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Department of Computer Science

CS313 Mobile Robotics

CS313-15 Mobile Robotics

Academic year
24/25
Department
Computer Science
Level
Undergraduate Level 3
Module leader
Claire Rocks
Credit value
15
Module duration
10 weeks
Assessment
Multiple
Study location
University of Warwick main campus, Coventry

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Introductory description

The main aim of the module is to provide an understanding of the fundamental principles of mobile robotics and related concepts. The module introduces various algorithms and data structures for safe navigation of a mobile robot, and covers some techniques for equipping the robot with an intelligent vision system.

Module aims

The main aim of the module is to provide an understanding of the fundamental principles of mobile robotics and related concepts. The module introduces various algorithms and data structures for safe navigation of a mobile robot, and covers some techniques for equipping the robot with an intelligent vision system.

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

  • Introduction to mobile robots
  • Sensors
  • State Estimation
  • Discrete Filter
  • Linear Gaussian Filter
  • Non-parametric Filters
  • Mapping
  • SLAM
  • Motion Planning

Learning outcomes

By the end of the module, students should be able to:

  • Demonstrate an understanding of the underlying principles of mobile robotics
  • Demonstrate a knowledge of the applications of mobile robotics
  • Apply these to analyse and solve real-world problems

Indicative reading list

(a) Sebastian Thrun, Wolfram Burgard, Dieter Fox, Probabilistic Robotics, MIT Press, 2005.
(b) Siegwest and Nourbakhsh, Introduction to Autonomous Mobile Robots, MIT Press, 2004.
(c) Dudek G and Jenkin M, Computational Principles of Mobile Robotics, Cambridge University Press, 2000.
(d) Craig JJ, Introduction to Robotics: Mechanics and Control (3rd ed), Prentice-Hall, 2005.
(e) Gonzalez R and Woods RC, Digital Image Processing, Prentice-Hall, 2002.

View reading list on Talis Aspire

Subject specific skills

Students will learn about :

  • the typical sensing modalities used in modern mobile robots
  • different approaches to localisation and navigation in mobile robotics
  • different applications of mobile robotics
  • They will learn techniques to analyse sensory input to solve real-world problems.

Transferable skills

  • Communication
  • Critical thinking
  • Problem solving

Study time

Type Required
Lectures 20 sessions of 1 hour (13%)
Practical classes 6 sessions of 2 hours (8%)
Private study 118 hours (79%)
Total 150 hours

Private study description

  • Background reading
  • Study lecture materials
  • Work for lab
  • Revision

Costs

No further costs have been identified for this module.

You do not need to pass all assessment components to pass the module.

Students can register for this module without taking any assessment.

Assessment group D4
Weighting Study time Eligible for self-certification
Lab report 20% Yes (extension)

This assessment is eligible for self-certification (extension).
In-person Examination 80% No

CS313 examination

  • Answerbook Gold (24 page)
  • Students may use a calculator
  • Engineering Data Book 8th Edition
Assessment group R3
Weighting Study time Eligible for self-certification
In-person Examination - Resit 100% No

CS313 resit examination

  • Answerbook Gold (24 page)
  • Students may use a calculator
  • Engineering Data Book 8th Edition
Feedback on assessment

Written feedback for the lab report will be provided on Tabula

Past exam papers for CS313

Pre-requisites
  • Ideally the student would find it useful to have completed CS130 Mathematics for Computer Scientists I, CS131 Mathematics for Computer Scientists II, ES107 Mathematics for Engineers, or a similar Mathematics module.

Courses

This module is Optional for:

  • Year 3 of UCSA-G4G1 Undergraduate Discrete Mathematics
  • Year 3 of UCSA-G4G3 Undergraduate Discrete Mathematics
  • Year 4 of UCSA-G4G4 Undergraduate Discrete Mathematics (with Intercalated Year)
  • Year 4 of UCSA-G4G2 Undergraduate Discrete Mathematics with Intercalated Year

This module is Option list A for:

  • Year 4 of UCSA-G504 MEng Computer Science (with intercalated year)
  • Year 3 of UCSA-G500 Undergraduate Computer Science
  • Year 4 of UCSA-G502 Undergraduate Computer Science (with Intercalated Year)
  • UCSA-G503 Undergraduate Computer Science MEng
    • Year 3 of G500 Computer Science
    • Year 3 of G503 Computer Science MEng
  • Year 3 of UCSA-G406 Undergraduate Computer Systems Engineering
  • Year 3 of UCSA-G408 Undergraduate Computer Systems Engineering
  • Year 4 of UCSA-G407 Undergraduate Computer Systems Engineering (with Intercalated Year)
  • Year 4 of UCSA-G409 Undergraduate Computer Systems Engineering (with Intercalated Year)

This module is Option list C for:

  • Year 3 of USTA-G302 Undergraduate Data Science
  • Year 3 of USTA-G304 Undergraduate Data Science (MSci)
  • Year 4 of USTA-G303 Undergraduate Data Science (with Intercalated Year)

Further Information

Term 2

15 CATS (7.5 ECTS)

Online Material

Module Organisers:

Claire Rocks

Debmalya.Mandal