COMP0127 Robotic Systems Engineering

This database contains the 2018-19 versions of syllabuses.

Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).

Academic session

2018-19

Module

Robotic Systems Engineering

Code

COMP0127

Module delivery

1819/A7P/T1/COMP0127 Postgraduate

Related deliveries

None

Prior deliveries

COMPGX01

Level

Postgraduate

FHEQ Level

L7

FHEQ credits

15

Term/s

Term 1

Module leader

Stoyanov, Danail

Contributors

Stoyanov, Danail

Module administrator

Horslen, Caroline

Aims

The students will gain insight into robotics systems and the general concepts, mathematic and algorithms that underpin moving and actuating robotic arms and devices. Specific topics we cover: fundamental linear algebra, kinematics and inverse kinematics, actuation dynamics and mechanisms, and motion planning.

Learning outcomes

On successful completion of the module, a student will be able to:

  1. understand robot kinematics
  2. understand robot motion planning
  3. understand different robotic mechanisms, specifically robotic arms
  4. programme with Python and ROS (optional C++)

Availability and prerequisites

This module delivery is available for selection on the below-listed programmes. The relevant programme structure will specify whether the module is core, optional, or elective.

In order to be eligible to select this module as optional or elective, where available, students must meet all prerequisite conditions to the satisfaction of the module leader. Places for students taking the module as optional or elective are limited and will be allocated according to the department’s module selection policy.

Programmes on which available:

  • MRes Robotics
  • MSc Business Analytics (with specialisation in Computer Science)
  • MSc Computational Statistics and Machine Learning
  • MSc Machine Learning
  • MSc Robotics and Computation

Prerequisites:

There are no formal prerequisites.

Students are recommended to be able to use Linux and have some background in programming, especially using Python, and be comfortable with linear algebra.

Content

The aim of this module is to provide the basic theory required for solving problems involving the motion of robotics and autonomous systems from a practitioner's point of view.

The module presents theory and methodology for analysis and modelling of robot kinematics, and methods for moving robots within workspaces. Special emphasis is placed on:

  • Linear algebra needed for robot motion and transformation
  • Robot kinematics and DH tables
  • Inverse kinematics and solving inverse systems
  • Planning and executing robot motion

Theoretical lectures will be accompanied by corresponding practical exercises using ROS and predominantly carried out in simulation.

An indicative reading list is available via http://readinglists.ucl.ac.uk/departments/comps_eng.html.

Delivery

The module is delivered through a combination of lectures, tutorials, seminars, written and programming exercises, and project work.

Assessment

This module delivery is assessed as below:

#

Title

Weight (%)

Notes

1

Coursework 1

20

 

2

Coursework 2

30

 

3

Coursework 3

50

 

In order to pass this module delivery, students must achieve an overall weighted module mark of 50%.