Course Outline
Introduction to ROS and Python for Robotics
- Overview of ROS features and architectural design.
- Key benefits of adopting ROS for mobile robotics applications.
Understanding ROS
- Core concepts and essential components.
- The ROS file system, directory structure, and communication models.
Setting up the Development Environment
- Installing ROS and Python dependencies.
- Configuring the ROS environment and workspace settings.
- Connecting a mobile robot platform to the ROS system.
Creating and Running ROS Nodes with Python
- Building ROS nodes using Python code.
- Executing nodes and leveraging command line tools.
- Writing and utilizing ROS node launch files.
- Implementing ROS parameters and logging mechanisms.
Creating and Using ROS Topics with Python
- Defining ROS topics via Python.
- Publishing data and subscribing to ROS topics.
- Utilizing standard and custom ROS message types.
- Monitoring and recording ROS topic data using built-in tools.
Creating and Using ROS Services with Python
- Developing ROS services using Python.
- Requesting and providing ROS service interfaces.
- Working with standard and custom ROS service definitions.
- Inspecting and invoking ROS services using diagnostic tools.
Creating and Using ROS Actions with Python
- Developing ROS actions with Python.
- Sending and receiving ROS action goals.
- Implementing standard and custom ROS action types.
- Managing and canceling ROS actions using utility tools.
Using ROS Packages and Libraries for Mobile Robots
- Leveraging the ROS navigation stack for mobile robots.
- Implementing ROS SLAM packages for mapping and localization.
- Employing ROS perception packages for environmental awareness.
Integrating ROS with Other Frameworks and Tools
- Combining ROS with OpenCV for computer vision tasks.
- Integrating ROS with TensorFlow for machine learning applications.
- Using ROS with Gazebo for simulation environments.
- Connecting ROS with other relevant frameworks and tools.
Troubleshooting and Debugging ROS Applications
- Addressing common issues and errors in ROS applications.
- Applying effective debugging techniques and utilizing diagnostic tools.
- Best practices and tips for optimizing ROS performance.
Summary and Next Steps
Requirements
- A solid grasp of fundamental robotics concepts and terminology.
- Practical experience in Python programming and data analysis.
- Familiarity with the Linux operating system and command line utilities.
Target Audience
- Robotics developers.
- Robotics enthusiasts.
Testimonials (3)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
Nazeera Mohamad - Ministry of Science, Technology and Innovation
Course - Introduction to Data Science and AI using Python
Individual support
Simon the 2nd - Cboost
Course - ROS: Programming for Robotics
The trainer was very available to answer all te kind of question I did
