Welcome to Introduction to Vision and Robotics (2021-2022)[SEM1]
Hello Blackboard Guest, we are pleased to welcome you to Introduction to Vision and Robotics (2021-2022)[SEM1].
My name is Chris Lu and I am the Lecturer for the "Introduction to Vision and Robotics" course. During this course, you will learn the basics of image processing and robotics. You will also learn about two software platforms:
1) OpenCV: A library of programming functions available in both Python and C++, mainly aimed at real-time computer vision.
2) Robot Operating Software (ROS): A real-time platform that provides services designed for analysis and control of robotic systems and includes services such as hardware abstraction, low-level device control, real-time communication between processes, and package management.
The course has three practical assignments starting in Week 4. The assignments are not marked. You will have a week to work on them and later that week an online session will be held to answer your questions and explain the final solution to the assignment. The aims of these sessions are: (1) practice coding with the aforementioned software platforms and (2) get ready for your final project. The practical sessions are held online and you can attend or watch the recorded videos.
Towards the end of the course, you will work on a project that combines image processing and computer algorithms to allow a robot to perform a specific task. For example, your system could have a 2D camera that detects an object for the robot to pick up.
Learning Outcomes
On successful completion of this course, you should be able to:
1. Students will be able to recall and explain the essential facts, concepts and principles in robotics and computer vision, demonstrated through written answers in examination conditions.
2. Students will be able to describe and evaluate the strengths and weaknesses of some specific sensor and motor hardware; and some specific software methods for sensory processing and motor control, demonstrated through written answers in examination conditions.
3. Students will be able to employ hardware (e.g. cameras, robots) and software (e.g. Matlab,robot simulator) tools to solve a practical problem of sensory-motor control, and will show a working system in a practical class.
4. Students will, in writing a joint report, identify problem criteria and context, discuss design and development, test, analyse and evaluate the behaviour of the sensory-motor control system they have developed.
For this course, we use the "flipped classroom" method. A flipped or inverted classroom is a type of blended learning focused on student engagement and active learning, where you are introduced to content at home and practice working through it in online supervised sessions. In a common Flipped Classroom scenario, students watch pre-recorded videos at home (all available here), then come to the online classes armed with questions and at least some background knowledge.
Flipped Classroom
What Students Might Do At Home In A Flipped Classroom:
Watch the online lectures
Review the online course material
Read physical or digital texts
Participate in online discussions on Piazza
Work on practical assignments
What Students Might Do At the Class and Tutorial Sessions In A Flipped Classroom:
Ask questions
Skill practice (guided or unguided by the lecturer)
Debate
Peer assessment and review
