Introduction to Robotics

Queensland University of Technology via EdCast

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Details

This course may be unavailable.

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Provider

EdCast
Pricing

Free Online Course
Languages

English
Certificate

Certificate Available
Duration & workload

9 weeks, 4-8 hours a week
Sessions

Finished

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Overview

This course is an introduction to the exciting world of robotics and the mathematics and algorithms that underpin it. You’ll develop an understanding of the representation of pose and motion, kinematics, dynamics and control. You’ll also be introduced to the variety of robots and the diversity of tasks to which this knowledge and skills can be applied, the role of robots in society, and associated ethical issues. If you have access to a Lego Mindstorms kit (9797) you will be able to build a simple robot arm and write the control software for it.

Combined with the Robotic Vision MOOC, this course is based on a 13 week undergraduate course Introduction to Robotics at the Queensland University of Technology.

Course Outcomes

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

describe and 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
design a robot joint control system and understand the nature of the rigid-body forces acting on a robot arm (optional advanced material)
reflect on the future role and development of robots in human society
apply the mathematical, algorithmic and control principles of robot arm manipulators to implement a working robot through physical construction and software development (applies to optional project)

Pathways through the course

You can follow three paths through the MOOC:

You can audit the course: Register and have access to all the content, lectures, quizzes and programming assignments which you can view at your leisure. You do not necessarily have to submit the assessments. You will not receive a certificate at the end of the course.
To receive a certificate of completion you should register for the course, study all the content and successfully complete at least four assessable quizzes and four programming assignments.
An additional option is to complete a robot building project which will be peer assessed.

Workload

You should spend about 4–8 hours per week on this course. Depending on your level of skill with MATLAB and programming in general, your studies might include:

2 hours viewing the lecture videos and completing the self-assessment quizzes;
30 minutes for each of six weekly assessable quizzes
2 hours for each of six weekly programming assignments;
1–2 hours building the robot or vision system (optional project) or doing further research and/or communicating on forums.

Time required for the last two items will depend on your level of skill with MATLAB and programming in general.

Certificate of Achievement

Throughout the course you will be asked to complete quizzes and programming exercises. These will be automatically marked. If you pass 4 quizzes and 4 programming assignments you will receive a Certificate of Achievement. The programming assignments will consist of several MATLAB tasks and will be based on the lecture content for that week.

The robot project will be peer assessed but doesn’t count towards the Certificate of Completion.

Assumed knowledge

To complete the MOOC you should know some basic programming (either of MATLAB or of an object-oriented programming language) and some of the following areas of maths: matrices, vectors and spaces, eigenvalues and eigenvectors. We’ve included links to Khan Academy on these topics. We believe this knowledge will be necessary to complete the course, and recommend that you view these before Week 1 begins, but you might prefer to watch them on an ‘as needed’ basis after you view our content.

Vectors
Matrices:
- basic matrix operations including multiplication and inversion
- zero and identity matrices
- vector transformations with matrices
- familiarity with the concepts of eigenvalues and eigenvectors.

Note: A free version of MATLAB will be available for the duration of the course. Also, Professor Corke’s textbook (not essential) will be available at a significant discount.

Requirements Hardware

Computer: You will need a computer that is capable of running MATLAB. For System Requirements, visit the MathWorks’ System Requirements page.
Lego Mindstorms: To complete the optional project part of this course you will need access to a robotics development kit – we work with Lego Mindstorms NXT and EV3 kits (approximately $300 to $500 depending on the source. Alternatively you can use an Arbotix based design which uses Dynamixel servos, 3D printed parts and an Arbotix microcontroller controller board.

Software

MATLAB. This is a proprietary technical computing and visualisation package developed by The Mathworks Inc. It is widely used in the engineering industry, in scientific research and for undergraduate education. MATLAB is a core part of the course and is available for free to students studying this course. It is used to illustrate techniques in the lectures (via screencasts) and also for the assignment (you need to write programs and submit them for automatic grading). A free MATLAB licence and software for installation will be available when you enrol in the course.
Open source toolboxes for MATLAB. These will also be available from the course site.
For the robot project, RWTH Mindstorms NXT Toolbox, open source from the Mindstorms website.

Other

Textbook (optional). Access to the textbook written by Professor Peter Corke (2011), Robotics, Vision and Control: Fundamental Algorithms in MATLAB (Springer) is optional, but considered beneficial.

Syllabus

This week we will look at where the idea of robots has come from, and the difference between fictional and real robots. We’ll look at a number of useful real world robots and what they do. Then we get started on the problem of describing where things are in the world. It’s critical to know where a robot is, and where are the things that it needs to deal with. We’ll start simply and consider the case of objects in a 2-dimensional plane. The skills you’ll learn and the tools we’ll use will be essential for the MATLAB assignments and the project.

Lecture 1: Introduction
Lecture 2: Where things are in 2D

Week 2

This week we talk about how to describe the position and orientation, the pose, of objects in 3 dimensions, which is considerably more difficult than the 2-dimensional case. We also discuss how we can compute object poses that change smoothly with time, for instance to guide the arm of a robot from one pose to another.

Lecture 3: Where things are in 3D
Lecture 4: Time varying coordinate frames

Week 3

This week we’ll finish our introduction to the fundamentals of describing pose by talking about how we can measure the motion of objects moving in the 3-dimensional world using accelerometers and gyroscopes. Then we’ll get started with robot arms and how to describe the 3D-pose of the robot’s gripper, or end-effector, given knowledge of its structure and its joint angles.

Lecture 5: Measuring the motion of things
Lecture 6: Robot arms & forward kinematics

Week 4

This week we consider the inverse problem to the last lecture, if we know the pose of the end robot’s end-effector how do we work out what the joint angles should be. Then we consider the relationship between the velocity of the joints and the velocity of the end-effector, which raises the issue of how to describe the rate of change of pose. To keep things simple we consider the 2-dimensional case.

Lecture 7: Inverse kinematics & robot motion
Lecture 8: Robot velocity in 2D: introducing the manipulator Jacobian

Week 5

This week we finish off our discussion of robot kinematics by extending what we learnt in the last lecture, for 2-dimensions, and consider how to describe the rate of change of 3D-pose which turns out to be a six-dimensional vector. So far we have just assumed that robot joints can be set to some particular angle, now it’s time to consider the underlying mechatronic system and control theory that enables this to happen.

Lecture 9: Robot velocity in 3D
Lecture 10: Robot joint control

Week 6

This week we extend the work of the last lecture to consider other forces that act on a robot arm and can effect the joint control system, for example gravity, friction and inertia. We finish with a discussion about the future of robotics, where the technology is headed, how robots can help solve some of the big problems facing our societies, and some ethical considerations that arise from the application of robotics.

Lecture 11: Rigid body dynamics
Lecture 12: The future of robots