Course Outline
Introduction to ROS and Python in the Context of Robotics
- An overview of ROS features and architectural design
- The advantages of adopting ROS for mobile robotics applications
Comprehending ROS
- Exploring core concepts and fundamental components
- Examining the ROS file system, directory structure, and communication models
Configuring the Development Environment
- Installing ROS and Python
- Setting up the ROS environment and workspace
- Linking a mobile robot platform with ROS
Developing and Executing ROS Nodes with Python
- Constructing ROS nodes utilizing Python
- Running nodes and utilizing command-line utilities
- Authoring and applying ROS node launch files
- Leveraging ROS parameters and logging mechanisms
Creating and Managing ROS Topics with Python
- Defining ROS topics using Python
- Publishing data and subscribing to ROS topics
- Implementing ROS message types and custom message definitions
- Monitoring and recording ROS topics through dedicated ROS tools
Developing and Utilizing ROS Services with Python
- Building ROS services in Python
- Handling service requests and service provision
- Working with ROS service types and custom service definitions
- Inspecting and invoking ROS services using ROS tools
Creating and Implementing ROS Actions with Python
- Defining ROS actions using Python
- Transmitting and receiving ROS action goals
- Employing ROS action types and custom action definitions
- Oversight and cancellation of ROS actions via ROS tools
Leveraging ROS Packages and Libraries for Mobile Robots
- Applying the ROS navigation stack to mobile robots
- Implementing ROS SLAM packages for mobile robotic systems
- Utilizing ROS perception packages for mobile robotics
Integrating ROS with External 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 purposes
- Connecting ROS with a wider range of frameworks and tools
Troubleshooting and Debugging ROS Applications
- Addressing frequent issues and errors encountered in ROS applications
- Applying robust debugging techniques and utilizing diagnostic tools
- Best practices and tips for enhancing ROS performance
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of fundamental robotics concepts and terminology
- Practical experience with Python programming and data analysis
- Familiarity with the Linux operating system and command-line interfaces
Target Audience
- Robotics developers
- Enthusiasts of robotics technology
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
