Autonomous Systems and Robotics Group

Autonomous Systems and Robotics is a cutting-edge degree programme offered by the University of Sheffield, designed to equip students with the essential knowledge and practical skills required to develop intelligent systems and autonomous machines. This interdisciplinary programme combines engineering, computer science, control systems, and artificial intelligence to prepare graduates for the rapidly evolving field of autonomous technologies. Throughout the course, students will explore core topics such as robotics, sensor integration, machine learning, control algorithms, and autonomous navigation, gaining a comprehensive understanding of how autonomous systems operate and interact within complex environments. The programme emphasizes hands-on experience through laboratory work, project-based learning, and collaborations with industry partners, enabling students to solve real-world problems related to autonomous vehicles, drones, robotic assistants, and other intelligent systems. Students will also study the ethical, societal, and safety considerations associated with deploying autonomous technologies, ensuring they are equipped to develop responsible and sustainable solutions. The curriculum is designed to be flexible, allowing students to specialize in particular areas such as computer vision, machine learning, or control engineering, according to their interests and career goals. Graduates of this programme will be well-prepared for careers in industries such as aerospace, automotive, defense, robotics manufacturing, and research and development, where autonomous systems are increasingly vital. The University of Sheffield's strong links with industry and research institutions provide students with valuable networking opportunities, internships, and exposure to the latest technological advancements. By completing this programme, students will gain the skills needed to design, develop, and deploy autonomous systems that can operate safely and efficiently across various applications, contributing to innovation in a world where automation is transforming the way we live and work.

• Robotics, Biomechatronics and Control (Supervisor: Dr Anderson)
• Robotic Implants to Control Body Functions (Supervisor: Dr Damian)
• Active Wearables for Efficient Living (Supervisor:Dr Damian)
• Autonomous Systems for Inspection and Condition Monitoring (Supervisor: Professor Dodd)
• Advanced Manufacturing (Supervisor: Professor Dodd)
• Future Air Transport (Supervisor: Professor Dodd)
• Modular reconfigurable robotic systems (Supervisor: Dr Gross)
• Evolutionary robotics and artificial life (Supervisor: Dr Gross)
• Advances in swarm robotics and multi-robot systems (Supervisor: Dr Gross)
• Novel swarm systems (Supervisor: Dr Gross)
• Tracking and Modelling of Cell Dynamics with Application to Swarm Robots (Supervisor: Professor Kadirkamanathan)
• Sequential Monte Carlo Methods for Bayesian Inference in Complex Systems (Supervisor: Dr Mihaylova)
• Multiple Object Tracking and Decision Making (Supervisor: Dr Mihaylova)
• Wireless Sensor Networks for Localisation in Indoor and Outdoor Environments (Supervisor: Dr Mihaylova)
• Automatic Object and Behaviour Recognition in Video/ Image Sequences (Supervisor: Dr Mihaylova)
• Vehicular Traffic Flow Modelling, Prediction and Control (Supervisor: Dr Mihaylova)
• Multi-Sensor Data Fusion and Smart Decision Making (Supervisor: Dr Mihaylova)
• Active control of noise and vibration (Supervisor: Dr Tokhi)
• Control of flexible manoeuvring systems (Supervisor: Dr Tokhi)
• Swarm intelligence optimisation techniques (Supervisor: Dr Tokhi)
• Adaptive/intelligent computing and control (Supervisor: Dr Tokhi)
• Assistive robotics (Supervisor: Dr Tokhi)
• Mobile service robotics (Supervisor: Dr Tokhi)
• High-performance real-time computing (Supervisor: Dr Tokhi)
• Reliable Response and Behaviour of Autonomous Robots (Supervisor: Professor Veres)
• Cooperative Behaviour of Autonomous Unmanned Vehicles (Supervisor: Professor Veres)
• Portable Agent Software Architecture for Robot Control (Supervisor: Professor Veres)

Requirements

• A good Master's degree, or a first class Honours degree or equivalent, from an approved institution in an appropriate Engineering or Science subject is normally required for entry. Applicants with other qualifications or experience are encouraged to contact the Research Admissions Tutor
• IELTS 6.5 (with at least 6 in each component) / TOEFL 88+
• Draft your PhD research project proposal
• Proof of your previous qualifications.
• Academic references (Two).
• English language certificate (EU and Overseas applicants).
• A supporting statement.
• Curriculum vitae/Resume.

Want to improve your English level for admission?

Prepare for the program requirements with English Online by the British Council.

• ✔️ Flexible study schedule
• ✔️ Experienced teachers
• ✔️ Certificate upon completion

📘 Recommended for students with an IELTS level of 6.0 or below.

Enroll in the course

Scholarships

• EPSRC Doctoral Training Account (DTA) awards 
• Departmental Fee Scholarships
• Departmental Prize Scholarships 
• Departmental Supervisor Scholarship

The MSc in Autonomous Systems and Robotics at the University of Sheffield is a comprehensive postgraduate program designed to equip students with the advanced knowledge and practical skills required to excel in the rapidly evolving fields of autonomous systems and robotics. This programme is particularly suitable for individuals interested in developing expertise in the design, development, and deployment of intelligent robotic systems capable of operating autonomously in complex environments. The curriculum integrates core topics such as robot perception, control, planning, machine learning, and system integration, providing a balanced blend of theoretical foundations and practical applications. Students will engage with cutting-edge research and industry-relevant projects, often collaborating with leading experts in the field from the Autonomous Systems and Robotics Group at the university. The university’s modern laboratories and research facilities offer students the opportunity to work with advanced robotic hardware and simulation tools, fostering an experiential learning environment. The program emphasizes hands-on experience through laboratory sessions, group projects, and a substantial research dissertation, enabling students to develop critical problem-solving skills and innovative approaches to autonomous systems challenges. Graduates of this MSc are well-prepared for careers in research, development, and consultancy roles across industries such as robotics manufacturing, aerospace, defense, healthcare, and autonomous vehicles. The university’s strong links with industry partners enhance employability prospects and provide networking opportunities that are highly valued by employers globally. Additionally, the programme encourages interdisciplinary collaboration, drawing on expertise from computer science, engineering, AI, and related fields. The MSc in Autonomous Systems and Robotics is suitable for recent graduates from engineering, computer science, or related disciplines seeking to deepen their understanding and enhance their technical capabilities in autonomous technologies. Overall, the program aims to produce graduates who can contribute to innovative developments and technological advancements in autonomous systems, with a focus on safety, reliability, and real-world deployment.