Undergraduate Course: Intelligent Autonomous Robotics (Level 10) (INFR10005)
|School||School of Informatics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 10 (Year 4 Undergraduate)
||Availability||Available to all students
|Summary||This 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.
* The problem of designing intelligent autonomous systems.
* Reactive control of behaviour.
* The subsumption architecture.
* Sensor fusion.
* 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
Information for Visiting Students
Course Delivery Information
|Academic year 2014/15, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|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.
|No Exam Information
| 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.
|* 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.
|Course organiser||Dr Mary Cryan
Tel: (0131 6)50 5153
|Course secretary||Miss Kate Farrow
Tel: (0131 6)51 3211
© Copyright 2014 The University of Edinburgh - 12 January 2015 4:11 am