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Course Outline
Introduction to Edge AI in Robotics
- What is Edge AI?
- Why Edge AI is essential for robotics
- Challenges of real-time AI in autonomous systems
Deploying AI Models on Edge Devices
- AI inference on NVIDIA Jetson and other edge hardware
- Using TensorFlow Lite and ONNX for edge deployment
- Optimizing AI models for real-time execution
Real-Time Perception for Autonomous Systems
- Computer vision for robotic navigation
- Sensor fusion: LiDAR, cameras, and IMUs
- Edge AI for object detection and tracking
Decision-Making and Control in Robotics
- Reinforcement learning for autonomous behaviors
- Path planning and obstacle avoidance
- Latency optimization in real-time AI systems
Integrating AI with ROS (Robot Operating System)
- Overview of ROS and its ecosystem
- Running AI-based perception models in ROS
- Edge AI in multi-robot and swarm robotics applications
Optimizing AI for Low-Power Robotic Systems
- Efficient neural network architectures for robotics
- Reducing power consumption in AI-driven robots
- Deploying AI on battery-powered robotic platforms
Real-World Applications and Future Trends
- Autonomous drones and industrial robots
- AI-powered robotic assistants
- Future advancements in Edge AI for robotics
Summary and Next Steps
Requirements
- An understanding of AI and machine learning models
- Experience with embedded systems or robotics
- Basic knowledge of real-time computing
Audience
- Robotics engineers
- AI developers
- Automation specialists
21 Hours
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 4800 € + VAT*
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