SOURCE-LINKED INTELLIGENCE
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
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-01T05:07:14.000Z
First collected: 2026-09-21T06:11:57.537Z. This is not the publication date.