Course Outline
Introduction to ROS and Python for Government Robotics
- Overview of ROS features and architecture
- Benefits of using ROS for mobile robotics in government applications
Understanding ROS for Government Use
- Core concepts and components
- ROS file system, directory structure, and communication model
Setting up the Development Environment for Government Robotics Projects
- Installation of ROS and Python
- Configuration of ROS environment and workspace
- Connecting a mobile robot platform with ROS for government operations
Creating and Running ROS Nodes with Python for Government Applications
- Creating ROS nodes using Python
- Running nodes and using command line tools
- Writing and using ROS node launch files
- Utilizing ROS parameters and logging for enhanced traceability and accountability
Creating and Using ROS Topics with Python for Government Robotics
- Creating ROS topics with Python
- Publishing and subscribing to ROS topics for real-time data exchange in government operations
- Utilizing ROS message types and custom messages for specific government requirements
- Monitoring and recording ROS topics using ROS tools for audit and analysis
Creating and Using ROS Services with Python for Government Applications
- Creating ROS services with Python
- Requesting and providing ROS services to support government missions
- Utilizing ROS service types and custom services for specialized tasks
- Inspecting and calling ROS services using ROS tools for efficient management
Creating and Using ROS Actions with Python for Government Robotics
- Creating ROS actions with Python
- Sending and receiving ROS action goals to enhance mission flexibility
- Utilizing ROS action types and custom actions for complex operations
- Managing and canceling ROS actions using ROS tools for robust control
Using ROS Packages and Libraries for Mobile Robots in Government Operations
- Using the ROS navigation stack for mobile robots to support government missions
- Implementing ROS SLAM packages for mobile robots to improve situational awareness
- Employing ROS perception packages for mobile robots to enhance data collection capabilities
Integrating ROS with Other Frameworks and Tools for Government Applications
- Using ROS with OpenCV for computer vision in government projects
- Using ROS with TensorFlow for machine learning applications in government operations
- Using ROS with Gazebo for simulation to support training and testing
- Using ROS with other frameworks and tools to expand functionality for government use
Troubleshooting and Debugging ROS Applications for Government Use
- Addressing common issues and errors in ROS applications for government systems
- Applying effective debugging techniques and tools to ensure reliability
- Tips and best practices for improving ROS performance in government environments
Summary and Next Steps for Government Robotics Projects
Requirements
- An understanding of fundamental robotics concepts and terminology
- Experience with Python programming and data analysis
- Familiarity with the Linux operating system and command line tools
Audience for Government
- Robotics developers
- Robotics enthusiasts
Testimonials (5)
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Jenna - TCMT
Course - Machine Learning with Python – 2 Days
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
The explaination
Wei Yang Teo - Ministry of Defence, Singapore
Course - Machine Learning with Python – 4 Days
Trainer develops training based on participant's pace