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MEng Mechatronic and Robotic Engineering

University of Sheffield

Institution
University of Sheffield
Level
undergraduate
Subject
Mechatronic and Robotic Engineering
Duration
4 years
UCAS code
H360
Typical offer
A-level AAA

Entry requirements

A Level: AAA IB: 36, with 6 in Higher Level Maths and a science; 34, with 6,5 (in any order) in Higher Level Maths and a science, and B in a science-based Extended Essay

About this course

MEng in Mechatronic and Robotic Engineering, a robotics engineering degree focused on the design and integration of intelligent machines, automated systems, and advanced technology. Core topics include Programming, Systems Design, Embedded Systems, Signal Processing, Microelectronics, and Control Systems. This four-year course includes extensive practical work, featuring collaborative group projects, industrial design tasks, and an individual project. The first year covers core foundations through Group Project and Engineering Skills, Engineering Modelling and Mathematics, System Analysis and Machine Learning, Electric and Magnetic Circuits, and Analogue and Digital Electronics. The second year builds on this with Industrial and Design Projects, Control and Communication Systems, Applied Engineering Mathematics, Embedded Systems Engineering, Robot Foundations, and Robot Statics and Dynamics. Later stages involve advanced study, individual project work, and multidisciplinary group tasks supervised by academic or industrial partners. Optional modules and advanced topics allow students to explore areas such as Space Systems and Spacecraft Design, Digital Signal Processing, Control Systems Design, Reinforcement Learning, and Robot Navigation.

Modules

  • Individual Project
  • Industrial Automation and Digitalisation
  • Machine Learning and Optimisation
  • Robotic Systems
  • Space Systems and Spacecraft Design
  • Digital Signal Processing
  • Control Systems Design
  • Group Project
  • Machine Vision
  • Robot Navigation - Advanced Robotics
  • Fourth year optional modules:
  • Reinforcement Learning - Nonlinear Systems and Control - Optimal and Predictive Control - Real-time Control and Embedded
  • Reinforcement Learning
  • Nonlinear Systems and Control - Optimal and Predictive Control - Real-time Control and Embedded Systems
  • Group Project and Engineering Skills
  • Engineering Modelling and Mathematics
  • System Analysis and Machine Learning
  • Electric and Magnetic Circuits
  • Analogue and Digital Electronics
  • Industrial and Design Projects
  • Control and Communication Systems
  • Applied Engineering Mathematics
  • Embedded Systems Engineering
  • Robot Foundations
  • Robot Statics and Dynamics