MSc Robotics, AI and Autonomous Systems

1 Year On Campus Masters Program

City University of London

Program Overview

The MSc Robotics, AI and Autonomous Systems prepares students to engineer and deploy next-generation autonomous technologies, including mobile robots, drones, autonomous vehicles, and other intelligent systems. It combines deep theoretical knowledge in robotics, control systems, AI/machine learning, and signal processing with practical hardware and software work, equipping students to design, build, and manage autonomous systems in real-world environments.

Curriculum structure

First Term (Core Foundations)

Advanced Signal Processing and Communications: Covers advanced signal processing and communication fundamentals for real-time data transmission, sensor integration, and robust communication, essential for autonomous systems.
Robotics, Imaging and Vision: Introduces image processing, computer vision, and robotics, integrating software, hardware, sensors, and instrumentation.
Engineering Programming: Builds practical programming skills (Python, C++), software engineering practices, debugging, and testing, vital for robotics and embedded systems.
System Dynamics, Propulsion and Control: Focuses on modeling, stability, navigation, control design, and dynamics for autonomous vehicles and mobile robots.

Second Term (Advanced AI, Autonomy & Embedded Systems)

Embedded Systems: Teaches embedded programming and real-time hardware/software integration, enabling students to deploy algorithms on autonomous hardware.
Machine/Machine, Human/Machine Teaming: Explores interaction between machines and humans and multi-agent cooperation, critical for autonomous systems in human environments.
Machine Learning: Covers AI and machine learning techniques tailored for perception, decision-making, and adaptive behavior in autonomous agents.
AI for Engineering Design Projects: A project-based module applying AI techniques in design, prototyping, and building autonomous systems, giving hands-on experience with real-world challenges.

Dissertation / Final Project

Students complete an Individual Project spanning 60 credits, addressing a design challenge or research problem. Projects may involve developing autonomous solutions, testing systems, or simulating robotics applications, integrating all theoretical and practical learning.

Focus areas

Robotics hardware and embedded systems; control systems; autonomous vehicles and UAVs; computer vision; AI and machine learning for autonomy; human-machine and machine-machine interaction; signal and sensor processing; embedded systems design; engineering programming; autonomous system design, simulation, and deployment; research and project-based development.

Learning outcomes

Graduates can design, program, and build autonomous robotic and vehicle systems; apply control theory, dynamics, and embedded systems knowledge; implement AI and machine learning for perception and decision-making; integrate hardware and software for real-world robotics; understand human-machine teaming and multi-agent cooperation; manage projects leading to autonomous prototypes or simulations; and pursue careers in robotics, aerospace, automotive, defence, energy, manufacturing, or R&D.

Professional alignment (accreditation / career prospects)

This MSc meets industry demand for experts in robotics, autonomous systems, AI, and intelligent vehicles. Graduates are prepared for roles in robotics companies, automotive firms (especially autonomous vehicles), aerospace, UAV development, defence, energy and utilities, manufacturing, research labs, or further study (PhD).

Reputation (employability & outcomes)

City’s programme offers strong lab facilities, including robotics laboratories and indoor arenas for UAV/robot testing, providing practical experience in real-time system validation. Combined with technical and AI training, this makes graduates highly sought after in industries where autonomous and intelligent systems are central.

Experiential Learning (Research, Projects, Internships etc.)

This MSc is designed to give you hands-on, technical and applied experience in robotics, AI, embedded systems, and autonomous system design. Students work in well-equipped labs and on substantial design projects, gaining both theoretical knowledge and practical experience with robotics hardware, embedded systems, sensing/vision, and control.

Practical experience includes:

Extensive lab work covering programming (Python, C++), embedded systems design, robotics, image processing & computer vision, control systems, and communications.
Modules requiring integration of hardware and software — e.g., building and testing robotic systems that perceive and react to their environment.
Hands-on projects on autonomous vehicles, mobile robots, and UAVs — learning dynamics, propulsion and control, navigation, and autonomy design.
Modules on machine learning and human-machine/machine-machine teaming — providing exposure to AI-driven robotics and autonomous decision systems.
A major individual project (dissertation) in the final term to solve a real robotics/AI/autonomous-systems problem, building a strong portfolio.
Use of advanced facilities — including a robotics laboratory, an indoor test arena for drones, and a “Hardware In the Loop” facility for validating industrial robotic designs.

What you’ll study — core themes, breadth and depth

The curriculum is broad and technically rigorous, covering robotics fundamentals, AI, embedded systems, control, communication, autonomy, and legal/ethical aspects. Topics include:

Signal processing and communications for robotic sensing and data transfer.
Robotics, imaging, and vision — combining hardware and software to enable perception and autonomous reaction.
Engineering programming and software engineering fundamentals.
System dynamics, propulsion, and control for mobile robots, UAVs, or autonomous vehicles.
Embedded systems — programming and integrating microcontrollers or hardware for real-time robotics applications.
Machine learning and AI for engineering — applying ML to robotics, autonomous decision-making, and sensor data processing.
Human-machine and machine-machine teaming — studying interactions for safety and collaboration in autonomous systems.
Project-based design modules using AI and autonomous-systems design processes.
Independent dissertation/project — implementing a robotics/AI/autonomous-systems project of your own.
Legal, regulatory, and ethical aspects related to deploying autonomous systems.

Career Paths & Why This Degree Opens Doors

Graduates are prepared for cutting-edge roles:

Robotics design and development, embedded systems engineering, autonomous vehicles, UAVs, and mobile robotics.
AI-driven systems design, including machine learning, computer vision, sensor data processing, and control systems.
Roles in aerospace, defence, automotive, manufacturing, energy, and other industries deploying autonomous or robotic systems.
Opportunities in R&D or further research (e.g., PhD in robotics or AI).
International career prospects — skills in programming, hardware, AI, control, and embedded systems are globally relevant.

Why This MSc Could Be a Great Fit for You

Combines software + hardware + AI + systems thinking, giving a holistic skill set demanded by modern robotics and autonomous-systems industries.
Lab work, projects, and a major dissertation provide hands-on experience and a tangible portfolio.
Legal, ethical, and regulatory training prepares you as a responsible technologist aware of real-world deployment challenges.
Broad coverage allows specialization in ground, air, or space robotics, autonomous vehicles, embedded systems, and machine learning.
Internationally relevant qualification with exposure to global-standard robotics environments and skills in high demand worldwide.

Progression & Future Opportunities

Graduates from the MSc Robotics, AI and Autonomous Systems are prepared for careers in fast-growing sectors relying on robotics, AI, and autonomous systems — from automotive and aerospace to space tech, defence, energy, manufacturing, and specialized robotics firms.

Typical job roles include:

Autonomous Systems Engineer (ground, drone, or aerial robotics)
Robotics / AI Engineer or Developer
Control Systems Engineer or Specialist
Embedded Systems Developer for robotics or autonomous platforms
Research & Development Engineer in robotics, aerospace, or autonomous systems

You will also benefit from the following opportunities through this course:

Strong technical and practical training: The curriculum includes robotics, machine learning, computer vision, signal processing, embedded systems design, control, and software/hardware integration — all aligned with industry requirements.
Industry-relevant experience via labs and projects: Design projects, lab work, hardware-in-the-loop testing, and a dissertation project provide hands-on experience in addition to theory.
Flexible study mode: Full-time or part-time options allow working professionals or those balancing other commitments to complete the MSc.
Broad sector applicability: Skills are relevant across robotics, aerospace, automotive, defence, manufacturing, energy, and emerging sectors like drones or space systems.
Preparation for cutting-edge and future-oriented roles: Graduates are equipped for roles in growing fields such as self-driving vehicles, drones, space robotics, and industrial automation.

Further Academic Progression:

Graduates can:

Enter directly into industry — robotics firms, aerospace companies, autonomous vehicle developers, defence contractors, or R&D labs.
Pursue research-oriented postgraduate paths (e.g., PhD) in robotics, autonomous systems, AI, machine learning, control systems, or related fields.
Combine technical knowledge with adjacent fields such as aerospace engineering, autonomous vehicles, smart systems design, or data science to move into interdisciplinary or leadership roles.

Why This Degree Could Be the Right Fit for You

If you are passionate about robotics, AI, and autonomous systems — and enjoy both software and hardware challenges — this MSc provides a powerful, up-to-date foundation. It combines technical depth, practical engineering skills, and real-world project experience.

It is ideal for students who want flexibility (full-time or part-time) and aspire to work in cutting-edge, future-oriented industries such as drones, self-driving vehicles, aerospace robotics, automation in manufacturing, or AI-driven systems.