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EE50235: Autonomous systems engineering

[Page last updated: 15 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: Department of Electronic & Electrical Engineering
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 1
Further information on unit assessment Assessment Summary: EX 100%
Further information on unit assessment Assessment Detail:
  • Examination (EX 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
Description: Aims:
To introduce students to the key elements of autonomous systems design.
To introduce key concepts in understanding, designing and critically appraising autonomous systems.
To provide key skills in implementing autonomous systems.

Learning Outcomes:
Design, validate and critically appraise autonomous systems (EP3, ET3, ET4, DP1, SM3).
Compare, contrast and evaluate autonomous systems design techniques and technologies (EP1, EP2, EA3).
Use a range of established and new techniques to design autonomous systems (ET5, EA1, EA2).

Skills:
Numeracy: Design digital systems (T,F,A)
Using IT effectively: Simulators and design tools (T,F,A)
Research and Analysis: evaluating designs critically (T,F,A)
Independent Working (T, F, A)
Problem Solving (T, F,A)

Content:
Autonomy and control algorithms
* advanced automation.
* safety and fault tolerance.
* guidance, navigation, command and control.
* intelligent systems (e.g. sense and avoid, sense and follow).
Power optimisation:
* energy storage and management for vehicle platforms.
Sensing technologies:
* object detection and recognition.
* basic imaging and signal processing.
Further information on programme availabilityProgramme availability:

EE50235 is Compulsory on the following programmes:

Department of Electronic & Electrical Engineering

EE50235 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFM51 : Integrated PhD Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM51 : MRes Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM52 : MSc Accountable, Responsible and Transparent Artificial Intelligence
  • TSCM-AFM48 : MSc Machine Learning and Autonomous Systems
  • TSCM-AWM48 : MSc Machine Learning and Autonomous Systems

Notes: