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Course Outline
Introduction to Edge AI in Robotics for Government
- Definition of Edge AI
- Importance of Edge AI in robotics for government operations
- Challenges associated with real-time AI in autonomous systems for government use
Deploying AI Models on Edge Devices for Government
- Implementing AI inference on NVIDIA Jetson and other edge hardware suitable for government applications
- Utilizing TensorFlow Lite and ONNX for deploying AI models in government environments
- Optimizing AI models to ensure real-time execution in government systems
Real-Time Perception for Autonomous Systems for Government
- Computer vision techniques for robotic navigation in government settings
- Sensor fusion incorporating LiDAR, cameras, and IMUs for enhanced situational awareness in government operations
- Edge AI capabilities for object detection and tracking to support government missions
Decision-Making and Control in Robotics for Government
- Application of reinforcement learning for autonomous behaviors in government robotics
- Path planning and obstacle avoidance strategies tailored for government use cases
- Latency optimization to ensure real-time performance in AI systems for government operations
Integrating AI with ROS (Robot Operating System) for Government
- Overview of ROS and its ecosystem, focusing on government applications
- Running AI-based perception models within the ROS framework to support government tasks
- Utilizing Edge AI in multi-robot and swarm robotics for government missions
Optimizing AI for Low-Power Robotic Systems for Government
- Designing efficient neural network architectures to support government robotic systems
- Strategies for reducing power consumption in AI-driven robots used by the government
- Deploying AI on battery-powered robotic platforms for government operations
Real-World Applications and Future Trends in Government Robotics
- Use of autonomous drones and industrial robots in government settings
- Development of AI-powered robotic assistants for government agencies
- Anticipated advancements in Edge AI for robotics within the government sector
Summary and Next Steps for Government
Requirements
- A comprehensive understanding of artificial intelligence and machine learning models for government applications
- Practical experience with embedded systems or robotics for government projects
- Fundamental knowledge of real-time computing principles for government operations
Audience
- Robotics engineers
- AI developers
- Automation specialists
21 Hours