ACS6501 Foundations of Robotics

Module Description (subject to change)

This is an introductory module on the foundations of robotics. The aim of this module is to consolidate fundamental robotics engineering aspects, including ethical ones, as well as introduce relevant topics
to those new to the discipline. The module is separated into five distinct themes:

  • Introduction to robotics and robot ethics
  • Introductory maths
  • Systems modelling and simulation
  • Control systems analysis and design
  • Introduction to programming

Credits: 15 (Autumn semester)

Module Leader

Dr Roderich Gross

Dr Roderich Gross

Pam Liversidge Building

If you have any questions about the module please talk to us during the lectures or the labs in the first instance. It is likely that other students will learn from any questions you ask as well, so don’t be afraid to ask questions.

Outside of lectures please contact one of us via email, or drop in to see one of us.

Other Teaching Staff

Professor George Panoutsos

Dr Anton Selivanov

Learning Outcomes

Learning Outcomes

By the end of the module students will have:

  1. Explain the concepts underpinning robotic systems, and demonstrate an understanding of how robots may impact society.

  2. Solve problems related to robotic systems engineering using relevant mathematical methods.

  3. Use relevant software to model, analyse, simulate, and control a basic mechatronic system.

  4. Acquire core programming concepts and apply these to operate a basic mechatronic system.



  • Brief history and overview of robotics (e.g. manipulators, wheeled robots, legged robots, aerial systems), variable autonomy.
  • Introduction to basic concepts in mathematics (e.g. set theory, functions, real and complex numbers), linear algebra (e.g. matrices and linear transformations, geometry of real vector spaces, row reduction, eigenvalues and eigenvectors), multivariate calculus (e.g. limits, derivatives, Newton's method, Taylor polynomials, integrals), linear differential equations, Laplace transform, probability, developing proofs.
  • Introduction to the purpose, uses and benefits of system modelling; physical equations of systems; empirical models; first and second order system models and time domain solution; system linearisation; transfer function models; mechanical system models; DC motor models; hydraulic actuator models; system block diagrams; state space models.
  • Digital simulation; numerical integration using Euler, Runge-Kutta methods; continuous simulation languages (MATLAB/SIMULINK); simulation of linear and non-linear dynamic systems.
  • Ethics concepts and foundations (e.g. categorical imperative, Utilitarianism), professional ethics, and ethics in a robotics context.
  • Computing concepts, in particular, data structures, algorithms and their analysis.
  • PIC control
  • Programming in MATLAB and C++
  • Programming micro-controller based mobile robots

Teaching Methods

Learning and Teaching Methods

NOTE: This summary of teaching methods is representative of a normal Semester. Owing to the ongoing disruption from Covid-19, the exact method of delivery will be different in 2020/21.

Lectures: 33 hours
Tutorials: 2 hours
Labs: 19 hours
Independent Study: 94 hours

Teaching Materials

Learning and Teaching Materials

All teaching materials will be available via Blackboard (MOLE).



  • Online Quiz 20%
  • Math Test 20%
  • Mobile Robot Simulation Report 30%
  • Simulink Laboratory Report 30%



Students will receive feedback throughout the module as they complete the tests and assignments.

Student Evaluation

Student Evaluation

Students are encouraged to provide feedback during the module direct to the lecturer. Students will also have the opportunity to provide formal feedback via the Faculty of Engineering Student Evaluation Survey at the end of the module.

You can view the latest Department response to the survey feedback here.

Recommended Reading

Recommended Reading

Core Text:

  1. Hubbard and Hubbard. Vector calculus, linear algebra, and differential forms: A unified approach. 5th edition. Matrix Editions. 2015
  2. Stroustrup. The C++ Programming Language. 4th edition. Matrix Editions. 2013
  3. Dorf and Bishop. Modern Control Systems. 9th edition. Prentice Hall. 2001
  4. Cormen et al. Introduction to algorithms. 3rd edition. The MIT Press. 2009
  5. Stroud and Booth. Engineering mathematics. 7th edition. Palgrave, 2013

Secondary Text:

  1. Winfield. Robotics: A Very Short Introduction. Oxford University Press. 2012
  2. Close, Frederick and Newell. Modelling and analysis of dynamic systems. 3rd edition. John Wiley & Sons. 2002
  3. Hung and Esfandiari. Dynamic systems: modelling and analysis. McGraw-Hill. 1998
  4. Essential MATLAB for Scientists and Engineers, Hahn, Butterworth Heinemann (e-book version online via University Library)
  5. Croft and Davison. Mathematics for engineers. 5th edition. Pearson, 2018
  6. Blackburn. Ethics: A very short introduction. Oxford University Press, 2003