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Duration 21 hours
Course Outline
Introduction to ROS 2 and Autonomous Navigation
- Overview of ROS 2 architecture and core capabilities
- Understanding navigation systems in robotics
- Setting up the ROS 2 development environment
Working with Sensors and Data Acquisition
- Integrating LiDAR and camera sensors
- Collecting and processing sensor data
- Visualizing sensor outputs using Rviz
Mapping and Localization Fundamentals
- Principles of SLAM
- Implementing 2D and 3D mapping
- Localization using AMCL and other techniques
Path Planning and Obstacle Avoidance
- Exploring path planning algorithms
- Dynamic obstacle detection and avoidance
- Testing navigation in simulated environments
Using Gazebo for Simulation
- Setting up Gazebo simulations with ROS 2
- Testing robot models and navigation stacks
- Analyzing performance in virtual environments
Deploying SLAM and Navigation on Real Robots
- Connecting ROS 2 to physical hardware
- Calibrating sensors and actuators
- Running real-time navigation experiments
Troubleshooting and Performance Optimization
- Debugging navigation issues in ROS 2
- Optimizing SLAM algorithms for efficiency
- Fine-tuning navigation parameters
Summary and Next Steps
Requirements
- Familiarity with fundamental robotics principles
- Experience working with Linux-based systems
- Basic proficiency in Python or C++ programming
Target Audience
- Robotics engineers
- Automation developers
- R&D professionals specializing in autonomous systems
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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Testimonials (1)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.