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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
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course explored the fundamental problems involved in producing real world intelligent behaviour in robots, covering the different information processing methods and control architectures that have been developed and are currently in use, including probabilistic methods and approaches inspired by biological systems. The course is structured around a practical task to develop navigation algorithms on a real robot platform.
Course description * 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
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Introduction to Vision and Robotics (INFR09019)
Prohibited Combinations Students MUST NOT also be taking Intelligent Autonomous Robotics (Level 11) (INFR11070) OR Robotics: Science and Systems (INFR11092)
Other requirements This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.

A good grounding in mathematics and some knowledge of first-order differential equations will be useful.
Information for Visiting Students
Course Delivery Information
Academic year 2014/15, Available to all students (SV1) Quota:  1
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 96 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) The coursework, carried out in groups of 2 or 3, requires you to program a robot to perform a specified task, and to present the results in written reports. The first two reports are worth 10% each, and the final report 30%.

You should expect to spend approximately 40 hours on the coursework for this course.

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.
Feedback Not entered
No Exam Information
Learning Outcomes
1 - Demonstrate familiarity with current robot control architectures by ability to choose the most appropriate method for a given robot task, to specify the components and interactions involved, and to design and programme an algorithm that solves the task.
2 - Identify and describe limitations of each architecture, particularly when applied to real robots interacting with the real world, rather than simulations.
3 - In written answers, describe and assess attempts to use robots to model biological systems.
4 - Write reports (in the form of journal papers) that explain in detail the implementation and evaluation of a robot performing a navigation task.
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
* Roland Siegwart, Illah R. Nourbakhsh and David Scaramuzza: Autonomous Mobile Robots. MIT Press 2011.
Additional Information
Course URL
Graduate Attributes and Skills Not entered
KeywordsNot entered
Course organiserDr Mary Cryan
Tel: (0131 6)50 5153
Course secretaryMiss Kate Farrow
Tel: (0131 6)51 3211
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