This thesis showcases how computer vision and artificial intelligencecan be combined to a system that is able to navigate surroundings byintercepting visual stimulants.The system is built to operate on signs which displays eight colored shapeswere different patterns of shapes will direct the user. When a sign is in-tercepted by the system, the shapes and their spatial positioning will beextracted with the help of computer vision and be processed by a modelof computation known as Vector Symbolic Architectures. This model of-fers a way to learn and reason about the patterns which leads to certainlocations. It uses high dimensional vectors to represent entities such ascolors, shapes and positions and with the help of basic mathematical op-erations provides the ability to produce vectors that represents conceptsconstructed of many such entities. Because of this representation it ispossible to preform classification and provide guidance based on the sim-ilarities of previous collected concepts.This paper will focus on the practical details of how such a Vector Sym-bolic Architecture model can be implemented and how it is able to providethe functionality for a navigation system.