Let’s Build an Arduino-based Kalman Filter for Attitude Determination

Attitude determination, the process of determining the orientation of an object with respect to a fixed reference frame, is an essential aspect of navigation, control, and guidance systems in various fields, such as aerospace, robotics, and autonomous vehicles. Sensor data from these systems are noisy. This is where the Kalman filter, a mathematical algorithm that combines measurements and predictions to estimate the state of a dynamic system, comes in. Kalman filtering is one of the most popular methods for cleaning up noisy sensor data and I am going to show you how you can build your own. In this article, we will explore how to build an Arduino-based Kalman filter for attitude determination. Building this for an Arduino means it will be a cost-effective and versatile solution for small-scale applications like hobby drones. We will cover a bit about the theory behind the Kalman filter, the hardware and software requirements, and the implementation of the filter using an Arduino Nano and six-axis (accelerometer + gyroscope) MPU-6050 motion sensor. By the end of this article, you will have a basic understanding of how Kalman filters work and how you can use a Kalman filter for attitude estimation. <a href="https://betterprogramming.pub/let-build-an-arduino-based-kalman-filter-for-attitude-determination-a895263b172">Read More</a>