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Robotics: Science and Systems (R:SS) Course Webpage

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; visual geometry, recognition of textured objects, shape matching and object categorization. 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. NOTE: This is a 20 pt course, as opposed to the standard 10 pt courses since this covers two introductory topics: robotics and vision and a practical element.

Course descriptor

When and Where?

When: 9:00 - 10:50 (with 10 min. break) on Mondays and Thursdays.

Where:  David Hume Tower Room LG.06 (50 George Square)

First Lecture: 15 Sep (Mon) 9:00-10:50 @  David Hume Tower LG.06

Practical times

Monday 11.00 - 13.00 (AT 3.01)

Thursdays 11.00 - 13.00 (AT 3.01)

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

Written Examination 50
Assessed Practicals 40
Assessed Assignments 10

Course Lecturers

Professor Sethu Vijayakumar - sethu.vijayakumar[at]ed.ac.uk

Dr Subramanian Ramamoorthy - s.ramamoorthy[at]ed.ac.uk

Professor Chris Williams - ckiw[at]inf.ed.ac.uk

Demonstrators

Vladimir Ivan - v.ivan[at]sms.ed.ac.uk

Andreea Radulescu - a.radulescu[at]sms.ed.ac.uk

Technical Support

Garry Ellard - gde[at]inf.ed.ac.uk

Tony Shade - ashade[at]inf.ed.ac.uk

 

Lecture plan (provisional)

Lecture time: 9:00 - 10:50 (with 10 min. break) on Mondays and Thursdays.

Week

Date

Lecture notes

Lecturer

Lecture topic

Milestones

1

15-Sep-2014

Introduction to Robotics
Transformations

Sethu Vijayakumar

Introduction; Notations, Transformations, Rotations (1h15mim), Primer for the Practicals (30min)

 Kit handout

1

18-Sep-2014

Introduction to Vision  (slides 2x2)
Image Formation (slides 2x2)

Chris Williams

Image acquisition: basic world-to-image geometry, lenses, reflection from surfaces, color spaces (1h); Single camera geometry (intrinsic and extrinsic parameters)

 Kit handout

2

22-Sep-2014


 

 Edinburgh Center for Robotics LAUNCH event

 

2

25-Sep-2014

Two View Geometry, (slides 2x2)

Chris Williams

Two-view geometry: setting, notion of point correspondences, transformation classes for planar objects: similarity, affine, homography (1h) Two-view geometry: fundamental matrix (properties and estimation), invariance classes, invariants for planar configurations of points and lines

 

3

29-Sep-2014

Kinematics,

Practical Implementation

Sethu Vijayakumar,

Vladimir Ivan

Kinematics (Forward, Inverse), Jacobian, Operational Space, Null Space, Optimality Principles (1h); Practicals Feedback and Help

Milestone 1 (Mon.)

3

2-Oct-2014

Interest Points, (2x2)

Chris Williams

Interest points and regions: general concept, plain Harris, scale-invariant Harris. Affine-invariant MSER.

Milestone 1 (Thu.)

4

6-Oct-2014

 Path Planning

 

Subramanian Ramamoorthy

Path planning and motion planning in c-space

 

 

4

9-Oct-2014

Feature Matching

Chris Williams

Describing and matching local features: SIFT descriptor, RANSAC matching.

 

5

13-Oct-2014

Kinematics (cont'd)
Practical Implementation

Sethu Vijayakumar,

Vladimir Ivan

Kinematics, Jacobian, Operational Space, Null Space, Optimality Principles, Multi Objective Planning (1h); Practicals Feedback and Help

 Milestone 2 (Mon.)

5

16-Oct-2014

Affine features
Specific object recognition

Chris Williams

Specific object recognition: global descriptors, interest point/region descriptors (SIFT, moments), matching interest points/regions, filtering mismatches with geometric consistency (local consistency tests, global consistency tests with RANSAC)

Milestone 2 (Thu.)

Homework 1 assigned

6

20-Oct-2014

Edge detection

Chris Williams

Specific object recognition: correspondence expansion, how to do it very fast for large-scale object/image retrieval (1h); Implementation issues (1h)

 

6

23-Oct-2014

Dynamics

Sethu Vijayakumar

Dynamics: Point mass, PID, Newton Euler, Joint Space, Optimal Operational Space Control, Non-holonomic sytems


7

27-Oct-2014

Control
SOC Additional Notes

Sethu Vijayakumar

Dynamics (cont'd)  (1h);  Control:  Intro to Optimal Control, HJB equations, LQR (1h)

Milestone 3 (Mon.)

7

30-Oct-2014

Image segmentation

Chris Williams

Edge detection and segmentation: simple thresholding, convolutions, canny, graph-cut, grab-cut

Milestone 3 (Thu.)

8

3-Nov-2014

Motion Planning

Subramanian Ramamoorthy

Sampling based motion planning, compositional methods

 

8

6-Nov-2014

Object categorization

Chris Williams

Object categorization taster: problem definition and challenges, two simple models (generalized hough transforms, sliding-windows), learning parameters from training data, part-based models, the need for weak supervision.

 Homework 1 due (6th Nov)

9

10-Nov-2014

State Estimation

 

Subramanian Ramamoorthy

State estimation, particle filters

Milestone 4 (Mon.)

 

9

13-Nov-2014

Localization and Mapping

Subramanian Ramamoorthy

Localisation and Mapping

Milestone 4 (Thu.)

10

17-Nov-2014

Exam Q&A

SV, SR, CW

Localisation and Mapping

Homework 1 feedback to be handed out

11
24-Nov-2014


Final Demo: Practice [Please complete your HW2 Write Up by now!]


 11  27-Nov-2014  Competition   Final Practical Demo / Competition  

Final Competition

Homework 2 (Practical report) due

           

 

 

 

 Recommended Texts

 
  • Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G., Robotics: Modelling, Planning and Control
  • 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, 2nd edition, Pearson 2012.
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