Course Outline
Foundations of TinyML for Robotics
- Key capabilities and constraints of TinyML
- The role of edge AI in autonomous systems
- Hardware considerations for mobile robots and drones
Embedded Hardware and Sensor Interfaces
- Microcontrollers and embedded boards suited for robotics
- Integrating cameras, IMUs, and proximity sensors
- Managing energy and compute budgets
Data Engineering for Robotic Perception
- Collecting and labelling data for specific robotics tasks
- Techniques for signal and image preprocessing
- Feature extraction strategies for resource-constrained devices
Model Development and Optimisation
- Selecting architectures for perception, detection, and classification
- Building training pipelines for embedded ML
- Model compression, quantization, and latency optimisation
On-Device Perception and Control
- Executing inference on microcontrollers
- Fusing TinyML outputs with control algorithms
- Ensuring real-time safety and responsiveness
Enhancing Autonomous Navigation
- Lightweight, vision-based navigation techniques
- Obstacle detection and avoidance strategies
- Maintaining environmental awareness under resource constraints
Testing and Validation of TinyML-Driven Robots
- Utilising simulation tools and field testing approaches
- Performance metrics for embedded autonomy
- Debugging and iterative improvement processes
Integration into Robotics Platforms
- Deploying TinyML within ROS-based pipelines
- Interfacing ML models with motor controllers
- Maintaining reliability across hardware variations
Summary and Next Steps
Requirements
- A solid understanding of robotics system architectures
- Hands-on experience with embedded development
- Familiarity with core machine learning concepts
Target Audience
- Robotics engineers
- AI researchers
- Embedded developers
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 (2)
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.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
