Design and Implementation of a Kalman Filter-Infused Algorithm for Tilt Estimation
Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However, measurements from low-cost inertial sensors are often degraded by noise and drift. This paper presents a single-axis tilt angle estimation system based on the MPU6050 inertial measurement unit, implemented on an RP2040 microcontroller platform, with sensor fusion achieved through a Kalman filter. The accelerometer provides a direct estimate of tilt angle from gravity but is sensitive to noise and short-term fluctuations. The gyroscope provides smooth angular rate measurements, but integration over time introduces drift. To overcome these l...
| Authors | Yuehan Ma, Hongji Dai |
|---|---|
| Primary category | cs.CV |
| Published | 1 September 2026 |
| Last updated at source | 1 October 2026 |
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