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Robotics MSc

Learn about the course below
Code
PGH671
Start
October 2023
Duration
1 year full-time
2 years part-time
Attendance
Full-time
Part-time
Fees
£10,500 (UK) *
£15,700 (EU/INT) *
Course leader
Dr Eris Chinellato
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Robots and autonomous systems are being introduced in virtually every industry. As new markets turn to robotics for the next step in their evolution, the need for qualified robotic engineers has never been greater.

Our Masters in Robotics blends practice with theory to equip you with the skills, knowledge and experience you’ll need for a career in robotics.

Why study MSc Robotics at Middlesex University?

Robotics research and the development of intelligent systems continue to be one of the key priorities set by both industry and the government. Significant growth is predicted in many robotics sectors. Our programme will provide you with both solid understanding of the fundamental theoretical principles of robotics and practical hands-on skills achieved through working directly with state-of-the-art equipment.

You’ll learn to program different types of robots, from manipulators to mobile robots to social robots, using industry standard hardware and software, such as Python and ROS. These skills and competences will prepare you for a career as a robotic engineer or academic researcher in the field.

The programme includes significant time developing practical projects, working under the supervision of our expert teaching staff, who are actively involved in industrial and academic activities in robotics and AI. You’ll also benefit from our close links to leading industry organisations, and direct access to new developments related to current research projects in which our staff are involved.

Course highlights

  • Direct personal access to advanced robotic equipment in our state-of-the-art facilities.
  • Focus on both industrial robotics and autonomous AI systems.
  • Contribute to the wide range of robotics research being carried out in the school.

Find out more

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What will you study on the MSc Robotics?

You will use a variety of industry standard and domestic robots, providing you with a breadth of experience using technologies such as industrial manipulators, multiple-arm collaborative robots, mobile platforms, social robots.

You’ll work with state-of-the-art sensors and actuators, and learn how to link and control them to build autonomous robotic systems. You’ll study AI and machine learning techniques and apply them to robotic applications. You’ll also learn to program different robotic systems through the appropriate environments (e.g. ROS, Python, MATLAB, TensorFlow) and acquire the key hardware and software skills requested by the robotics industry, enabling progression into more specialised areas of robotics, depending on your interests.

We’ll also teach you how to present your work to an academic or professional audience, through different means (reports, presentations, multimedia).

Modules

  • Modules

    • Mobile Robotics (15 credits) - Compulsory

      Mobile robots are widely used in dangerous and remote locations and are increasingly being introduced into everyday human environments (self-driving cars, autonomous delivery systems, UAVs). In this module you’ll study how such intelligent sensor-guided systems work, and you’ll learn to program them to achieve complex autonomous behaviours.

    • Robot Manipulation (15 credits) - Compulsory

      In this module you’ll learn use and program state of the art robot arms and end effectors, such as those employed in car production lines, CNC machines, medical research, pick and place operations. Such machines are generally mounted in fixed positions and can move with speed or with load carrying capability and precision.

    • Machine Learning for Robotics (15 credits) - Compulsory

      This module is designed to provide you with state-of-the-art knowledge of Machine Learning and Artificial Intelligence techniques that are widely used in robotics, to enable you to design your own intelligent robotic system. You’ll be able to evaluate ML and AI techniques used in robotics, and strategically apply and combine them into real robot applications.

    • Intelligent Sensing for Robotics (15 credits) - Compulsory

      This module explores advanced sensor solutions and sensing mechanisms, such as computer vision and tactile exploration, and how they are used in autonomous robots. You’ll learn to gather sensory data and employ appropriate techniques, including machine learning algorithm, for intelligent data processing in robotics.

    • Robot Control (30 credits) - Compulsory

      This module will introduce you to the sensors and actuators currently most used in robotic systems, and how these are programmed and controlled. Fundamental notions of control methods are enriched by projects performed with real hardware, showing the practical effects of various control strategies. The module will also introduce you to academic reading and writing for robotics research and development.

    • Robotic Systems Integration (30 credits) - Compulsory

      The module will review how the various hardware and software components of a robotic system can be joined and integrated. A range of different robot systems will be analysed and explained. In addition, through a group project coursework, the module provides you with the opportunity to develop their competence in undertaking projects through a systematic research and development process, using a formal project management approach.

    • Project (60 credits) - Compulsory

      The module is designed to consolidate the knowledge and skills you’ve gained in the preceding modules and provide you with the opportunity to develop and demonstrate mastery in undertaking advanced robotics projects in their future employment. You’ll display advanced skills and practical experience in planning, problem solving, and implementing robotics solutions and in making effective written and oral project presentations.

More information about this course

See the course specification for more information:

Optional modules are usually available at levels 5 and 6, although optional modules are not offered on every course. Where optional modules are available, you will be asked to make your choice during the previous academic year. If we have insufficient numbers of students interested in an optional module, or there are staffing changes which affect the teaching, it may not be offered. If an optional module will not run, we will advise you after the module selection period when numbers are confirmed, or at the earliest time that the programme team make the decision not to run the module, and help you choose an alternative module.

We are regularly reviewing and updating our programmes to ensure you have the best learning experience. We are thus enhancing our teaching methods with new and innovative ways of learning, and by following the most recent advancements in the field.

How is the MSc Robotics taught?

The course is taught through a series of practical lab sessions as well as self-directed study and project-based learning.

You’ll be taught how to use state of the art robots by experienced academic staff. In addition, there are technical tutors and Graduate Academic Assistants to support the individual student during and after formal class situations.

Assessment

There are no exams in the course, and assessment is based on a large and balanced variety of tasks and assignments, such as individual and group projects, coding and hardware implementations with live or recorded demos, reports, presentations, project proposals and literature reviews, logbooks and blogs.

Teaching and learning from 2022

After the disruptions to teaching and the necessary adjustments required by the pandemic, full time face to face teaching was reintroduced from the academic year 2022-23.

We have nevertheless kept some elements of teaching developed during the pandemic, where we think these can benefit students, and in case partial or total online teaching would have to be reinstated. These elements include the increased and more advanced use of Virtual Machines, the recording of important parts of certain classes, the variety of assessment methods, including video and blog submissions.

Learning structure: typical hourly breakdown in 2021/22

Live in-person on campus learning

Contact hours per week, per level:

6 hours

Live online learning

Average hours per week, per level:

6 hours

Support

You have a strong support network available to you to make sure you develop all the necessary academic skills you need to do well on your course.

Our support services will be delivered online and on campus and you have access to a range of different resources so you can get the help you need, whether you’re studying at home or have the opportunity to come to campus.

You have access to one to one and group sessions for personal learning and academic support from our library and IT teams, and our network of learning experts. Our teams will also be here to offer financial advice, and personal wellbeing, mental health and disability support.

  1. Standard entry requirements
  2. International (inc. EU)
  3. How to apply
  1. UK
  2. EU fees
  3. EU/International
  4. Additional costs
  5. Scholarships and bursaries

How can the MSc Robotics support your career?

Well-qualified graduates with a Masters in Robotics are in high demand and as a result, the career options available to our graduates are extensive. Robotics plays a large and increasing role in manufacturing and product handling, exploration, the office and the home, with products including: unmanned ground and air vehicles, automated warehousing and delivery solutions, autonomous robot cleaning and other household devices, semi-autonomous biomedical and assistive applications, toys and gaming, etc.

Graduates of the programme are well equipped for careers in a range of industries and SMEs, from advanced manufacturing and handling, to oil and gas exploration, nuclear energy to railways and automotive, healthcare to defence. Enrolment in PhD programs and pursuing further academic development and research is also a likely progression outcome.

Dr Eris Chinellato

Dr Eris Chinellato's expertise touches a number of different fields related to robotics and AI research, from grasping optimisation based on visual and tactile processing to computational neuroscience models applied to bio-inspired robotic systems. He teaches the Machine Learning and project modules.


We’ll carefully manage any future changes to courses, or the support and other services available to you, if these are necessary because of things like changes to government health and safety advice, or any changes to the law.

Any decisions will be taken in line with both external advice and the University’s Regulations which include information on this.

Our priority will always be to maintain academic standards and quality so that your learning outcomes are not affected by any adjustments that we may have to make.

At all times we’ll aim to keep you well informed of how we may need to respond to changing circumstances, and about support that we’ll provide to you.

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