University of Strathclyde

What you'll study

The programme delivers a blend of taught modules, laboratory classes and a substantial individual project or industrial dissertation. You will study core topics in robotic perception, planning and control alongside AI techniques used for autonomy, with opportunities to work on hardware and simulation platforms.

Typical modules and topics

• Perception and Computer Vision – sensor models, feature extraction, object recognition, depth sensing and visual odometry.
• Machine Learning for Robotics – supervised and reinforcement learning methods applied to control, policy learning and behaviour generation.
• Robot Control and Motion Planning – kinematics and dynamics, trajectory planning, state estimation and feedback control.
• Sensor Fusion and Probabilistic Robotics – Bayesian filtering, SLAM and multi-sensor integration for robust state estimation.
• Embedded Systems and Real-time Implementation – microcontrollers, real-time operating systems, hardware–software co-design and deployment.
• Multi-agent and Distributed Autonomous Systems – coordination, communication protocols and swarm/collective behaviours.
• Safety, Ethics and Regulation of Autonomous Systems – risk assessment, verification, legal and societal implications of autonomy.
• Research/Industrial Project – a substantial project carried out individually or with an industry partner, often involving prototype development, field trials or data-driven evaluation.

Teaching methods include lectures, seminars, practical labs using robotics platforms and simulation tools (including ROS and common physics engines), guest talks from industry, and supervised research. Assessment is by coursework, laboratory reports, examinations where appropriate, and the final project dissertation.

Entry requirements

Applicants are normally expected to hold a good honours degree (typically a UK upper second-class, 2:1, or equivalent) in engineering, computer science, mathematics, or a closely related discipline. Candidates with a lower second-class degree plus relevant practical experience or demonstrable skills in programming, electronics or modelling may be considered.

Essential background includes undergraduate exposure to programming (for example Python, C/C++), linear algebra, probability and control or dynamics. Applicants who lack specific elements of this background may be offered conditional admission with short preparatory modules.

International applicants will need to demonstrate English language proficiency; a commonly accepted benchmark is an overall IELTS score of 6.5 with no component below 6.0, or an equivalent qualification. Applications are considered on a rolling basis and entry is competitive; selection also takes into account references, personal statement and any relevant project or work experience.

Career prospects

Graduates move into a wide range of roles across industry and research. Typical destinations include:

• Robotics engineer or systems integrator in manufacturing, logistics and automation companies.
• Autonomy software developer for autonomous vehicles, aerial drones and maritime systems.
• Perception and computer vision engineer in medical robotics, surveillance or inspection sectors.
• Machine learning engineer focusing on embodied AI, reinforcement learning and control.
• Research and development roles in technology companies, research institutes or as preparation for a PhD in robotics, AI or related areas.
• Technical consultant, product engineer or startup founder working on novel robotic products and services.

The programme’s mix of practical laboratory work and project experience is designed to equip you with the technical and project-management skills employers seek, including software development, systems integration, testing and validation of autonomous systems.

Why study at University of Strathclyde

Strathclyde has a long-established engineering school with a strong emphasis on applied research and industrial collaboration. You will benefit from hands-on access to specialist laboratories and robotics workspaces, teaching by academic staff active in robotics, AI and control research, and connections with regional and national technology companies.

The university’s location in Glasgow places you within a vibrant technology and manufacturing ecosystem, which supports guest lectures, industry projects and potential placement opportunities. The programme’s interdisciplinary approach, combining computing, electronics and systems engineering, prepares graduates to work across sectors where autonomous systems are being developed and deployed.

Overall, the MSc in Autonomous Robotic Intelligent Systems is designed to provide the technical depth, practical experience and industry relevance needed to launch a career in robotics and autonomy or to progress into postgraduate research.