Postgraduate Course: Robotics: Science and Systems (INFR11092)
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 11 (Postgraduate) |
Credits | 20 |
Home subject area | Informatics |
Other subject area | None |
Course website |
http://course.inf.ed.ac.uk/rss |
Taught in Gaelic? | No |
Course description | This course will be a Masters degree level introduction to several core areas in robotics: kinematics, dynamics and control; motion planning; state estimation, localization and mapping; vision for robotics. Lectures on these topics will be complemented by a large practical that exercises knowledge of a cross section of these techniques in the construction of an integrated robot in the lab, motivated by a task such as robot navigation. Also, in addition to lectures on algorithms and lab sessions, we expect that there will be several lecture hours dedicated to discussion of implementation issues - how to go from the equations to code.
The aim of the course is to present a unified view of the field, culminating in a practical involving the development of an integrated robotic system that actually embodies key elements of the major algorithmic techniques. |
Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | Students MUST NOT also be taking
Introduction to Vision and Robotics (INFR09019) OR
Intelligent Autonomous Robotics (Level 10) (INFR10005)
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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.
Multivariate Calculus, Linear Algebra and matrix manipulations, Basic notions of Statistics and concepts including expectation and conditional probability. |
Additional Costs | None |
Information for Visiting Students
Pre-requisites | None |
Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
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Delivery period: 2014/15 Semester 1, Available to all students (SV1)
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Learn enabled: No |
Quota: None |
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Web Timetable |
Web Timetable |
Course Start Date |
15/09/2014 |
Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 30,
Supervised Practical/Workshop/Studio Hours 8,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
156 )
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Additional Notes |
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Breakdown of Assessment Methods (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
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Exam Information |
Exam Diet |
Paper Name |
Hours & Minutes |
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Main Exam Diet S1 (December) | | 2:00 | |
Summary of Intended Learning Outcomes
- model the motion of robotic systems in terms of kinematics and dynamics
- analyse and evaluate a few major techniques for feedback control, motion planning and computer vision as applied to robotics
- translate a subset of standard algorithms for motion planning, localization and computer vision into practical implementations
- implement and evaluate a working, full robotic system involving elements of control, planning, localization and vision |
Assessment Information
You should expect to spend approximately 42 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. |
Special Arrangements
None |
Additional Information
Academic description |
Not entered |
Syllabus |
The tentative coverage of topics is as follows:
- Kinematics - forward and inverse
- Dynamics
- Control
- Sensing - proprioception, etc.
- Motion planning - basics and sampling based methods
- Motion planning - planning under uncertainty, etc.
- State estimation, localization and mapping
- Implementing SLAM; Multi-modal sensor fusion
- Image acquisition
- Edge detection and segmentation
- Shape description and matching
- Two-view geometry
- Interest points and regions
- Recognition of specific objects
- Visual servoing and ego-motion estimation |
Transferable skills |
Not entered |
Reading list |
H. Choset, K.M. Lynch, S. Hutchinson, G. Kantor, Principles of Robot Motion: Theory, Algorithms, and Implementations.
S. Thrun, W. Burgard and D. Fox, Probabilistic Robotics.
D.A. Forsyth, J. Ponce, Computer Vision: A Modern Approach.
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Study Abroad |
Not entered |
Study Pattern |
Not entered |
Keywords | Not entered |
Contacts
Course organiser | Dr Subramanian Ramamoorthy
Tel: (0131 6)50 9969
Email: sramamoo@inf.ed.ac.uk |
Course secretary | Ms Katey Lee
Tel: (0131 6)50 2701
Email: Katey.Lee@ed.ac.uk |
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© Copyright 2014 The University of Edinburgh - 29 August 2014 4:12 am
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