Robotic Vision in QUT MOOC

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Course outline

This course includes an introductory week, followed by six weeks of lectures. Each week includes two video lectures, quizzes and MATLAB programming exercises.

  • Getting started: Pre-course activities are available in the week prior to week 1.
  • These activities help you prepare for the course.
  • Week 1: Robotic vision and Getting images into a computer
  • Week 2: Image processing and Spatial operators
  • Week 3: Feature extraction and What is color?
  • Week 4: Image formation and Image geometry
  • Week 5: 3D vision and Robot joint control
  • Week 6: Vision and motion .
  • Final week: All quiz and MATLAB assessments must be submitted. Participants who have completed the optional projects in both this course and Introduction to robotics can do the extension activity and combine the output of both projects.

Learning outcomes

By the end of this course you should be able to:

  • describe and explain the utility of vision as a sensor for robots and evaluate the challenges inherent in visual information
  • describe the underlying principles of common image processing techniques and the circumstances where they are applicable, the rationale for reducing image pixels to features and the principles of image region segmentation and feature extraction
  • describe the mathematical and geometric principles underlying the formation of images
  • describe the principles of continuous spectra, trichromatic vision and the separation of chrominance and luminance information
  • demonstrate the software skills to import images from a variety of sources into MATLAB and perform a number of image processing and feature extraction algorithms using MATLAB
  • apply the mathematical and algorithmic and control principles of computer vision to implement a working vision system (applies to optional project)
  • integrate the robot arm and robotic vision system into a functional system in which the desired object is recognised and the robot moves to it (applies to optional projects).

Before the course

We recommend that you review these Khan Academy instructional videos on mathematics before the course starts:

Assessment

Throughout the course you’ll have the opportunity to complete assessable quizzes and programming exercises. These will be marked automatically. The programming exercises will consist of MATLAB tasks and will be based on the lecture content for that week.

Certificate of participation

If you complete the assessment successfully you will receive a certificate of participation. The certificate does not earn credit points towards a QUT qualification. The overall assessment is worth a total of 240 points (120 points for assessable quizzes and 120 points for MATLAB programming tasks). You need to achieve an overall score of 50% (120 points). The quizzes and programming tasks are weighted equally, so it does not matter how you make up your 120 points.

Optional project

As an additional project you can build a working robotic vision system using your computer, a connected camera and MATLAB software you write in MATLAB. This isn’t a requirement for the certificate of participation, however it’s a valuable opportunity to apply your knowledge and skills. If you completed the optional project in the Introduction to robotics open online course and have a robot arm, you can integrate it with your vision system to create a simple, visually guided robot.

Workload

You should spend about 4-8 hours per week on this course. Depending on your understanding of MATLAB and programming in general your studies might include:

  • 2 hours viewing the lecture videos and completing the optional quiz questions to check your understanding
  • 30 minutes for each of the six weekly assessable quizzes
  • 2 hours for each of the six weekly programming exercises
  • 1-2 hours building the robot (optional project) or doing further research and/or communicating on the discussion forum.

Hardware requirements

You’ll need a computer capable of running MATLAB. Visit the MathWorks website to check the MATLAB system requirements.

If you plan to do the optional project, you’ll need a webcam attached to the computer or a mobile phone and the ability to transfer images to the computer.

Software requirements

You’ll need this software:

  • MATLAB, a proprietary technical computing and visualisation package, is a core requirement. MathWorks have generously provided a downloadable license to use MATLAB for free for the duration of the course. You can access the licence and the software from the course site once you have registered
  • open source toolboxes for MATLAB. These will be available from the course site.

Textbook

Access to the textbook written by Professor Peter Corke, Robotics, Vision and Control: Fundamental Algorithms in MATLAB (2011, Springer) is optional, but considered beneficial. The textbook will be available for purchase at a significant discount after you’ve registered. The course includes free extracts from the textbook for you to read online while studying with Peter.

Facilitator

Peter Corke is Professor of Robotic Vision at QUT and Director of the Australian Research Council Centre of Excellence for Robotic Vision. He wrote the textbook Robotics, Vision and Control (2011) and authored the MATLAB toolboxes for Robotics and Machine Vision .

Peter’s long-term research interests are in vision based robot control, field robotics and wireless sensor networks.

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Author: iotmaker

I am interested in IoT, robot, figures & leadership. Also, I have spent almost every day of the past 15 years making robots or electronic inventions or computer programs.

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