The MSc Robotics and Artificial Intelligence is designed to equip students with the advanced knowledge and skills needed to develop the innovative solutions required by the emerging global industry in Robotics and AI, and across many other sectors where robotics and AI skills are applicable. These may include robotics and AI in agriculture, food processing, transport, logistics, manufacturing, healthcare, and energy.
The MSc ranges from mechatronics through programming and algorithms for robot control and automation with AI, including details of modern deep learning and large language models (i.e. how chatbots such as ChatGPT work), robots as physical AI agents, as well as classical and probabilistic AI approaches to robotics perception, navigation, and reasoning. Industry standard tools such as Python, ROS2, and PyTorch are used throughout.
The programme aims to prepare students to work in a research and development capacity, such as in industrial robotics and AI companies and academic PhD study. 色中色 hosts the UK's - and one of the world's - largest concentration of agricultural robotics researchers, and is a major hub of UK agribusiness. Many students choose to specialise in this area, including by collaborating with local companies who have existing R&D relationships with our research. Course content is informed by research carried out at the University of 色中色, especially in the 色中色 Centre for Autonomous Systems. This aims to ensure that content remains consistently underpinned by the latest thinking.
The programme is an extension Master's. It assumes that students will have already completed a computer science or similar technology-based degree, and will want to extend that knowledge in depth and with specialist focus on Robotics and AI. Students have the chance to enhance and apply existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates, and independent research. The course assumes a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain.
The MSc Robotics and Artificial Intelligence is designed to equip students with the advanced knowledge and skills needed to develop the innovative solutions required by the emerging global industry in Robotics and AI, and across many other sectors where robotics and AI skills are applicable. These may include robotics and AI in agriculture, food processing, transport, logistics, manufacturing, healthcare, and energy.
The MSc ranges from mechatronics through programming and algorithms for robot control and automation with AI, including details of modern deep learning and large language models (i.e. how chatbots such as ChatGPT work), robots as physical AI agents, as well as classical and probabilistic AI approaches to robotics perception, navigation, and reasoning. Industry standard tools such as Python, ROS2, and PyTorch are used throughout.
The programme aims to prepare students to work in a research and development capacity, such as in industrial robotics and AI companies and academic PhD study. 色中色 hosts the UK's - and one of the world's - largest concentration of agricultural robotics researchers, and is a major hub of UK agribusiness. Many students choose to specialise in this area, including by collaborating with local companies who have existing R&D relationships with our research. Course content is informed by research carried out at the University of 色中色, especially in the 色中色 Centre for Autonomous Systems. This aims to ensure that content remains consistently underpinned by the latest thinking.
The programme is an extension Master's. It assumes that students will have already completed a computer science or similar technology-based degree, and will want to extend that knowledge in depth and with specialist focus on Robotics and AI. Students have the chance to enhance and apply existing knowledge of computer programming and mathematical frameworks through laboratory workshops, lectures, debates, and independent research. The course assumes a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain.
Extend your existing knowledge through this extension Master's
Develop advanced knowledge and skills needed to develop innovative solutions
Informed by the research of academic teams at 色中色
Complete an independent research project in a specialist area
Students on this programme can experience a blend of different teaching and learning approaches. The programme aims to enable the development of skills through practical workshops in the laboratory, and academic knowledge through debate, lectures, discussion, and personal research.
Modules assume a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain. Each module typically consists of 12 weeks of study. This time includes a supporting lecture programme, a series of supported laboratory sessions, and time for the completion of assignment exercises and examinations. Weekly contact hours on this programme may vary depending on the individual module options chosen and the stage of study. The programme is also supported by online access to lecture material and related information.
Postgraduate level study involves a significant proportion of independent study, exploring the material covered in lectures and seminars. As a general guide, for every hour spent in class, students are expected to spend at least two to three hours in independent study.
Students on this programme can experience a blend of different teaching and learning approaches. The programme aims to enable the development of skills through practical workshops in the laboratory, and academic knowledge through debate, lectures, discussion, and personal research.
Modules assume a familiarity with programming concepts and the supporting mathematical framework, while presenting advanced concepts relating specifically to the computing domain. Each module typically consists of 12 weeks of study. This time includes a supporting lecture programme, a series of supported laboratory sessions, and time for the completion of assignment exercises and examinations. Weekly contact hours on this programme may vary depending on the individual module options chosen and the stage of study. The programme is also supported by online access to lecture material and related information.
Postgraduate level study involves a significant proportion of independent study, exploring the material covered in lectures and seminars. As a general guide, for every hour spent in class, students are expected to spend at least two to three hours in independent study.
Join Dr Charles Fox, Senior Lecturer in Computer Science, for this one-off lecture where he discusses the many ways AI is being fused with robotics.
This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.
This module aims to cover the theoretical fundamentals and practical application of machine learning algorithms, including supervised, unsupervised, reinforcement and evolutionary learning. Practical programming exercises complement and apply the theoretical knowledge acquired to real-world problems such as data mining.
This module focuses on advanced concepts in robotics. Students are introduced to navigation and state estimation for mobile robots and discuss optimality principles and relevant algorithms for path planning, trajectory optimisation and control for robot manipulators. In the second part of the module, there will be a discussion of data-driven approaches that can learn from human teachers and interaction with the environment. To deepen the understanding of the introduced mathematical concepts, practical examples will be discussed in the lectures as well as implemented in the workshops.
This module aims to explore current methodologies in the field of computer vision, covering a range of aspects in capturing, processing, analysing and interpreting rich visual content.
The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in computer vision, equipping them with knowledge in practical depth. The module will also provide the opportunity for training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of computer vision systems.
The module will also cover applications of computer vision in various fields, such as in object recognition/tracking, medical image analysis, multimedia indexing and retrieval and intelligent surveillance systems, allowing the students the opportunity to establish a full awareness to the technology advance in this rapidly evolving field.
This module introduces the mathematical and practical foundations of robotics which underlie most advanced systems. Mathematical foundations include relevant engineering mathematics, dynamics and kinematics, probability and elementary control, while practice includes understanding sensors and actuators used in real-world systems.
This module introduces cutting-edge topics in robotics and autonomous systems research areas, including both theory and practical applications. The module will follow a research seminar format, involving input from colleagues across the School of Computer Science and other Schools at 色中色. Additionally, guest lectures from industry representatives and leading international researchers will be offered. Industrial applications such as robotics for agriculture and food production will naturally be covered as part of this module. Students will further benefit from opportunities to discuss potential research topics that they can explore to build and enhance their research and critical thinking skills.
This module is designed to cover the fundamental skills and background knowledge that students need to undertake research related to the title of the award being studied, including: surveying literature; selecting and justifying a research topic; planning of research; selection of appropriate research methods; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations.
This module presents students with the opportunity to carry out a significant inquiry-driven research project, focusing on a topical area of interest that is aligned with their programme of study. This is primarily realised through the development of a dissertation and substantive research and/or software implementation output.
The research project is an individual piece of work, which enables students to apply and integrate elements of study from a range of modules, centred on a specific research question. The student will undertake work that is relevant to the ongoing research in either one of the established research centres within the School of Computer Science or through the development of a project concept in consultation with their allocated academic supervisor.
This module focuses on practical and aspects of software development and engineering for robotics. It aims to equip students with an in-depth understanding of the specific programming requirements in the domain, such as (soft-) real time processing, coordination & orchestration of robotics systems and different communication paradigms of integrated robotic systems.
Students can engage in practical assignments, programming robots in simulation and the real world. Different components of robotic systems (examples comprise perception, localisation, path planning, mapping, search & learning) will be taught and appraised, facilitated by lectures and guided learning in workshops. Students have the chance to develop and understanding of the fundamentals of robotic frameworks and middlewares, enabling them to program and orchestrate complex robotic systems in practice.
Students may have the opportunity to work on tasks informed by state-of-the-art robotics research challenges and competitions. Where feasible, students will be given the opportunity to work towards specific tasks in such internationally recognised challenges, with the potential to qualify for participation.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
This module aims to cover the theoretical fundamentals and practical applications of decision-making, problem-solving and learning abilities in software agents.
Search is introduced as a unifying framework for Artificial Intelligence (AI), followed by key topics including blind and informed search algorithms, planning and reasoning, both with certain and uncertain (e.g. probabilistic) knowledge. Practical exercises in AI programming will complement and apply the theoretical knowledge acquired to real-world problems.
This module aims to cover the theoretical fundamentals and practical application of machine learning algorithms, including supervised, unsupervised, reinforcement and evolutionary learning. Practical programming exercises complement and apply the theoretical knowledge acquired to real-world problems such as data mining.
This module focuses on advanced concepts in robotics. Students are introduced to navigation and state estimation for mobile robots and discuss optimality principles and relevant algorithms for path planning, trajectory optimisation and control for robot manipulators. In the second part of the module, there will be a discussion of data-driven approaches that can learn from human teachers and interaction with the environment. To deepen the understanding of the introduced mathematical concepts, practical examples will be discussed in the lectures as well as implemented in the workshops.
This module aims to explore current methodologies in the field of computer vision, covering a range of aspects in capturing, processing, analysing and interpreting rich visual content.
The aim is to offer students with a deep understanding and to allow an exposure to the latest developments in computer vision, equipping them with knowledge in practical depth. The module will also provide the opportunity for training in programming skills (e.g. Matlab), tools and methods that are necessary for the implementation of computer vision systems.
The module will also cover applications of computer vision in various fields, such as in object recognition/tracking, medical image analysis, multimedia indexing and retrieval and intelligent surveillance systems, allowing the students the opportunity to establish a full awareness to the technology advance in this rapidly evolving field.
This module introduces the mathematical and practical foundations of robotics which underlie most advanced systems. Mathematical foundations include relevant engineering mathematics, dynamics and kinematics, probability and elementary control, while practice includes understanding sensors and actuators used in real-world systems.
This module introduces cutting-edge topics in robotics and autonomous systems research areas, including both theory and practical applications. The module will follow a research seminar format, involving input from colleagues across the School of Computer Science and other Schools at 色中色. Additionally, guest lectures from industry representatives and leading international researchers will be offered. Industrial applications such as robotics for agriculture and food production will naturally be covered as part of this module. Students will further benefit from opportunities to discuss potential research topics that they can explore to build and enhance their research and critical thinking skills.
This module is designed to cover the fundamental skills and background knowledge that students need to undertake research related to the title of the award being studied, including: surveying literature; selecting and justifying a research topic; planning of research; selection of appropriate research methods; evaluation of research; presentation and reporting of research; and legal, social, ethical and professional considerations.
This module presents students with the opportunity to carry out a significant inquiry-driven research project, focusing on a topical area of interest that is aligned with their programme of study. This is primarily realised through the development of a dissertation and substantive research and/or software implementation output.
The research project is an individual piece of work, which enables students to apply and integrate elements of study from a range of modules, centred on a specific research question. The student will undertake work that is relevant to the ongoing research in either one of the established research centres within the School of Computer Science or through the development of a project concept in consultation with their allocated academic supervisor.
This module focuses on practical and aspects of software development and engineering for robotics. It aims to equip students with an in-depth understanding of the specific programming requirements in the domain, such as (soft-) real time processing, coordination & orchestration of robotics systems and different communication paradigms of integrated robotic systems.
Students can engage in practical assignments, programming robots in simulation and the real world. Different components of robotic systems (examples comprise perception, localisation, path planning, mapping, search & learning) will be taught and appraised, facilitated by lectures and guided learning in workshops. Students have the chance to develop and understanding of the fundamentals of robotic frameworks and middlewares, enabling them to program and orchestrate complex robotic systems in practice.
Students may have the opportunity to work on tasks informed by state-of-the-art robotics research challenges and competitions. Where feasible, students will be given the opportunity to work towards specific tasks in such internationally recognised challenges, with the potential to qualify for participation.
† Some courses may offer optional modules. The availability of optional modules may vary from year to year and will be subject to minimum student numbers being achieved. This means that the availability of specific optional modules cannot be guaranteed. Optional module selection may also be affected by staff availability.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
We want you to have all the information you need to make an informed decision on where and what you want to study. In addition to the information provided on this course page, our What You Need to Know page offers explanations on key topics including programme validation/revalidation, additional costs, and contact hours.
The programme is assessed through a variety of means, including in-class tests, coursework, projects, and examinations. The majority of assessments are coursework-based, reflecting the practical and applied nature of computer science. The final stage research project enables students to further specialise and complete a piece of work of significant complexity.
The programme is assessed through a variety of means, including in-class tests, coursework, projects, and examinations. The majority of assessments are coursework-based, reflecting the practical and applied nature of computer science. The final stage research project enables students to further specialise and complete a piece of work of significant complexity.
Our MSc students often publish papers for robotics conferences and in journals during their studies, in collaboration with their lecturers and other researchers at 色中色. This style of learning is known as 'student as producer'.
Here are some recent examples with student names in bold, including links to the PDF publications, and some with video demonstrations. Getting a publication is often a key requirement for obtaining a funded PhD place or industry research and development job.
J Swindell, M Darbyshire, M. Popovi膰, R. Polvara. . Proc. Intelligent Autonomous Systems, 2025. (Winner, best student paper award)
Heselden JR, Paparas D, Stevenson RL, Das GP. Machines. 2025; 13(1):2.
L Zhou, O Sinavski, A Polydoros. . IEEE International Conference on Robotic Computing, 2024.
R Stevenson, D Paparas, O Faris, X Xu, C Merchant, E Smith, B Nicholls, C Fox. . TAROS2024
L Zhou, O Ali, EA Soumo, E Attenborough, J Swindell, G Davies, C Fox. 3D . TAROS2024.
A Bora and H Cuayáhuitl. . Mach. Learn. Knowl. Extr. 6(4), 2355-2374, 2024.
K Gaikwad, R Soni, C Fox, C Waltham. . TAROS2023
R Trimble, C Fox. . TAROS2023
SJ Carter, NC Tsagkopoulos, G Clawson, C Fox. . Journal of Open Hardware 7 (1), 9, 2023. ()
F Camara, C Waltham, G Churchill, C Fox. . Journal of Open Hardware, 2023 (
J Davy, C Fox. . TAROS 2023 ()
G Clawson. . Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
E Alabi, F Camara, C Fox. . TAROS2023.
Perrett, A., Pollard, H., Barnes, C., Schofield, M., Qie, L., Bosilj, P., & Brown, J. M. (2023). . Computers, Environment and Urban Systems, 102, 101968.
V Wichitwechkarn, C Fox. 7 (1), 1-13, 2023 ()
K Gaikwad, R Soni, C Fox, C Waltham. . TAROS2023
G Clawson. . Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
E Alabi, F Camara, C Fox. . TAROS2023.
Perrett, A., Pollard, H., Barnes, C., Schofield, M., Qie, L., Bosilj, P., & Brown, J. M. (2023). . Computers, Environment and Urban Systems, 102, 101968.
R Trimble, C Fox. . TAROS2023
G Clawson, C Fox. . UKRAS 2022
J Bennett, B Moncur, K Fogarty, G Clawson, and Charles Fox. . ICMC, 2022 ()
G Clawson. . Proceedings of the 5th UK-RAS Conference 2022
J Stevenson, C Fox. . Proc. Biomimetic and Biohybrid Systems (Living Machines) 2022
H Rogers, B Dawson, G Clawson, C Fox. . Oxford AIMS Conference 2021
A Henry, C Fox. ICMC 2021 ()
Heiwolt, K, Mandil, W, Cielniak, G and Hanheide, M (2020) A UKRAS20
H Rogers, C Fox. An open source seeding agri-robot Proceedings of The 3rd UK-RAS Conference, 2020 ()
Millard, A, Ravikanna, R, Groß, R, and Chesmore, D (2019) , TAROS2019.
Robot Whiskers
Our students present an open source hardware (OSH) design and build a robotic whisker sensing system
Hear from Ayaan, a MSc Robotics and Autonomous Systems student about his time on the course and what you can look forward to if you join the programme.
Technical resources available to Robotics and AI students include computer labs, GPUs, a mechatronics fablab, and robot labs including fleet of diverse mobile and social robots, advanced compliant robotic manipulators, and state-of-the-art agricultural robots.
Postgraduate Application Support
Applying for a postgraduate programme at 色中色 is easy. Find out more about the application process and what you'll need to complete on our How to Apply page. Here, you'll also be able to find out more about the entry requirements we accept and how to contact us for dedicated support during the process.
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An informal interview by video call with the Programme Leader may also be required to make sure candidates have the right background for the course. This informal contact may also include requests for samples of self-directed project work involving a significant element of software and/or systems development.
There are two requirements and students will need to provide evidence of both of them in their application:
(1) A first or upper second class honours degree in computer science or a related discipline. This could include engineering, mathematics, or other numerate science and technology subjects.
(2) Competence in computer programming, roughly to the level of being able to write a basic video game such as Pong in any language. Acceptable forms of evidence of this skill to include in your application include, but are not limited to: (a) academic degree transcript showing 2:1 level scores in two or more programming classes; (b) a copy of a university, employment, or hobby project report detailing programming work; (c) a link to a source code site such as gitlab or github containing samples of your code. (d) a certificate of completion of an online programming course and exam such as https://www.udemy.com/course/the-complete-python-developer-certification-course/ or https://www.udemy.com/course/learn-basics-of-c/
If you have a good numerate degree but no programming experience then you may be able to satisfy the requirements by self-studying programming and passing a programming test online, such as through the above links. This may take a few weeks or months of part-time study depending on your previous knowledge. It is quite common for students to apply in this way.
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications:
/studywithus/internationalstudents/entryrequirementsandyourcountry/
Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page:
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-session English and Academic Study Skills courses. These specialist courses are designed to help students meet the English language requirements for their intended programme of study:
Please note application assessment criteria may vary by country and we may close to applications from some domiciles. Please view the Your Country pages of our website before making an application.
There are two requirements and students will need to provide evidence of both of them in their application:
(1) A first or upper second class honours degree in computer science or a related discipline. This could include engineering, mathematics, or other numerate science and technology subjects.
(2) Competence in computer programming, roughly to the level of being able to write a basic video game such as Pong in any language. Acceptable forms of evidence of this skill to include in your application include, but are not limited to: (a) academic degree transcript showing 2:1 level scores in two or more programming classes; (b) a copy of a university, employment, or hobby project report detailing programming work; (c) a link to a source code site such as gitlab or github containing samples of your code. (d) a certificate of completion of an online programming course and exam such as https://www.udemy.com/course/the-complete-python-developer-certification-course/ or https://www.udemy.com/course/learn-basics-of-c/
If you have a good numerate degree but no programming experience then you may be able to satisfy the requirements by self-studying programming and passing a programming test online, such as through the above links. This may take a few weeks or months of part-time study depending on your previous knowledge. It is quite common for students to apply in this way.
If you have studied outside of the UK, and are unsure whether your qualification meets the above requirements, please visit our country pages for information on equivalent qualifications:
/studywithus/internationalstudents/entryrequirementsandyourcountry/
Overseas students will be required to demonstrate English language proficiency equivalent to IELTS 6.0 overall, with a minimum of 5.5 in each element. For information regarding other English language qualifications we accept, please visit the English Requirements page:
If you do not meet the above IELTS requirements, you may be able to take part in one of our Pre-session English and Academic Study Skills courses. These specialist courses are designed to help students meet the English language requirements for their intended programme of study:
Please note application assessment criteria may vary by country and we may close to applications from some domiciles. Please view the Your Country pages of our website before making an application.
You will need to have funding in place for your studies before you arrive at the University. Our fees vary depending on the course, mode of study, and whether you are a UK or international student. You can view the breakdown of fees for this programme below.
The University offers a range of merit-based, subject-specific, and country-focused scholarships for UK and international students. To help support students from outside of the UK, we offer a number of international scholarships which range from 拢1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
You will need to have funding in place for your studies before you arrive at the University. Our fees vary depending on the course, mode of study, and whether you are a UK or international student. You can view the breakdown of fees for this programme below.
The University offers a range of merit-based, subject-specific, and country-focused scholarships for UK and international students. To help support students from outside of the UK, we offer a number of international scholarships which range from 拢1,000 up to the value of 50 per cent of tuition fees. For full details and information about eligibility, visit our scholarships and bursaries pages.
Postgraduate Funding Options
Find out more about the optional available to support your postgraduate study, from Master's Loans to scholarship opportunities. You can also find out more about how to pay your fees and access support from our helpful advisors.
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For more information about this course, please contact the Programme Leader.
Dr Charles Fox is a researcher in artificial intelligence, robotics, and cognitive science, with a particular focus on neural computing and Bayesian models. His work spans applications such as autonomous agricultural robotics, human interaction with self-driving vehicles, and geographic data analytics. He holds degrees from the University of Cambridge, the University of Edinburgh, and a DPhil from the University of Oxford, and has held roles in industry and academia including high-frequency trading and research positions in robotics and autonomous systems.
Dr Fox is an award-winning educator, recognised with multiple teaching honours including the University of 色中色’s Teaching Excellence Award and the 色中色 Students’ Union Inspirational Teacher Award. His students have achieved significant success, earning national awards and producing high-impact research publications across undergraduate and postgraduate levels.
Dr Charles Fox
chfox@lincoln.ac.uk
To get a real feel for what it is like to study at the University of 色中色, we hold a number of dedicated postgraduate events and activities throughout the year for you to take part in.
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