Speed Estimation for Control of an Unmanned Ground Vehicle using Extremely Low Resolution Sensors.

In mobile robotics, the low-level control is a key component that translates the desires of the high-level system into actual voltages and currents to drive the motors. PID controllers have been extensively used for speed control, but their performance depend heavily on the quality of the process variable (PV) estimation. In fact, noise and outliers –if not properly filtered– might lead to system instability. In this work, we present a speed estimation strategy that enables us to develop an inexpensive, accurate and easy-to-install speed control solution. The proposed system relies on a Hall effect sensor and a Single-Dimensional Kalman Filter and its suitability is demonstrated through a number of real experiments controlling the speed of an Unmanned Ground Vehicle. We detail the design, implementation and validation processes and provide a GitHub repository with the developed software and CAD designs.