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COMP30451: Robotics (2007-2008)

This is an archived syllabus from 2007-2008

Level: 3
Credit rating: 10
Pre-requisites: Either MT1662 or MT1672; some knowledge of C programming, COMP20411
Co-requisites: No Co-requisites
Duration: 8 weeks of lectures plus 4 weeks of practical sessions
Lectures: 16 hours
Lecturers: Robert Richardson
Course lecturer: Robert Richardson

Additional staff: view all staff
Sem 1 w1-5,7-12 Lab Rob Mon 09:00 - 11:00 -
Sem 1 w1-5,7-12 Lecture 1.5 Mon 10:00 - 11:00 -
Sem 1 w1-5,7-12 Lecture 1.3 Tue 14:00 - 15:00 -
Sem 1 w1-5,7-12 Lab Rob Tue 14:00 - 16:00 -
Assessment Breakdown
Exam: 90%
Coursework: 0%
Lab: 0%


This course unit introduces students to robotic systems coving multi-link robotic systems, mobile robotic systems, actuators, sensors, biologically inspired robotics and machine learning techniques. The main aim is to give students an introduction to the field, historic background, development and current cutting edge research points, as well as a practical introduction how to move and control robots. The course unit is practical, and students will be given access to robots for exercises.

Learning Outcomes

At the end of the course unit students will be able to:

Program a robot to perform a specified task (e.g. obstacle avoidance or wall following) in a target environment.
Describe different mechanical configurations of robot manipulators.
Have an understanding of the functionality and limitations of robot actuators and sensors.
Undertake kinematics analysis of robot manipulators.
Understand the importance of robot dynamics Understand and be able to apply a variety of techniques to solve problems in areas such as robot control and navigation.
Understand how simulations of robots work, where they can be useful and where they can break down.
Appreciate the current state and potential for robotics in new application areas.

Assessment of Learning outcomes

Understanding of the topics covered in the course is assessed in two ways. A 2 hour examination covers the students understanding of the theoretical issues, such as robot control paradigms, machine learning techniques, actuator and sensor theory. The ability to use this knowledge in a practical manner is tested through practical sessions with robots. The lab demonstrators mark practical sessions.

Contribution to Programme Learning Outcomes

The course contributes towards knowledge and understanding of Computer Science through its practical orientation towards programming robots, signal processing in real time, controller architecture and hardware issues.

Intellectual skills are trained through the analysis of control problems, identification of ways of solving them and implementation of the solution. Successes or failures are immediately evident through the resulting robot behaviour.

Practical skills are trained through the practical sessions of the course.

Finally transferable skills are trained by having to work tight (lab session) deadlines working in groups during practical sessions, understanding task statements, analyzing them and solving problems.



Definitions and history of robotics.

Sensors and actuators

Types of actuator, types of sensor.

Robotic systems

Robot design, biologically inspired robotics, kinematics, dynamics, locomotion, control.

Autonomous mobile robotic systems

Benefits, problems, suitable tasks, machine learning, navigation.


Simulation of a robot and its environment. Assessment of simulation accuracy. Model acquisition and validation.

Reading List

There is no set text for this course, and the lecture notes aim to be self-contained. The following books provide useful supporting material for certain sections of the course. Special resources needed to complete the course unit Students will use the Robotics Laboratory.