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of the Shell Innovation Award
Design of a low cost, small-scale localisation system suited to the Eurobot competition
Group Members
Justin Godden, Oliver Heilmann, Caroline Layzell, Michael Leat, Alice Loneragan
Professor Paul White, Professor Martyn Hill
The Boeing Company
Localisation is the understanding of one’s position relative to their environment. This project proposes the design of a localisation system for autonomous robots featuring an innovative combination of gyroscopic, optical and ultrasonic sensors to determine their position. The system has been designed to improve performance in the Eurobot competition and has wider applications ranging from automotive vehicles to domestic robotics.

Throughout this project, various types of sensors were assessed to find the combination which provided the most cost effective solution for this application. The use of a Kalman filter, which is a technique used to fuse readings from an array of different sensors and a PID controller, used to correct any inaccurate motions as the robot traverses its path, were investigated. To evaluate the accuracy of the platform, a bespoke test method was designed and manufactured. It uses an overhead camera to track the actual position of the robot, which is then compared to the robot’s estimated position.

At the conclusion of the project, a completed system using an optical sensor and proportional–integral–derivative (PID) controller, which uses feedback to apply corrections, was designed and manufactured. The system is able to estimate its position to within an accuracy of 20 mm. The test method has been validated to measure the position trajectory of a robot with an accuracy of 3 mm.
Exploded diagram of robot showing internal components.