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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2012/2013
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DRPS : Course Catalogue : School of Informatics : Informatics

Undergraduate Course: Intelligent Autonomous Robotics (Level 10) (INFR10005)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) Credits10
Home subject areaInformatics Other subject areaNone
Course website http://www.inf.ed.ac.uk/teaching/courses/iar-4 Taught in Gaelic?No
Course descriptionThe aims of this course are to introduce the fundamental problems of producing real world intelligent behaviour in robots, some of the different kinds of information processing techniques and control architectures that have been developed, and how biological systems can be modelled on robots and contribute to their design.

The course is structured around a practical-based programme involving the development of navigation algorithms on a real robot platform. We will cover related sensing and control ideas, approaches, and organisational architectures. We consider some alternative types of mechanism suggested for the production of desired intelligent behaviour by both engineers and biologists.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Introduction to Vision and Robotics (INFR09019)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Intelligent Autonomous Robotics (Level 11) (INFR11070) OR Robotics: Science and Systems (INFR11092)
Other requirements Successful completion of Year 3 of an Informatics Single or Combined Honours Degree, or equivalent by permission of the School. A good grounding in mathematics and some knowledge of first-order differential equations will be useful.
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2012/13 Semester 1, Available to all students (SV1) Learn enabled:  No Quota:  None
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
CentralLecture1-11 09:00 - 09:50
CentralLecture1-11 09:00 - 09:50
First Class Week 1, Thursday, 09:00 - 09:50, Zone: Central. 2.14 Appleton Tower
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S2 (April/May)2:00
Delivery period: 2012/13 Semester 1, Part-year visiting students only (VV1) Learn enabled:  No Quota:  None
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
CentralLecture1-11 09:00 - 09:50
CentralLecture1-11 09:00 - 09:50
First Class Week 1, Thursday, 09:00 - 09:50, Zone: Central. 2.14 Appleton Tower
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S1 (December)2:00
Summary of Intended Learning Outcomes
1 - Knowledge of robot control architectures, and understanding of the issues involved in programming real robots as opposed to simulators.
2 - Familiarity with current approaches to robotics, including reactive, subsumption, cybernetic, classical, probabilistic, evolutionary and multirobot approaches
3 - Understand the main issues and methods in mobile robot navigation systems
4 - Understand how to model and evaluate models of biological systems on robots
5 - Program a robot to do specified tasks, dealing with sensing and acting in the real world, evaluate the results and present the work in a written report.
Assessment Information
Written Examination 50
Assessed Assignments 50
Oral Presentations 0

Assessment
One assignment, carried out in groups of 2 or 3, accounts for 40% of the course marks. This requires you to program a robot to perform a specified task, and to present the results in a written report. The other 10% of the coursework marks will be for satisfactory completion of the weekly goals towards this task, demonstrated in each practical session and in short progress writeups.

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.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus * The problem of designing intelligent autonomous systems.
* Reactive control of behaviour.
* The subsumption architecture.
* Sensor fusion.
* Control.
* Planning.
* Evolutionary and collective robotics.
* Robots as biological models.
* Simple navigation: gradient following, potential fields, landmarks.
* Navigation with maps: localisation and learning maps.

Relevant QAA Computing Curriculum Sections: Artificial Intelligence, Intelligent Information Systems Technologies
Transferable skills Not entered
Reading list * Valentino Braitenberg: Vehicles. MIT Press 1984
* Ronald C Arkin: Behavior-based Robotics, MIT press, 1998
* Robin R. Murphy: Introduction to AI Robotics, MIT Press, 2000
Introduction to Autonomous Mobile Records, R.Siegwart and I.Nourbakhsh
Study Abroad Not entered
Study Pattern Lectures 20
Tutorials 0
Timetabled Laboratories 10
Non-timetabled assessed assignments 40
Private Study/Other 30
Total 100
KeywordsNot entered
Contacts
Course organiserDr Mary Cryan
Tel: (0131 6)50 5153
Email: mcryan@inf.ed.ac.uk
Course secretaryMiss Kate Weston
Tel: (0131 6)50 2701
Email: Kate.Weston@ed.ac.uk
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