MSc
2022 start September 

Robotics

Department of Automatic Control and Systems Engineering, Faculty of Engineering

Build on your existing knowledge to become an expert in robotics and autonomous systems, with the interdisciplinary skills to join the next generation of engineers.
Swarm robots

Course description

Robotics is increasingly important to a variety of sectors, including manufacturing, healthcare, aerospace, marine and many more. Cyber-physical systems, such as robotics and autonomous systems, the Internet of Things, the smart grid and cloud computing, are being used more widely

This course helps you translate your existing knowledge and skills by developing your knowledge and skills in the key areas of robotics and autonomous systems. You’ll learn about sensing and perception, cognition and autonomy, control and planning and robotic devices and systems.

You’ll be able to apply your skills across many engineering disciplines and you’ll use industry-standard CAD and hardware tools to design and analyse mechatronic systems.

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Modules

The modules listed below are examples from the last academic year. There may be some changes before you start your course. For the very latest module information, check with the department directly.

Core modules:

Data Modelling and Machine Intelligence

All of our lives are affected by machine intelligence and data models - Google is a very visible example; but if you are a victim of identity theft, if you want a loan to buy a house or if you want to pass through immigration at an airport, a model derived from data using some form of machine learning technique will be involved. Engineers increasingly look to machine intelligence techniques such as neural networks and other machine learning methods to solve problems that are not amenable to conventional analysis e.g. by application of Newton's & Kirchhoff's laws, and other physical principles. Instead, they use measurements of system variables to compute a model of the process that can then be used in design, analysis and forecasting. System identification is a specific example of data modelling. We will look at the underlying principles of machine learning, the advantages and limitations of the various approaches and effective ways of applying them with the aim of making you a competent practitioner.

15 credits
Foundations of Robotics

This is an introductory module on the foundations of robotics. The aim of this module is to consolidate fundamental robotics engineering aspects, including ethical ones, as well as introduce relevant topics to those new to the discipline. The module is separated into five distinct themes:
(a) Introduction to robotics and robot ethics
(b) Introductory maths
(c) Systems modelling and simulation
(d) Control systems analysis and design
(e) Introduction to programming

15 credits
Mechatronics for Robotics

This module covers methods to represent, analyse and design mechanical, electrical, computational systems and control, and their integration into mechatronic systems. This module will enable you to design, analyse, develop and integrate and evaluate mechatronic systems. The module includes lectures on the principles of mechatronic systems, 2D/3D CAD design, fabrication, sensors and instrumentation, actuation, digital data acquisition, signal pre-processing, hardware interfaces, microcontroller programming and peripherals; practicals on analysing mechatronic components; and project on developing a mechatronic system.

15 credits
Manipulator Robotics

The module aims to explore robotic manipulators, from theoretical concepts and modelling to practical implementations. You will be introduced to the different types and applications of robotic manipulators. An emphasis is placed on modelling and simulation. Sensing and actuation is also covered, with a focus on control of robot manipulators. You will be exposed to a wide range of practical applications of robotic manipulators, and encouraged to discuss and reflect on the implications of using robots (e.g. ethical considerations, safety, social and economic impacts), especially within manufacturing.

15 credits
Mobile Robotics and Autonomous Systems

Robotics and autonomous systems are having an increasing impact on society and the way we live. From advanced manufacturing and surgical robots to unmanned aerial systems and driverless cars, this exciting area is presenting increasing technological challenges. This module provides you with the advanced knowledge and understanding to apply control and systems engineering concepts to the closely related disciplines of robotics and autonomous systems. The module covers theoretical and technical analysis, and design aspects of mobile and manipulator robots with reference to their applications. The module further covers advanced techniques in autonomous decision making for robots and autonomous vehicles.

15 credits
Machine Vision

The module gives knowledge of machine vision methods for a broad range of applications. It introduces you to image and video processing models and methods and provides you with skills on how to embed them in autonomous systems. You will be able to apply the acquired knowledge to both industrial and research areas.

15 credits
Multisensor and Decision Systems

The ability to use data and information from multiple sources and make informed decisions based on that data is key to many applications, e.g. manufacturing, aerospace, robotics, finance and healthcare. Through effective use of multisensory data and decision making we can reduce uncertainty, improve robustness and reliability, enhance efficiency and ultimately improve the performance of systems. In this module you will develop an in depth knowledge and understanding of multisensor and decision systems and the underlying mathematics and algorithms. You will develop your confidence in solving complex problems requiring the application of multisensory and decision techniques to a wide variety of applications.

15 credits
Robotics Project and Dissertation

The aim of the project is to give you the opportunity to develop further your advanced knowledge and skills and apply these to a specific problem or set of problems. It builds on the taught modules and develops a greater level of independence. You will be allocated a project supervisor with whom you will develop the project specification and who will provide overall guidance on the project. However, you are expected to demonstrate a high level of initiative and independence. You will also develop skills in creative and critical thinking, analysis, reflection, effective project management and communication. The project is very different from many of your taught modules where the lecturer takes the lead in your learning. In the project, you are expected to take the lead and the supervisor is expected to provide overall guidance and help.

60 credits

Optional modules - examples include:

Industrial Training Programme (ITP) in Computational Intelligence

This module will provide an insight into advanced computational intelligence systems via industry-relevant project work. This will be in collaboration with an industrial partner. The industrial partner will set a real technical challenge and your group will undertake practical and theoretical work and present a report that will also require an in-depth literature review. To supplement the main technical challenge there will be focused technical seminars on relevant topics. These topics will be provided by both academics and industry engineers. In addition, the industrial partner will provide seminars relevant to both professional and technical skills to help you complete the project.

15 credits
Deep Learning

An important field within artificial intelligence is machine learning, which enables systems to learn from data rather than being explicitly programmed to solve a task. Conventional machine learning algorithms tend to rely on a human to carefully engineer and extract features to present to a machine learning algorithm, which can be time-consuming and difficult. A deep learning system, by contrast, takes raw data as input and learns to extract features automatically. This approach has led to significant improvements in processing images, video, speech and audio. Deep learning has also had an impact on the design of intelligent agents, giving rise to the area of deep reinforcement learning, which is where an agent learns in a reward-based framework. An example of deep reinforcement learning is where the Google DeepMind team designed an agent that learned to play Atari computer games to better-than-human-expert level.

15 credits

The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption. We are no longer offering unrestricted module choice. If your course included unrestricted modules, your department will provide a list of modules from their own and other subject areas that you can choose from.

Duration

1 year full-time

Teaching

There are lectures, seminars, tutorials, individual assignments and a major research project.

Roderich Gross

Our new MSc Robotics will provide you with the essential knowledge, understanding and skills that are needed for designing, implementing and deploying the robotics and autonomous systems (RAS) of the future. You will be inspired to think differently and create innovative solutions with the potential to change our lives.

Roderich Gross
Senior Lecturer in Robotics and Computational intelligence

Assessment

You’ll be assessed by exams, coursework assignments and a project dissertation.

Your career

Our courses are informed by our research and our strong links with industry. This MSc is an ideal preparation for students aiming to move onto a PhD and research career, or those who want to work in industry with robotics and autonomous systems. The MSc covers the required technical knowledge and skills, along with wider professional skills such as critical thinking, project management and communication, for graduates to excel in their chosen career.

Entry requirements

Minimum 2:1 honours degree in a numerate subject such as engineering mathematics or physical sciences.

To thrive in this degree you’ll need to have excellent mathematical notation and basic computer programming skills. 

Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.

Pathway programme for international students

If you're an international student who does not meet the entry requirements for this course, you have the opportunity to apply for a pre-masters programme in Science and Engineering at the University of Sheffield International College. This course is designed to develop your English language and academic skills. Upon successful completion, you can progress to degree level study at the University of Sheffield.

We also accept a range of other UK qualifications and other EU/international qualifications.

If you have any questions about entry requirements, please contact the department.

Apply

You can apply for postgraduate study using our Postgraduate Online Application Form. It's a quick and easy process.

Apply now

Contact

pgtacse@sheffield.ac.uk
+44 114 222 5644

Any supervisors and research areas listed are indicative and may change before the start of the course.

Our student protection plan

Recognition of professional qualifications: from 1 January 2021, in order to have any UK professional qualifications recognised for work in an EU country across a number of regulated and other professions you need to apply to the host country for recognition. Read information from the UK government and the EU Regulated Professions Database.

Explore this course:

    Roderich Gross

    Our new MSc Robotics will provide you with the essential knowledge, understanding and skills that are needed for designing, implementing and deploying the robotics and autonomous systems (RAS) of the future. You will be inspired to think differently and create innovative solutions with the potential to change our lives.

    Roderich Gross
    Senior Lecturer in Robotics and Computational intelligence

    ACST17 Off Off