Strapdown Inertial Navigation Systems for Positioning Mobile Robots-MEMS Gyroscopes Random Errors Analysis Using...

Area of Science:

• Robotics
• Navigation Systems
• Sensor Technology

Background:

• Estimating mobile robot movement and orientation is crucial for navigation.
• Strapdown inertial navigation systems (INS) commonly employ gyroscopes for this task.
• Gyroscopes are sensitive components susceptible to various error sources.

Discussion:

• Analysis of MEMS gyroscope (InvenSense MPU-6050) random error components, including bias instability and random rate walk.
• Investigation of white and exponentially correlated (Markov) noise effects on gyroscope performance.
• Determination of Allan variance graphs, bias instability coefficients, and angle random walk for each axis at a 70 Hz sampling frequency.

Key Insights:

• Markov noise and random rate walk were not detected in the investigated gyroscopes.
• The X and Z axes exhibited higher noise levels compared to the Y axis.
• Calibration identified correction coefficients to mitigate destabilizing factors and axis misalignment.

Outlook:

• Post-calibration gyroscope output signals remain noisy and offset, necessitating further noise reduction.
• Alpha-beta or Kalman filters are recommended for processing accelerometer and gyroscope data to minimize noise influence.
• Optimizing gyroscope parameters and implementing advanced filtering techniques are essential for enhanced robotic navigation accuracy.