the fused Madgwick shows more precision in heading/yaw estimation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4782872
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