Curious about studying MSc Intelligent Systems and Roboticsat University of Essex? We've gathered all the key details—entry requirements, modules, fees, and more. Hear from real students by checking out reviews, or take the next step by booking an open day to explore it for yourself.
Master of Science - MSc
University of Essex
Full Time
Oct 2027
1 Year
Our MSc Intelligent Systems and Robotics course provides a comprehensive coverage of contemporary intelligent systems, with robots serving as a major example of the technology. Thanks to the leading research being undertaken in our School of Computer Science and Electronic Engineering, you gain a solid understanding of the foundations of this technology,.Our MSc Intelligent Systems and Robotics is delivered by our team of researchers, with expertise spanning the entire range of intelligent systems and experience of developing robots intended for land, under water and in the air.Research carried out by our team has resulted in appearance in the Robot Soccer World Cup final, an autonomous robot fish in the London Aquarium, and a self-programming computer vision system.
What fascinates you? Apply your learning in computer science or engineering to solve a problem. Design, implement and evaluate a solution, producing a dissertation on your investigation and giving an oral presentation of your work. Test your knowledge, while gaining practical experience and building your project management skills.
This module gives an introduction to intelligent systems and robotics. It goes on to consider the essential hardware for sensing and manipulating the real world, and their properties and characteristics. The programming of intelligent systems and real-world robots are explored in the context of localisation, mapping, and fuzzy logic control.
Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.
Wish to design, program and evaluate embedded systems from software specification to hardware implementation? Study the techniques to develop software for embedded systems and robotics. Examine performance needs and the key issues in designing real-time software for embedded systems in real-world applications. Understand the main techniques of real-time programming.
Computer vision is the discipline that tries to understand the content of images and videos. It has an extraordinarily wide range of applications; well-known ones include inspection on production lines, reading number plates, mixing live and computer-generated action in movies, and recognising faces. However, researchers are working on applications such as driverless cars, building 3D models from photographs, robot navigation, gaming interfaces, and automated medical diagnosis -- in fact, whenever you as a human looks at the world and try to understand what you see is fair game for computer vision. This module introduces you to the principles of computer vision through a series of lectures and demonstrations. You have an opportunity to learn how to use these principles and algorithms on real-world vision problems in the associated laboratories using the industry-standard toolkit, OpenCV.
This module aims to prepare students for conducting an independent research project leading to a dissertation and to provide them with an appreciation of research and business skills related to their professional career. As a precursor to their project students, individually select an area of Computer Science, or Electronic Engineering, or Computational Finance and perform the necessary background research to define a topic and prepare a project proposal under the guidance of a supervisor. The module guides them by a) introducing common research methods b) creating an understanding of basic statistics for describing and making conclusions from data c) helping to write a strong proposal including learning how to perform literature search and evaluation and d) giving an in-depth view into the business enterprise, financial and management accounting and investment appraisal.
Teamwork skills are essential for employability. The aim of this module is to provide students with the opportunity to apply their specialised knowledge to a realistic problem and gain practical experience of the processes involved in the team-based production of software. Wherever possible, teams are organised on the basis of shared interest, and the problem is designed to exercise their understanding of their area of specialised study. Starting from an outline description of a realistic problem, each team is required to develop a fully implemented software solution using appropriate engineering and project management techniques.