Jonathan Lee Rossi

Yosemite

Striving for Vertical

I am working on a project to build a two-wheeled, self-balancing robot that uses Linear Quadratic Estimation (specifically, the Kalman Filter) in order to make continuous corrections to its angular velocity to stay upright. As I am developing the project, I am writing a comprehensive paper that details the theory and practice of building the robot. This paper can be downloaded below. Please reach out to me at jonathan.lee.rossi@gmail.com if you have questions about the project, or are building a similar project of your own and want to discuss!

Building the Robot/IMU Teapot Demo

This video demonstrates an initial check to ensure the IMU (Inertial Measurement Unit) is working properly. I use the on-board DMP (a built-in data fusion tool that is okay for diagnostics but which we will replace with the Kalman Filter) to get a visual representation of the IMU's data as the robot moves around.  

Testing the Kalman Filter

  In this video, we explore the data coming out of the IMU in multiple forms: as raw data, as processed by the Complementary Filter, and most importantly, as fused under the Kalman Filter!

Download the Paper

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