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.
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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.
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.
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.
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.
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.
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.
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.
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 taking what we've learnt in recent years by enhancing our teaching methods with new and innovative ways of learning.
We have developed new approaches to teaching and learning for the 2021/22 academic year.
We are currently reviewing our approach to teaching and learning for 2022 entry and beyond. We've learned a lot about how to give you a quality education - we aim to combine the best of our in-person teaching and learning with access to online learning and digital resources which put you more in charge of when and how you study. We will keep you updated on this throughout the application process.
Your timetable will be built around on campus sessions using our professional facilities, with online sessions for some activities where we know being virtual will add value. We’ll use technology to enhance all of your learning and give you access to online resources to use in your own time.
The table below gives you an idea of what learning looks like across a typical week. Some weeks are different due to how we schedule classes and arrange on campus sessions.
This information is likely to change slightly for 2022 entry as our plans evolve. You'll receive full information on your teaching before you start your course.
Learning structure: typical hourly breakdown in 2021/22
Live in-person on campus learning
Contact hours per week, per level:
Live online learning
Average hours per week, per level:
Outside of these hours, you’ll be expected to do independent study where you read, listen and reflect on other learning activities. This can include preparation for future classes. In a year, you’ll typically be expected to commit 1200 hours to your course across all styles of learning. If you are taking a placement, you might have some additional hours.
Definitions of terms
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.
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'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.
Start: October 2022
Duration: 1 year full-time, 2 years part-time
Start: October 2022, EU/INT induction: September 2022
Duration: 1 year full-time
Code: MA: PGW280, MSc: PGW281
Start: October 2022, September 2022 (EU/INT induction)
Duration: 1 year full-time, 2 years part-time