Race track position estimation for the UoM racing car

Abstract

In order to allow for data-driven engineering decisions to be made, a platform for managing the data is required. This project aims to create a system which will streamline the process of gathering, management and analysis of automotive sensory data tied to a positional measurement. After analysing different proposed solutions, an integrated tracking system based on measurements from an Inertial Measurement Unit (IMU) and a Differential Global Navigations Satellite System (DGNSS) receiver was implemented. Data from these devices is gathered using a Raspberry Pi, which relays the data to a web-hosted server. Here, the processing and storage of data is implemented, allowing the system to be accessed remotely via a cross-platform web application. The accuracy of different positional measurement techniques is assessed through the selection of specific criteria. Based on this assessment, it was concluded that best estimation of position was obtained through the use of a Kalman filter.