MSc Robotics and Autonomous Systems

1 Year On Campus Masters Program

University of Bath

Program Overview

The MSc equips students with the ability to design, build and deploy robotic and autonomous systems — blending core engineering (mechanical, electrical, embedded systems) with software, AI and real‑world applications. It’s ideal for candidates with a background in mechanical, electronic, or electrical engineering (or a related field) who want to transition into roles such as robotics engineer, autonomous systems developer or intelligent machines specialist.

Curriculum Structure:
Year 1 (Full‑time route or 15‑month including placement):
In the taught phase, students engage with modules such as “Autonomy and AI/ML” (10 credits) where they explore machine learning, sensor data fusion and navigation algorithms in autonomous systems. They also study “Robot software” (10 credits), where they apply industry‑standard tools (e.g., ROS, simulation frameworks) to program and control robotic systems. In addition, the module “Robotic engineering analysis” (10 credits) deals with robot kinematics, dynamics and control — helping students develop the analytical framework for sophisticated robotic platforms.
Project/Placement Phase:
If opting for the 15‑month variant, after semester 2 the student moves into a professional placement (30 credits) working with an industry partner to apply their skills in a real‑world context. Simultaneously or subsequently, they undertake a major Robotic and autonomous systems design & integration project (10 credits) or alternative consultancy/research project (30 credits) where they integrate sensors, electronics, control systems and software into working prototypes.

Focus areas:
Robotics engineering • Autonomous systems and embedded AI/ML • Robot software systems and integration • Systems design and control • Commercialisation of new technologies in robotics.

Learning outcomes:
On successful completion, students will be capable of designing and analysing robotic and autonomous systems, using both the hardware and software stack; they will be able to apply machine learning and sensor‑fusion methods to real‑world embedded systems; additionally, they will gain the professional skills (project management, ethics in robotics, commercialisation) required to transition into industry or further research.

Professional alignment (accreditation):
While the official page does not highlight a specific external accreditation for this MSc, the programme is embedded in the Faculty of Engineering & Design at Bath and leverages strong industry links, making it highly relevant for engineering roles.

Reputation (employability rankings):
The University of Bath is recognised for its strong engineering programmes and emphasises the hands‑on and industry‑facing nature of this MSc. The inclusion of professional placements and strong project work adds to employability. For instance, the official course page states: “You’ll graduate with the skills to innovate and deliver resource‑efficient practices and solutions for robotic and autonomous systems.”

Experiential Learning (Research, Projects, Internships etc.)

From the very beginning, students engage in practical, applied work in robotics and autonomy. You’ll make use of rapid‑prototyping workshops (3D printing, laser cutting, vacuum forming), robotics‑/EV‑equipment, advanced CNC and manual machining, real‑time digital simulation and GPU‑accelerated labs — all designed to let you build, test and iterate robotics and autonomous‑system solutions. You’ll also use professional software frameworks like the Robot Operating System (ROS) for simulation and robot‑software tasks. Over the course of the programme you’ll carry out both group and individual design projects, and (in the placement version) a real industry placement — so you’ll leave with a portfolio of applied work ready for employers.

Given that orientation, here are specific experiential learning features built into the programme:

Access to specialist facilities: rapid‑prototyping (3D printers, laser cutters, vacuum forming); advanced robotics, electric vehicle and autonomous systems equipment; CNC & manual machining workshops; real‑time simulation labs and a GPU‑accelerated AI/ML dedicated lab.
Use of cloud/HPC resources (e.g., the university’s “Nimbus” cloud‑supercomputing facility) for large‑scale simulation, AI/ML workloads and autonomous‑system data processing.
Modules involving software and robotics tools: e.g., a “Robot software” unit where you’ll work with ROS, microcontrollers and embedded systems in both individual and team settings.
A design/integration project (“Robotic and autonomous systems design and integration”) where you’ll work in teams to integrate mechanical, electrical, sensor and control systems, simulate and test them, and produce technical reports and presentations.
Modules in autonomous decision‑making and AI/ML for autonomy: e.g., “Autonomy and AI/ML” unit where you analyse sensor data, integrate learning methods and develop navigation algorithms under uncertainty.
Professional and research skills development: including modules on ethics (“Robo‑ethics”), commercialization of new technologies (“Commercialising new technology”), plus opportunities for consultancy or research projects depending on your path.
A professional‑practice placement option (in the 15‑month version) of up to three months working in industry, putting into practice what you’ve learned and building industry contacts.
Strong support structures: you’ll receive guidance from personal academic tutors, career advisors and access tailored resources to help develop your professional skills alongside the technical ones.

Progression & Future Opportunities

Graduates of the University of Bath MSc Robotics & Autonomous Systems are well‑positioned for roles such as robotics engineer, autonomous systems designer, embedded AI systems developer or controls / navigation systems engineer—driven by hands‑on experience and industry‑relevant skills. Here’s how the programme supports that trajectory:

The university’s Faculty Postgraduate Employability Team provides tailored support, including CV and interview workshops, and helps students secure professional placements as part of the course.
This course emphasises industry engagement, with students undertaking a professional placement (three‑month) or group consultancy project with industry partners.
Students will gain access to specialist facilities: rapid‑prototyping labs, EV/robotics test rigs, GPU‑accelerated AI/ML labs and a cloud super‑computer facility for simulation.
The curriculum is designed around current sector needs—modules include Autonomy & AI/ML, Robotic & Autonomous Systems Design & Integration, Robot Software and more—building technical and professional skills.
Graduation outcomes: The programme reports that its alumni find employment at organisations such as ThyssenKrupp, Unique Group, CMR Surgical, Ocado Technology and Small Robot Company, demonstrating broad opportunity.
The professional placement built into the 15‑month variant gives a concrete edge: students apply theory in a workplace environment, expand networks and enhance employability.

Further Academic Progression:
Graduates may proceed to doctoral level (PhD) research in areas such as advanced autonomous systems, robotics perception and AI control, or human‑robot interaction. Alternatively, they could pursue specialist postgraduate certificates in related domains like autonomous vehicles, unmanned aerial systems or embedded systems design. For those entering industry first, after gaining experience they may move into leadership, R&D management or systems architect roles in robotics and automation.