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

Number of participants


Price per participant

Upcoming Courses

Related Categories