Skip to 0 minutes and 4 seconds The world is going to need a lot of people who understand robotics. Are you up for that challenge? The robotics industry is going through explosive growth at the moment. As the capability of robots increases, we’re going to see them play a more and more important part in all of our lives. If you love figuring out how things work, then you’ll enjoy learning the mathematics behind how robots move. Try out your programming skills in practical MATLAB assignments, and program your robot to do a useful task. My name is Professor Peter Corke, join me in the exciting challenge of making robots move.
Introducing Robotics: Making Robots Move
The world needs people who understand how to get robots moving.
Duration
3 weeksWeekly study
3 hours
Introducing Robotics: Making Robots Move
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Discover how robots can be programmed to move.
Making robots move requires both mathematical knowledge and programming skills. We begin with the problem of describing where things are in the world. Starting simply, we consider objects in a two-dimensional plane, exploring the concepts of position, pose, rotation, and translation.
Robot movement relies on the principles of kinematics – the motion of a body or bodies. You’ll program forward kinematics equations in MATLAB and learn approaches to inverse kinematics.
We examine types of motion in 2D, and dive into some principles of joint control theory. We finish with a taste of 3D robotics!
What topics will you cover?
- Geometry and vectors for robotics
- Position, pose, orientation, rotation and translation: describing where things are in the world.
- Types of robots: forms and functions
- Forward and inverse kinematics
- Types of motion in 2D
- Joint control
- A taste of 3D robotics
Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Explain what robots are and what they can do.
- Describe mathematically the position and orientation of objects and how they move.
- Describe mathematically the relationship between robot joint coordinates and robot tool pose.
Who is the course for?
This course assumes that you are familiar with concepts from advanced high-school mathematics or engineering; in particular, analytic geometry and linear algebra (including points, vectors, matrices, matrix-vector and matrix-matrix multiplication, and linear transformations).
You’ll also need to know how to program in MATLAB to complete the practical exercises. You won’t need to download the MATLAB software to complete this course (unless you already have it and wish to use it), as you will be linked directly into an online version of MATLAB through FutureLearn.
What software or tools do you need?
Everything you need to succeed in this course is provided, or can be downloaded for free. If you’d like to attempt the exercises throughout this course, you will be using a program called MATLAB. All exercises are embedded in the course, so you don’t need to have MATLAB to participate.
However, if you’d like to follow along with Professor Corke’s MATLAB demonstrations, work on the exercises, or explore topics on your own, MathWorks has provided a licence for MATLAB Online for this course. We will guide you through the setup of MATLAB and the Robotics Toolbox at the beginning of the course. The use of MATLAB is what will really give you a powerful learning experience, letting you try out the exercises and examples provided.
If you have not used MATLAB before, and would like to take a two-hour introductory course, please check out the MATLAB Academy’s MATLAB Onramp course. This covers the MATLAB basics with walk-through activities. This is an optional activity.
Who will you learn with?
Professor of Robotic Vision at QUT and Director of the Australian Centre for Robotic Vision (ACRV). Peter is also an IEEE fellow and on the editorial board of several robotics research journals.
PhD Candidate with the Australian Centre for Robotic Vision researching towards robust visual object recognition to facilitate useful robotic tasks.
Dr Pepperell completed his PhD in robotic vision at QUT in 2016, with a research focus in vision-based place recognition.
Who developed the course?
Queensland University of Technology
QUT is a leading Australian university ranked in the top 1% of universities worldwide by the 2019 Times Higher Education World University Rankings. Located in Brisbane, it attracts over 50,000 students.
Established
1989Location
Brisbane, AustraliaWorld ranking
Top 180Source: Times Higher Education World University Rankings 2019
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