Robotics is one of the most discussed topics in recent years; robots are becoming ubiquitous in industrial environments as well as in everyday life. However, as the adoption of robotic technology progressively rises, the skill shortage in robotic engineers will also widen accordingly. This Robotics MSc course will offer students the opportunity to gain practical robot programming experience. 

Overview

  • Start dateOctober
  • DurationOne year full-time, two-three years part-time
  • DeliveryTaught modules 40%, Group project 20%, Individual research project 40%
  • QualificationMSc
  • Study typeFull-time / Part-time
  • CampusCranfield campus

Who is it for?

As the demand for robotics engineer is increasing this course has been developed for graduates to equip themselves with the skills and knowledge required for associated careers. This course is suitable for those with essential engineering mathematics knowledge and basic computer programming skills.

A unique experience of the breadth of the field of robotics providing students with not only a broad understanding of their uses and applications in modern society but also the fundamental science behind them.


Why this course?

Robotics technologies are being increasingly adopted across various industries, these include automotive, oil and gas, aerospace and energy as well as potential significant future growth in the service robot domain. This course will improve the employment prospects of students by providing them with relevant theoretical knowledge and practical skills to become robotics engineers and experts in robotics, to meet the rising global demands. It is unique in its focus on human aspects supported by practical applications.

This masters course provides insight into multiple application domains for intelligent and autonomous robot systems including industry, hazardous environments, health care, domestic / assistive robotics and autonomous vehicles.

We are very well located for visiting part-time students from all over the world, and offer a range of library and support facilities to support your studies. This enables students from all over the world to complete this qualification whilst balancing work/life commitments.This MSc programme benefits from a wide range of cultural backgrounds which significantly enhances the learning experience for both staff and students.

Informed by Industry

The course is directed by an industrial advisory panel who meet twice a year to ensure that it provides the right mix of hands-on skills and up-to-date knowledge suitable for to the wide variety of applications that this field addresses.

A number of members also attend the annual student thesis presentations which take place at the end of July, a month or so before the end of the course. This provides a good opportunity for students to meet key employers.

Our industrial partner ABB Robotics will deliver practical workshops at their state-of-the-art Milton Keynes training facility.

Your teaching team

Cranfield University is a leader in Applied Mathematics and Computing applications, and you will be taught by leading academic staff.

The course also includes lectures by leading academics and industry specialists.

External speakers include Simon Turner of ABB Robotics who is highly experienced in delivering professional robot training.

Accreditation

Accreditation will be sought for the MSc in Robotics from the Institution of Mechanical Engineers (IMechE) and the Institution of Engineering and Technology (IET).

Course details

Eight one-week assessed modules, a group project and an individual project. Students are also supported in their learning and personal development through exposure to; industry seminars, group poster session, group discussions, group presentations, video demonstrations, case studies, laboratory experiments, coursework and project work. Students will receive hands-on experience with our range of conventional and collaborative robots located in the Aerospace Integration Research Centre - supporting practice workshops, student group projects and individual projects. You will participate in a study tour carried out at ABB Robotics in Milton Keynes where you will spend up to a week at our industrial partner ABB Robotics’ training centre receiving practical robot training.

The new MSc in Robotics will use standard teaching and assessment methods as well as technology enhanced teaching (TET) methods such as a Virtual Learning Environment (VLE) to support different learning styles. Theories and fundamental of robotics will be taught in both lecture and workshop formats where videos and technology demonstrators will be used as teaching aids. For example, a collaborative robot will be used in the teaching of Human-Robot Interaction and Virtual Reality technology will be used in teaching Digital Robotics. Lecture videos will be available on VLE to provide an interactive learning experience. Students will receive hands-on experience on programming industrial robots initially in a robot simulation lab, which follows by a practical robot-programming workshop using real industrial robot supported by ABB Robotics. The use of robotics technology will enable students to see robot engineering phenomena first-hand where they can test engineering principles and theories with real devices.





Group project

The group design project is intended to provide you with invaluable experience of delivering a project within an industry structured team. The project allows you to develop a range of skills including learning how to establish team member roles and responsibilities, project management, delivering technical presentations and gaining experience of working in teams that include members with a variety of expertise and often with members who are based remotely.

Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.

Individual project

The individual research project allows you to delve deeper into an area of specific interest. It is very common for industrial partners to put forward real world problems or areas of development as potential research thesis topics. For part-time students it is common that their research thesis is undertaken in collaboration with their place of work.

Assessment

Taught modules 40%, Group project 20%, Individual research project 40%

University Disclaimer

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory modules and (where applicable) some elective modules affiliated with this programme which ran in the academic year 2017–2018. There is no guarantee that these modules will run for 2018 entry. All modules are subject to change depending on your year of entry.

Compulsory modules
All the modules in the following list need to be taken as part of this course

Fundamentals of Robotics

Module Leader
  • Dr Gilbert Tang
Aim
    Robotics technologies are being increasingly adopted across various industries, these include automotive, oil and gas, aerospace and energy as well as potential significant future growth in the service robot domain. The aim of this module is to introduce students to different types of robots and their practical uses. Students will experience offline programming of industrial robot as well as hands on programming during a study tour on the last day of the module.
Syllabus
    • Introduction to Robotics and history of robots
    • Classification of robotic systems
    • Industrial Robots
    • Basic control of robots
    • Robot sensing
    • Robotic applications
    • Offline programming of industrial robot
    • Practical robot programming

Intended learning outcomes

On successful completion of this module a student should be able to:

1. Distinguish different types of robots across different domains, appraise their characteristics and examine their common applications.
2. Examine critical components of different robot systems and critique the functionalities and performance of different configurations.
3. Distinguish industrial robot programming methods and techniques, and construct robot procedures for automated operations.
4. Demonstrate a systematic approach in constructing an offline programme using professional robot simulation software package.
5. Develop an industrial robot programme and integrate onto a real robot to perform simple tasks.




Robotics Control

Module Leader
  • Seemal Asif
Aim
    This module aims to provide students with the fundamental knowledge for solving robot control problems that will be applicable in the design of robot control systems. The syllabus covers control theories that are essential for the control of robot manipulators as well as mobile robots.

Syllabus
     • Transformation of coordinates
    • Kinematics and inverse kinematics
    • Jacobians
    • Modelling Control, Proportional (P), Proportional-Integral (PI), Proportional-Integral-Derivative (PID) and Model Based Predictive Controller (MPC)
    • Feedback Control System
    • Motion and path planning
    • Collision avoidance and navigation


Intended learning outcomes

On successful completion of this module a student should be able to:

1. Examine a given control problem and appraise the suitability of a control system as a solution
2. Construct Forward Kinematic and Inverse Kinematic solutions for a Multi Degree of Freedom Robots
3. Design a feedback control system for solving a real world situation
4. Construct the path and motion planning of a robot manipulator for solving a practical task


Artificial Intelligence and Machine Learning for Robotics

Module Leader
  • Dr Antonios Antoniadis
Aim

    Artificial Intelligence and Machine Learning combined with increasing availability of large datasets are significant drivers for technological development of robots and autonomous systems, and they are being increasing utilised in new products and services.

    The aim of this module is to provide students with the necessary knowledge and understanding for the application of machine learning & artificial intelligence techniques to real world industrial problems within the domain of robotics and beyond.

Syllabus
    • Introduction to Machine Learning Theory Applications.
    • Decision tree modelling, logical reasoning.
    • Probability theory and Bayesian methods.
    • Classification methods and clustering techniques.
    • Bio-inspired artificial intelligence algorithms.
    • Reinforcement learning.
    • Case study for robotics applications.


Intended learning outcomes

On successful completion of this module a student should be able to:

1. Construct a wide range of machine learning techniques to solve industry problems particularly within the domain of robotics.
2. Appraise the application of machine learning approaches to a wider set of data mining and classification type problems.
3. Using a provided implementation, plan machine learning analysis on suitable forms of computer and robotics data.
4. Examine the concepts and operation of a range of machine learning algorithms in order to facilitate re-implementation in a software programming environment with which they are already familiar.
5. Develop programme in solving machine learning problems through interactive learning workshops.

Programming Methods for Robotics

Aim
    Object oriented programming (OOP) is the standard programming methodology used in nearly all fields of major software construction today, including engineering and science and C++ is one of the most heavily employed languages. OOP using C++ is also needed in a number of software tools, such as OpenCV in Machine Vision for Robotics or ROS in Digital Robotics, in order to program specific modules and further enhance their associated functionality. This module aims to answer the question ‘what is OOP’ and to provide the students with the understanding and skills necessary to write well designed and robust OO programs in C++. Students will learn how to write C++ code, starting from fundamental programming aspects and progressing through to advanced OOP. Hands-on programming sessions form an essential part of the module.

Syllabus
    • Programming concepts and their implementation
    • The OOP methodology, classes, abstraction and encapsulation.
    • Destructors and memory management.
    • Stream input and output.
    • Function and operator overloading.
    • Inheritance and aggregation.
    • Polymorphism and virtual functions.
    • Templates, Exception handling.
    • The C++ Standard Library and STL.


Intended learning outcomes On successful completion of this module a student should be able to:

1. Examine the principles of the object oriented programming methodology - abstraction, encapsulation, inheritance and aggregation – and implement in the development of C++ programs.
2. Create robust C++ programs of simple to moderate complexity given a suitable specification.
3. Develop C++ programs through implementation of the Standard Template Library .
4. Construct robust C++ programs using development environments and associated software engineering tools.

Human-Robot Interaction

Module Leader
  • Dr Gilbert Tang
Aim
    Human-robot interaction (HRI) is a relatively new topic that has gained popularity in recent years due to updates in safety legislations and advancement in interactive and collaborative technology. Human-robot interaction is becoming more common in social and domestic settings, and human-robot collaborative systems could be the solution to numerous industrial problems. However, the HRI must be designed appropriately to ensure high-level of usesability and seamless interaction. The aim of this module is to introduce students to human-robot interaction design and technology, and their applications. Students will learn about natural user interface and its applications in interaction. There will be opportunities to experience and practice hands-on programming of industrial collaborative robots to carry out basis tasks.

Syllabus
    • Introduction to Human-Robot Interaction
    • Human-Robot Interactive Systems
    • Interaction Design/ Collaboration and teamwork
    • Natural User Interface
    • Natural Language User Interface
    • Safe Human-Robot Interaction
    • Robot programming for collaborative tasks

Intended learning outcomes

On successful completion of this module a student should be able to:

1. Examine different types of HRI system and appraise fundamental HRI theory and principles in HRI systems design.
2. Differentiate different types of human-robot interface, distinguish their functionalities and investigate novel applications.
3. Implement HRI and safety principles to develop a safe HRI system that complies to current robot standards.
4. Appraise and implement intuitive user interfaces in enhancing the efficiency and seamlessness of the interaction between humans and robots.
5. Design and construct a robot programme for carrying out human-robot collaborative tasks

Machine Vision for Robotics

Module Leader
  • Dr Zeeshan Rana
Aim
    The most powerful method of sensing available to humans is vision. In computing and robotics visual information is represented as a digital image. In order to process visual information in computer systems we need to know about processing digital images. By processing visual information we can develop automated visual interpretation and understanding – artificial vision, itself a large part of wider field of the Artificial Intelligence. In order to achieve this we must be able to extract high-level visual information such as edges and regions from images and additionally allow for the efficient storage of large amounts of visual data which can then be used in robotics applications.

Syllabus
    • Image Applications
    • Image Representation
    • Image Capture Hardware
    • Image Sampling & Noise
    • Image Geometry & Locality, Processing Operations Upon Images
    • Camera Projection / Convolution Model
    • Image Transformation
    • Image Enhancement
    • Stereo Vision and Object Tracking
    • Case Study: Vision Based Metrology in Robotics
Intended learning outcomes

On successful completion of this module a student should be able to:

1. Appraise the applications of common digital image representations techniques in solving Machine Vision problems.
2. Demonstrate a systematic application of Local and Global Image Transformations, and Basic Image Feature extraction for image processing.
3. Construct computer programme for implementing Image processing in Frequency domain.
4. Construct computer programme for implementing counter noise in digital images.
5. Analyse and appraise the robotics applications of three dimensional Stereo vision based systems and Object Tracking.






Autonomy in Robotic Systems

Module Leader
  • Professor Antonios Tsourdos
Aim
    The aim of this module is to introduce the students to the algorithms suitable for real life problems concerning autonomy in robotics: path planning, task allocation, robotic perception, mapping and navigation, cooperative robotics, including accuracy assessment and uncertainty reduction for these applications.
Syllabus
    • Introduction to autonomy aspects (1 lecture)
    • Perception and sensing technologies (4 lectures)
    • Sensor fusion algorithms and architectures (3 lectures)
    • Autonomy in Robotics: learning and reactive paradigms (3 lectures)
    • Autonomy in Robotics: Multi-agents problem (3 lectures)
    • Navigation: path planning (4 lectures)
    • Navigation: localization and mapping (4 lectures)

Intended learning outcomes

On successful completion of this module a student should be able to:

1) Examine fundamental meaning and appraise the applicability of AI methods for robotics with multiple degrees of autonomy.
2) Examine commonly used AI algorithms and develop solutions to practical examples in context of the autonomous robotics.
3) Appraise suitable methods for autonomy in common robotics applications and analyse their performance in real-life scenarios.
4) Develop and enhance the level of autonomy in robotic systems through implementation of AI algorithms, and critique the performance of the algorithm in a simulated environment.



Psychology, Ethics and Standards

Module Leader
  • Dr Sarah Fletcher
Aim
    As robots and robotic devices are increasingly becoming part of our day-to-day lives it is vital that we know how to effectively integrate them with people new advanced systems. This module explores the changing landscape of robotics in society and how we comply with evolving demands and perspectives of ethics and safety standards. With a focus on fundamental human factors and psychological principles we examine how to optimise the integration of people with different types of robotic systems and environments. Students will be given the opportunity to apply practical human analysis tools and techniques that complement traditional engineering approaches to enhance usability and performance in the design of safe human-robot interaction.


Syllabus
    • Fundamental psychology
    • Human performance and error
    • Social cognition and behaviour
    • HCI and user-centred design
    • Safety standards and ethics
    • Research methods
    • Research practicals


Intended learning outcomes On successful completion of this module a student should be able to:

1. Examine how humans receive, process and utilise information in their interactions with robot systems
2. Analyse human factors affecting system performance and
identify impacts from the surrounding environment on human-robot interaction
3. Appraise the design of systems using a user-centred approach
4. Interpret requirements of current legislation and safety standards for the design of human-robot systems and understand key ethical principles
5. Select and apply appropriate methods for analysing the design of human-robot systems and interactions across contexts




Fees and funding

MSc Full-time £10,000
MSc Part-time £10,000 *
  • * Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A non-refundable deposit is payable on offer acceptances and will be deducted from your overall tuition fee.  Home/EU Students will pay a £500 deposit.  Overseas Students will pay a £1,000 deposit.
  • Additional fees for extensions to the agreed registration period may be charged.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.
MSc Full-time £20,000
MSc Part-time £20,000 *
  • * Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A non-refundable deposit is payable on offer acceptances and will be deducted from your overall tuition fee.  Home/EU Students will pay a £500 deposit.  Overseas Students will pay a £1,000 deposit.
  • Additional fees for extensions to the agreed registration period may be charged.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.

Funding Opportunities

To help students find and secure appropriate funding, we have created a funding finder where you can search for suitable sources of funding by filtering the results to suit your needs. Visit the funding finder.

Postgraduate Loan from Student Finance England
A Postgraduate Loan is now available for UK and EU applicants to help you pay for your Master’s course. You can apply for a loan at GOV.UK

Santander MSc Scholarship
The Santander Scholarship at Cranfield University is worth £5,000 towards tuition fees for full-time master's courses. Check the scholarship page to find out if you are from an eligible Santander Universities programme country.

Chevening Scholarships
Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at Cranfield university. The scholarship includes tuition fees, travel and monthly stipend for Master’s study.

Cranfield Postgraduate Loan Scheme (CPLS)
The Cranfield Postgraduate Loan Scheme (CPLS) is a funding programme providing affordable tuition fee and maintenance loans for full-time UK/EU students studying technology-based MSc courses.

Commonwealth Scholarships for Developing Countries
Students from developing countries who would not otherwise be able to study in the UK can apply for a Commonwealth Scholarship which includes tuition fees, travel and monthly stipend for Master’s study.

Future Finance Student Loans
Future Finance offer student loans of up to £40,000 that can cover living costs and tuition fees for all student at Cranfield University.

Entry requirements

A first or second class UK Honours degree (or equivalent), in Aeronautics/ Aerospace Engineering, Mechanical Engineering, Electrical/ Electronic Engineering, Pure mathematics, Computer Science, Software Engineering, Mechatronic Engineering, Information Technology, or be applying as part of a recognised double-degree programme with their home EU institution. Applications from candidates with lesser qualifications but with considerable relevant work experience will be considered.

Applicants who do not fulfil the standard entry requirements can apply for the Pre-Masters programme, successful completion of which will qualify them for entry to this course for a second year of study.

English Language

If you are an international student you will need to provide evidence that you have achieved a satisfactory test result in an English qualification. Our minimum requirements are as follows:

IELTS Academic – 7
TOEFL – 100
Pearson PTE Academic - 68
Cambridge English Scale – 190
Cambridge English: Advanced - C
Cambridge English: Proficiency – C

In addition to these minimum scores you are also expected to achieve a balanced score across all elements of the test. We reserve the right to reject any test score if any one element of the test score is too low.

We can only accept tests taken within two years of your registration date (with the exception of Cambridge English tests which have no expiry date).

Students requiring a Tier 4 (General) visa must ensure they can meet the English language requirements set out by UK Visas and Immigration (UKVI) and we recommend booking a IELTS for UKVI test.

Applicants who do not already meet the English language entry requirement for their chosen Cranfield course can apply to attend one of our Presessional English for Academic Purposes (EAP) courses. We offer Winter/Spring and Summer programmes each year to offer holders.

Your career

The MSc in Robotics is designed to equip you with the skills required to pursue a successful career working in the UK and overseas.

The International Federation of Robotics’ Executive Summary report shows that the deployment of industrial robots had constantly increased in the last decade and it is predicted that global robot installations will increase by at least 15% annually in the next 3 years. Mike Wilson, the President of British Automation and Robot Association, has highlighted that robotics is one of the key technologies in ensuring UK’s manufacturing can be as competitive and productive as possible and the UK needs to address skill pipeline issues in order to meet the skills that are required by the industry going forward. According to the US Bureau of Labor Statistics (BLS), the mechanical engineering field - which includes robotics engineers - was projected to experience five percent employment growth over ten years to 2022. It is important to recognise these increasing needs which will lead to a high demand for highly trained robotic engineers.

Applying

Online application form. UK students are normally expected to attend an interview and financial support is best discussed at this time. Overseas and EU students may be interviewed by telephone.

Apply now