Hello everyone, I'm Sean. Welcome to Introduction to Robotics lecture. In this video, I will tell you the general information of this course, what previous knowledge you need to have and what you will learn.
We have to hold the course in digital way again, so it's a pity that you cannot access to the labs to see the robots and we cannot see each other in person.
But the digital courses also offer the advantages for resource sharing and reuse.
If you can watch this video, I believe you have got my email. So don't forget our first online meeting on 9th April this Friday at 9 o'clock.
I'm expecting to see you guys. In that time, I will explain the organization of this module, the assignment staff and the exam. Great.
Then let's start. So at the beginning, I want to introduce myself a little bit.
So this is my webpage. I'm a fourth year PhD student in times. This is my second semester to the lecture, to be the lecture of introduction to robotics.
Our group has charged this lecture more than five years. My research field is deep learning based on collaboration, text or manipulation and learn from human.
In here, you can find my publications. If you are interested in any related topic, feel free to talk with me and then let's start.
So you see here, this lecture time is always Friday and we will have 13 lectures in this semester because the digital way I will always upload the lecture videos every Friday in Moodle.
You can arrange your time to watch the videos during the whole week. And for each lecture, there will be several video clips.
Each video is subject-wise. This better enables flexible self-study. And, you know, the lecture belongs to the robot technology module.
This module contains lecture, exercise and the robot practical course. The exercise and the practical course will be carried out alternatively on Friday morning.
So this week, we will have our first online meeting for the exercise and then next week is robot practical course.
I will charge for the exercise and the contents of the, because the contents of the exercise and the lectures are closely related.
And my colleague Yannick, so here we can, sorry, we can find Yannick.
Yannick and the one teacher assistant, Jonas, will charge for the practical course.
And for the lectures, I will take most of the lectures and my colleague, Michael Goiner, his research field is past planning on trajectory generation and he will give two lectures about this topic.
And here is his talk, publications and talks. And then my other colleague, Mark Besterman, he's working on a humanoid robot, the Vulcan robot.
And he's also charging for the robot cup team in our campus. The robot cup team is playing with the football robot and he will give a lecture about the principles of Vulcan.
Actually, the Vulcan lecture is a very high level of robotics instead of introduction to robotics. However, it's great to give you an impression how to fuse the knowledge we learn in this course into the real robot applications.
Okay, so we have seen my colleagues and all the lectures in this course.
Then here you see the big blue button room, you will find them in Moodle.
And then some of the emails and the room number of Professor Junghui Zhang, he's our supervisor, the leader of the Times Group.
And then this is the email of me and Yannick and our secretary.
So if you have any questions and confusion about any part of the lectures, the course, or you expect further discussion of the lecture or of the course, please contact us or contact me directly.
We can set up an online meeting with you. And here is the website of our course and this is the website for Moodle.
So you can find our course lecture in our website in here.
Here, I will always upload all the videos in Moodle and update the information in Moodle, but all the slides and the data and the exercise assignments, I will also upload on this website.
So you can also find information on this webpage.
The next thing is I want to introduce some related courses in Informatical. So like intelligent robotics, hold by Mark Besseman, this course will carry out in the winter semester, which is a higher level of robotics.
It talks about the sensors, how to build an autonomous robot, and you will find many more interesting applications in this lecture.
And then in this year, it's very popular to apply an AI related method to robotic field.
So our institute also provides some artificial intelligence related courses. If you are interested in this, feel free to have a shot.
The next lesson is the previous knowledge of this lecture. The first one is linear algebra.
So from the first lecture, we will talk about the homogeneous transformation, matrix multiplication, inverse matrix dot product, cross product, and these concepts will continually be mentioned in almost every lecture.
And here is a very impressive linear algebra.
In this tutorial, I think these tutorials are the best one in YouTube. So you can click on the slides, then you will find this channel in YouTube.
And then some basics in physics and some related computer skills. So all the coding stuff in our module is working on Linux, so Linux operating system.
And then you need your programming skills like patience. Nowadays, the students always choose patience.
Actually, you also can choose C++. Then MATLAB. Actually, last year, I think no students chose MATLAB to solve the exercise, the task of the exercise.
But if you want, of course, you can solve it by MATLAB. And then you need some good skills and how you know how to exercise to access to Mafiasi and the poor computers.
And then the Vulkan platform is Ubuntu 18.06. This is the Linux system we will work on. So Yannick will explain to you about this system and how to install Rose Melodic in the practical course.
So you will learn all this from the practicals. But if you feel you are short for any of these skills, please prepare first, then it's better to further study.
Great. And then let's go to the most important thing for this introduction video. I want to show you a robot demo. So here is the Thames Pier 2 robot.
It is a humanoid robot. Her name is Trixie. She has two arms and two hand effectors. And regarding the right arm, then you see there is the forearm and forearm and up arm and shoulder and wrist and so on.
So this is a humanoid robot, you see. And the left side is a parallel gripper here. And the right side, you can see this is a five fingered, dexterous hand called shadow hand.
It is one of the most dexterous robot hands in the world. It's a PT still. Yeah, you cannot see the robot in physical right now.
And we usually have a laptop in the first exercise. Therefore, this time I prepared a Thames laptop video in exercise module. In that video, I introduced Thames hardware robots and show many interesting robot videos about the research in Thames and our previous master projects.
After that video, you will have an expression about Thames Lab. I hope you will enjoy the laptop video.
Then I gonna show you the demo. Sorry, it's a bit noisy.
You see the robot grasp the bottle by the left gripper and pour water into the cup and then place the bottle on the desk.
So now the question comes. Can you come up with a way of controlling the arm to move from one location to another like the left arm move from one location to another?
I'll give you five seconds. Five, four, three, two, one. I guess some of you have got some ideas, for example, collaboration, right? Use a joysticker or use a keyboard or use some pedal to control the robot arm move forward or move backward, left or right.
Yes, true.
The first thing is you need to know where the current location of the arm. So if you want to control the robot by teleportation, you need to know where the robot is and where the goal location is.
So you need some variables or you need some parameters to present this location. This is related to a special description of a robot.
And also you see here, PR2 is a quite complicated robot. It has so many different parts, the arms, the torso, the head, and also it has a base. You cannot see the base from the video, but at the bottom, there is a big base and with four wheels.
So assume you have known the location of the base of the robot. So maybe you can get the location of the base by GPS. So how can you get the positions of the other parts of the robot? So if you know the base of the robot, then you want to know where is the left arm of the robot.
This means you need to find the relationships between all these links, all these bodies, all these parts. Therefore, you need to determine a model, the kinematics model, which can describe the relationship of the whole robot, then we can infer the relative position of different parts.
The left arm, you see, moves, you cannot see it. So the left arm moves slowly towards the bottle, but actually in real life, if you see here, if I want to grasp this bottle, I can grasp the bottle this way or this way or this way.
I try to keep my hand fixed, but no. So just imagine, even though the pose of the hand is same, I mean, the bottle is here, then I always grasp the bottle in this way. But the elbow, you see, the pose of the elbow can be very different.
So similar to the robot, even though the final, the pose of the gripper will like this, but the arm, the forearm and the elbow can be in different places, in different locations.
And so given the goal state, and calculate how the joints should be, what's the robot configuration? So this is inverse kinematics.
And when the whole arm is moving, let's see here, it generates dynamics. We have to consider the external force, the mass of the robot, the mass of the bottle, the friction, the inertial forces, etc.
And then you see the arm moves along a smooth trajectory. How can the robot generate a collision-free and smooth trajectory? This is related to trajectory planning and trajectory generation.
And let's see the video again. You see, the left arm moves very stably, not shakenly, not like this. So this is involved into control theory, how to control the robot stably.
So everything in this video looks very simple, but behind this, there are lots of stuff, the basis of robotics. I don't know whether you see here.
Oh, so I need to play the video again. This is really the last time I play this video. You see here is what you appear to.
It conducts the same trajectory like the real robot. How will you build a robot model for realisation? And this is also related to how to represent the kinematics of the system, the robot description.
And you will have fun experiments of the robot description file in our practicals.
Okay, so this is a very indicative example to show you the contents can be involved in our course. I have mentioned some terminologies, the spatial description, kinematics, dynamics, and the task-oriented trajectory planning, trajectory generation and control concepts.
And then at the last, you will learn how to program for controlling the robot. Everything will conduct on the robot operation system platform.
And then you will learn how to write a robot description file, how to set up your robot in simulation, and we will go through all this content in this lecture.
So great, this is the end of this introduction. Please organise your time. I will try my best to share experience and explore the essence of robotics with you.
And I believe we still can have a very productive semester. So see you guys on Friday.