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Derivation-Based Calibration of IMUs Using Savitzky-Golay Filters.

Diogo Vieira1,2,3, Miguel Oliveira1,2,3, Rafael Arrais4,5

  • 1Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.

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Summary
This summary is machine-generated.

This study introduces a new method for calibrating Inertial Measurement Units (IMUs) in robots. It avoids integration errors by using derivatives, improving accuracy for mobile platforms and drones.

Keywords:
Savitzky–Golay filterextrinsic calibrationinertial measurement unitrobotic system calibration

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Area of Science:

  • Robotics
  • Sensor Technology
  • Mechatronics

Background:

  • Accurate sensor calibration is vital for robotic applications.
  • Inertial Measurement Units (IMUs) are commonly used in mobile robots and drones.
  • Existing IMU calibration methods often require a second sensor and suffer from integration errors.

Purpose of the Study:

  • To present a novel extrinsic calibration method for IMUs in robotic systems.
  • To overcome the limitations of current calibration techniques, specifically integration errors.
  • To improve the accuracy and reliability of IMU measurements in robotics.

Main Methods:

  • Developed a derivative-based approach using Savitzky-Golay filters to avoid IMU integration.
  • Estimated the transformation between an IMU sensor and its parent frame.
  • Minimized differences between derived and measured linear accelerations and angular velocities.
  • Validated the method using simulated data to establish ground truth.

Main Results:

  • The proposed method demonstrated higher accuracy compared to existing alternatives.
  • The calibration technique effectively avoids errors associated with IMU integration.
  • The method is applicable to industrial-grade IMUs, showing practical utility.

Conclusions:

  • The new derivative-based IMU calibration method offers superior accuracy.
  • This approach provides a robust solution for extrinsic IMU calibration in robotics.
  • The method's applicability to industrial IMUs highlights its potential for real-world robotic systems.