Undergraduate Course: Introduction to Vision and Robotics (INFR09019)
Course Outline
| School |
School of Informatics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 09 (Year 3 Undergraduate) |
Credits |
10 |
| Home subject area |
Informatics |
Other subject area |
None |
| Course website |
http://www.inf.ed.ac.uk/teaching/courses/ivr |
|
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| Course description |
Robotics and Vision applies AI techniques to the problems of making devices capable of interacting with the physical world. This includes moving around in the world (mobile robotics), moving things in the world (manipulation robotics), acquiring information by direct sensing of the world (e.g. machine vision) and, importantly, closing the loop by using sensing to control movement. Applying AI in this context poses certain problems, and sets certain limitations, which have important effects on the general software and hardware architectures. For example, a robot with legs must be able to correct detected imbalances before it falls over, and a robot which has to look left and right before crossing the road must be able to identify approaching hazards before it gets run over. These constraints become much more serious if the robot is required to carry both its own power supply and its own brain along with it. This module introduces the basic concepts and methods in these areas, and serves as an introduction to the more advanced robotics and vision modules. |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
|
| Prohibited Combinations |
|
Other requirements |
Successful completion of Year 2 of an Informatics Single or Combined Degree, or equivalent by permission of the School. This course assumes experience of AI knowledge and representation issues (equivalent to first and second year courses in Informatics); enough school algebra and geometry to understand the optics of image formation with lenses; enough school physics to understand Newton's Laws of Motion; the general mechanical intuitions required in such tasks as bicycle maintenance; enough electrical knowledge to understand how electric batteries make electric motors work. You are expected to be familiar with these mathematical methods: Bayes rule, Multivariate Gaussian Distribution,
Covariance matrices, Convolution, the Jacobean (relating derivatives of a vector valued function to its vector valued inputs).
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| Additional Costs |
None |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 1, Available to all students (SV1)
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WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | | | 09:00 - 09:50 | | Central | Lecture | | 1-11 | | 09:00 - 09:50 | | | |
| First Class |
Week 1, Tuesday, 09:00 - 09:50, Zone: Central. Faculty Room North, David Hume Tower |
|
| Delivery period: 2010/11 Semester 1, Part-year visiting students only (VV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | | | 09:00 - 09:50 | | Central | Lecture | | 1-11 | | 09:00 - 09:50 | | | |
| First Class |
Week 1, Tuesday, 09:00 - 09:50, Zone: Central. Faculty Room North, David Hume Tower |
Summary of Intended Learning Outcomes
1 - Students will be able to recall and explain the essential facts, concepts and principles in robotics and computer vision, demonstrated through written answers in examination conditions.
2 - Students will be able to describe and evaluate the strengths and weaknesses of some specific sensor and motor hardware; and some specific software methods for sensory processing and motor control, demonstrated through written answers in examination conditions.
3 - Students will be able to employ hardware (e.g. cameras, robots) and software (e.g. Matlab,robot simulator) tools to solve a practical problem of sensory-motor control, and will show a working system in a practical class.
4 - Students will, in writing a joint report, identify problem criteria and context, discuss design and development, test, analyse and evaluate the behaviour of the sensory-motor control system they have developed. |
Assessment Information
Written Examination 75
Assessed Assignments 25
Oral Presentations 0
Assessed Coursework
Reports on practical projects.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year. |
| Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
| Not entered |
Contacts
| Course organiser |
Dr Marcelo Cintra
Tel: (0131 6)50 5118
Email: mc@inf.ed.ac.uk |
Course secretary |
Miss Tamise Totterdell
Tel: 0131 650 9970
Email: t.totterdell@ed.ac.uk |
|
copyright 2010 The University of Edinburgh -
1 September 2010 6:09 am
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