Self Driving and ROS – Learn by Doing! Odometry & Control

سرفصل های دوره

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

1. Introduction

1. Course Motivation

2. The Self-Driving Program

3. Course Presentation

4. Meet your Teacher

5. Get the Most out of the Course

6. Course Material.html

2. Setup

1. Install Ubuntu on Virtual Machine.html

2. Install Ubuntu on Dual Boot.html

3. Install ROS

4. Configure the Development Environment

3. ROS Introduction

1. Why a Robot Operating System

2. What is ROS

3. Hardware Abstraction

4. Low-Level Device Control

5. Messaging between Process

6. Package Management

7. Architecture of a ROS Application

8. LABCreate and Activate a WorkspaceLAB

9. PYSimple PublisherPY

10. C++Simple PublisherC++

11. PYSimple SubscriberPY

12. C++Simple SubscriberC++

4. Locomotion

1. Robot Locomotions

2. Mobile Robots

3.1 L27 Friction Effects.pdf

3. Friction Effects

4. Robot Description

5. URDF

6. LABCreate the URDF ModelLAB

7. RViz

8. Parameter Server

9. LABParameter ServerLAB

10. LABVisualize the RobotLAB

11. Launch Files

12. LABVisualize the Robot with Launch FilesLAB

13. Gazebo

14. LABSimulate the RobotLAB

15. LABLaunch the SimulationLAB

5. Control

1. ROS Control

2. Control Types

3. LABROS Control with GazeboLAB

4. YAML Configuration File

5. LABYAML Configuration FileLAB

6. LABLaunch the ControllerLAB

6. Kinematics

1. Robot Kinematics

2. Pose of a Mobile Robot

3. Translation Vector

4. LABIntroduction to TurtlesimLAB

5. PYTranslation VectorPY

6. C++Translation VectorC++

7.1 L52 Rotation Matrix.pdf

7. Rotation Matrix

8. PYRotation MatrixPY

9. C++Rotation MatrixC++

10. Transformation Matrix

7. Differential Kinematics

1. Differential Kinematics

2. Velocity of a Mobile Robot

3.1 L58 Linear Velocity.pdf

3. Linear Velocity

4.1 L59 Angular Velocity.pdf

4. Angular Velocity

5.1 L60 Velocity in World Frame.pdf

5. Velocity in World Frame

6.1 L61 Differential Forward Kinematics.pdf

6. Differential Forward Kinematics

7. Simple Speed Controller

8. PYSimple Speed ControllerPY

9. C++Simple Speed ControllerC++

10. LABTeleoperating with JoystickLAB

11. LABUsing the diff drive controllerLAB

8. TF Library

1. The TF Library

2. Operations with Transformations

3. Static and Dynamic Transformations

4. PYSimple TF Static BroadcasterPY

5. C++Simple TF Static BroadcasterC++

6. ROS Timer

7. PYROS TimerPY

8. C++ROS TimerC++

9. PYSimple TF BroadcasterPY

10. C++Simple TF BroadcasterC++

11. ROS Services

12. PYService ServerPY

13. C++Service ServerC++

14. PYService ClientPY

15. C++Service ClientC++

16. PYSimple TF ListenerPY

17. C++Simple TF ListenerC++

18. Angle Rapresentations

19. Euler Angles

20. Quaternion

21. PYEuler to QuaternionPY

22. C++Euler to QuaternionC++

23. LABTF ToolsLAB

9. Odometry

1. Where is the Robot

2. The Local Localization Challenge

3. Wheel Odometry

4.1 L93 Differential Inverse Kinematics.pdf

4. Differential Inverse Kinematics

5. PYDifferential Inverse KinematicPY

6. C++Differential Inverse KinematicC++

7.1 L96 Wheel Odometry Position.pdf

7. Wheel Odometry - Position

8.1 L97 Wheel Odometry Orientation.pdf

8. Wheel Odometry - Orientation

9. PYWheel OdometryPY

10. C++Wheel OdometryC++

11. PYPublish Odometry MessagePY

12. C++Publish Odometry MessageC++

13. PYBroadcast Odometry TransformPY

14. C++Broadcast Odometry TransformC++

10. Probability for Robotics

1. Motivation

2.1 L105 Random Variables.pdf

2. Random Variables

3.1 L106 Conditional Probability.pdf

3. Conditional Probability

4.1 L107 Probability Distributions.pdf

4. Probability Distributions

5. Gaussian Distributions

6.1 L109 Total Probability.pdf

6. Total Probability Theorem

7.1 L110 Bayes Rule.pdf

7. Bayes Rule

8. Sensor Noise

9. PYAdding Noise to Robot MotionPY

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

11. LABOdometry ComparisonLAB

11. Sensor Fusion

1. Advantages of having Multiple Sensors

2. Gyroscope

3. Accelerometer and IMU

4. LABSimulate IMU SensorIMU

5. Kalman Filter

6. PYFilter InitializationPY

7. C++Filter InitializationC++

8. Measurement Update

9. PYMeasurement UpdatePY

10. C++Measurement UpdateC++

11. State Prediction

12. PYState PredictionPY

13. C++State PredictionC++

14. LABLocalization with Kalman FilterLAB

15. Extended Kalman Filter (EKF)

16. PYIMU RepublisherPY

17. C++IMU RepublisherC++

18. LABSensor Fusion with robot localizationLAB

12. Conclusions

1. Recap

2. Whats Next

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تولید کننده: Udemy-Training