Odometer Module for Mobile Robot with Position Error Estimation

In this article, an odometry module for a mobile robot with probabilistic position estimation is proposed. The localization processing is based on Extended Kalman Filter (EKF) from which only prediction phase is used. This configuration is prepared for a possible later extension with Global navigation satellite system (GNSS). Scale factor correction and University of Michigan Benchmark test (UMBmark) measurements were concluded to correct model parameters of the robot. The correction outcome was tested on an experiment with simultaneous Global Positioning System (GPS) and odometry localization. The realized differential drive mobile robot has an optical encoder for each wheel. They are connected to STM32F4 development board which calculates the odometric data and sends them with a time-stamp from GPS module over the Bluetooth to PC. Visualization and control program was created to log and store the odometric data and also to set up the odometric parameters in the firmware of the microcontroller.