Self Driving and ROS 2 - Learn by Doing! Odometry & Control

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Antonio Brandi

20:43:11

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1. Introduction

1. Course Motivation.mp4

02:53

2. The Self-Driving Program.mp4

03:29

3. Course Presentation.mp4

06:16

4. Meet your Teacher.mp4

02:27

5. [EXTRA] Boost your Robotics Software Developer Career.html

6. Get the Most out of the Course.mp4

03:40

7. Course Material.html

2. Setup

1. Install Ubuntu on Virtual Machine.html

2. Install Ubuntu on Dual Boot.html

3. Install ROS 2.mp4

03:38

4. Configure the Development Environment.mp4

09:01

3. Introduction to ROS 2

1. Why a Robot Operating System.mp4

04:18

2. What is ROS 2.mp4

03:13

3. Why a NEW Robot Operating System.mp4

04:58

4. ROS 2 Architecture.mp4

03:12

5. Hardware Abstraction.mp4

02:53

6. Low-Level Device Control.mp4

01:22

7. Messaging Between Process.mp4

07:00

8. Package Management.mp4

01:41

9. Architecture of a ROS 2 Application.mp4

02:59

10. LABCreate and Activate a WorkspaceLAB.mp4

11:18

11. PYSimple PublisherPY.mp4

18:16

12. C++Simple PublisherC++.mp4

23:14

13. PYSimple SubscriberPY.mp4

13:15

14. C++Simple SubscriberC++.mp4

15:44

4. Locomotion

1. Robot Locomotions.mp4

05:54

2. Mobile Robots.mp4

04:15

3. Friction Effects.mp4

09:54

4. Robot Description.mp4

03:33

5. URDF.mp4

04:41

6.1 STL Gazebo.zip

6. LABCreate the URDF ModelLAB.mp4

31:24

7. Rviz 2.mp4

05:32

8. Parameters.mp4

01:55

9. PYParametersPY.mp4

13:33

10. C++ParametersC++.mp4

17:04

11. LABROS 2 Parameter CLILAB.mp4

06:36

12. LABVisualize the RobotLAB.mp4

09:07

13. Launch Files.mp4

02:01

14. LABVisualize the Robot with Launch FilesLAB.mp4

20:23

15. Gazebo.mp4

04:48

16.1 bumperbot.urdf.zip

16.2 Solidworks URDF Exporter.html

16.3 Solidworks URDF Exporter Tutorial.html

16. LABSimulate the RobotLAB.mp4

14:59

17. LABLaunch the SimulationLAB.mp4

11:10

5. Control

1. ROS 2 Control.mp4

08:43

2. Control Types.mp4

05:36

3. LABros2 control with GazeboLAB.mp4

13:57

4. YAML Configuration File.mp4

02:43

5. LABConfigure ros2 controlLAB.mp4

12:11

6. LABLaunch the ControllerLAB.mp4

05:54

7. LABros2 control CLILAB.mp4

07:53

6. Kinematics

1. Robot Kinematics.mp4

03:52

2. Pose of a Mobile Robot.mp4

03:53

3. Translation Vector.mp4

04:46

4. LABIntroduction to TurtlesimLAB.mp4

11:05

5. PYTranslation VectorPY.mp4

16:34

6. C++Translation VectorC++.mp4

28:13

7. Rotation Matrix.mp4

08:14

8. PYRotation MatrixPY.mp4

10:29

9. C++Rotation MatrixC++.mp4

10:22

10. Transformation Matrix.mp4

03:39

7. Differential Kinematics

1. Differential Kinematics.mp4

01:36

2. Velocity of a Mobile Robot.mp4

03:17

3. Linear Velocity.mp4

06:04

4. Angular Velocity.mp4

05:28

5. Velocity in World Frame.mp4

05:05

6. Differential Forward Kinematics.mp4

04:08

7. Simple Speed Controller.mp4

01:54

8. PYSimple Speed ControllerPY.mp4

24:12

9. C++Simple Speed ControllerC++.mp4

30:53

10. LABLaunch the Simple ControllerLAB.mp4

14:03

11. LABTeleoperating with JoystickLAB.mp4

15:40

12. LABUsing the diff drive controllerLAB.mp4

22:28

8. TF2 Library

1. The TF2 Library.mp4

05:23

2. Operations with Transformations.mp4

05:31

3. Static and Dynamic Transformations.mp4

03:00

4. PYSimple TF2 Static BroadcasterPY.mp4

14:09

5. C++Simple TF2 Static BroadcasterC++.mp4

14:09

6. PYSimple TF2 BroadcasterPY.mp4

13:09

7. C++Simple TF2 BroadcasterC++.mp4

13:21

8. ROS 2 Services.mp4

05:43

9. PYService ServerPY.mp4

19:10

10. C++Service ServerC++.mp4

21:05

11. PYService ClientPY.mp4

18:36

12. C++Service ClientC++.mp4

23:31

13. PYSimple TF2 ListenerPY.mp4

20:06

14. C++Simple TF2 ListenerC++.mp4

23:12

15. Angle Rapresentations.mp4

01:41

16. Euler Angles.mp4

03:04

17. Quaternion.mp4

03:54

18. PYEuler to QuaternionPY.mp4

11:47

19. C++Euler to QuaternionC++.mp4

12:39

20. LABTF2 ToolsLAB.mp4

07:31

9. Odometry

1. Where is the Robot.mp4

03:01

2. The Local Localization Challenge.mp4

05:22

3. Wheel Odometry.mp4

07:49

4. Differential Inverse Kinematics.mp4

05:33

5. PYDifferential Inverse KinematicPY.mp4

18:54

6. C++Differential Inverse KinematicC++.mp4

20:40

7. Wheel Odometry - Position.mp4

03:17

8. Wheel Odometry - Orientation.mp4

03:38

9. PYWheel OdometryPY.mp4

10:35

10. C++Wheel OdometryC++.mp4

10:47

11. PYPublish Odometry MessagePY.mp4

14:47

12. C++Publish Odometry MessageC++.mp4

16:16

13. PYBroadcast Odometry TransformPY.mp4

11:45

14. C++Broadcast Odometry TransformC++.mp4

13:15

10. Probability for Robotics

1. Motivation.mp4

07:09

2. Random Variables.mp4

08:55

3. Conditional Probability.mp4

07:18

4. Probability Distributions.mp4

08:40

5. Gaussian Distributions.mp4

04:52

6. Total Probability Theorem.mp4

05:44

7. Bayes Rule.mp4

05:11

8. Sensor Noise.mp4

02:37

9. PYAdding Noise to Robot MotionPY.mp4

07:31

10. C++Adding Noise to Robot MotionC++.mp4

11:33

11. LABLaunch Noisy ControllerLAB.mp4

13:29

12. LABOdometry ComparisonLAB.mp4

07:26

11. Sensor Fusion

1. Advantages of having Multiple Sensors.mp4

06:28

2. Gyroscope.mp4

03:38

3. Accelerometer and IMU.mp4

03:30

4.1 bumperbot.urdf.zip

4. LABSimulate IMU SensorIMU.mp4

15:46

5. Kalman Filter.mp4

06:28

6. PYFilter InitializationPY.mp4

15:00

7. C++Filter InitializationC++.mp4

20:26

8. Measurement Update.mp4

02:23

9. PYMeasurement UpdatePY.mp4

05:22

10. C++Measurement UpdateC++.mp4

05:17

11. State Prediction.mp4

02:33

12. PYState PredictionPY.mp4

09:16

13. C++State PredictionC++.mp4

10:15

14. LABLocalization with Kalman FilterLAB.mp4

06:29

15. Extended Kalman Filter (EKF).mp4

04:24

16. PYIMU RepublisherPY.mp4

06:45

17. C++IMU RepublisherC++.mp4

08:44

18.1 ekf.zip

18. LABSensor Fusion with robot localizationLAB.mp4

24:31

12. Conclusions

1. Recap.mp4

02:34

2. Whats Next.mp4

02:09

3. BONUS Lecture.html

Description

Create a ROS2 based Self-Driving robot and learn about Robot Localization and Sensor Fusion using Kalman Filters

What You'll Learn?

Create a Real Self-Driving Robot
Mastering ROS2, the last version of the Robot Operating System
Implement Sensor Fusion algorithms
Simulate a Self-Driving robot in Gazebo
Programming Arduino for Robotics Applications
Use the ros2_control library
Develop a Controller
Odometry and Localization
Kalman Filters and Extended Kalman Filter
Probability Theory
Differential Kinematics
Create a Digital Twin of a Self-Driving Robot
Master the TF2 library

Who is this for?

Self-Driving enthusiast

Makers and Hobbists keen on robotics

Software developers taht wants to learn ROS 2 and Robotics

Students or Engineers that wants to learn how to buid a robot from scratch

Developers that already knows ROS 2 and that want to use it in a real world application

ROS Developers that want to learn and migrate to ROS 2

Robotics Engineers that wants to develop skills in Autonomous Navigation

Beginner Python developers curious about Self-Driving

Beginner C++ developers curious about Self-Driving

What You Need to Know?

Basic knowledge of Python or C++

Basic knowledge of Linux

No prior knowledge of ROS or ROS 2 required

No prior knowledge of Robotics theory required

No hardware required. All the course can be followed also using only the PC

More details

Description
Would you like to build a real Self-Driving Robot using ROS2, the second and last version of Robot Operating System by building a real robot?

Would you like to get started with Autonomous Navigation of Robot and dive into the theoretical and practical aspects of Odometry and Localization from industry experts?

The philosophy of this course is the Learn by Doing and quoting the American writer and teacher Dale Carnegie
Learning is an Active Process. We learn by doing, only knowledge that is used sticks in your mind.

In order for you to master the concepts covered in this course and use them in your projects and also in your future job, I will guide you through the learning of all the functionalities of ROS both from the theoretical and practical point of view.

Each section is composed of three parts:
Theoretical explanation of the concept and functionality
Usage of the concept in a simple Practical example
Application of the functionality in a real Robot

There is more!

All the programming lessons are developed both using Python and C++ . This means that you can choose the language you are most familiar with or become an expert Robotics Software Developer in both programming languages!

By taking this course, you will gain a deeper understanding of self-driving robots and ROS 2, which will open up opportunities for you in the exciting field of robotics.
Who this course is for:
Self-Driving enthusiast
Makers and Hobbists keen on robotics
Software developers taht wants to learn ROS 2 and Robotics
Students or Engineers that wants to learn how to buid a robot from scratch
Developers that already knows ROS 2 and that want to use it in a real world application
ROS Developers that want to learn and migrate to ROS 2
Robotics Engineers that wants to develop skills in Autonomous Navigation
Beginner Python developers curious about Self-Driving
Beginner C++ developers curious about Self-Driving

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Automotive Engineering

Antonio Brandi

Instructor's Courses

Hey, I'm Antonio Brandi and I'm glad you are here!I am a Robotics Engineer specialized in Autonomous Navigation for Robot applications with several years of experience working with ROS and mobile robots both for industrial and commercial applications.Actually I'm working with the brightest minds in the field of ROS and Robotics at Pal Robotics.Despite having an Engineering background, I'm a ROS self learner and I know how tough and demotivating it can be rushing through all the concepts and documentations. Furthermore, I genuinely think that the best way to learn something is to scratch your head and build something real that you can interact and play with.That's why my courses will handle both the required theoretical background and its implementation in the real world!Remember to have fun and experimenting while learning

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