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Enhancing Sensor Data Integration for Precise Motion Tracking

This project involves correcting unit conversions, fixing errors, and improving accuracy in integrating velocity and position data from sensors. Data on rotations, constant motion, and stationary periods has been collected. Gyroscopes tend to drift over time, while accelerometer data requires more precise filtering methods like Kalman filter. The focus is on finding optimal filters for acceleration, testing planar motion displacement, and integrating transformation matrix code for 3D motion testing.

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Enhancing Sensor Data Integration for Precise Motion Tracking

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  1. Current Works • Corrected unit conversions in code • Found an error in calculating offset (to zero sensors) • Fixed error, but still not accurately integrating to correct velocity/position • Collected data on rotations, constant motion in one direction, and when stationary • Orientation data is fairly accurate, but gyroscopes do drift over time • Accelerometer data needs more precise filtering • Tried low pass, high pass, and started testing a band pass filter on accelerometer data • High pass should remove error due to incorrect offset • Wrote Kalman filter m file for roll orientation

  2. Stationary Test

  3. Rotation Test

  4. Move 1 meter in Y Direction

  5. What’s Next? • Find and implement optimal filter for acceleration • Test on planar motion displacement • Test Kalman filter for orientation • Integrate transformation matrix code to begin testing with 3D motion

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