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Course Outline
Introduction to Smart Robotics and AI Integration for Government
- Overview of robotics in Industry 4.0 for government applications
- The role of artificial intelligence in perception, planning, and control within public sector workflows
- Software and simulation environments tailored for government use
Perception Systems and Sensor Fusion for Government
- Computer vision technologies for robotics, including 2D/3D cameras and LiDAR, optimized for government operations
- Techniques for sensor calibration and fusion to enhance situational awareness in public sector environments
- Methods for object detection and environment mapping to support mission-critical tasks
Deep Learning for Perception in Government Applications
- Neural network architectures for visual recognition, tailored for government needs
- Utilizing TensorFlow or PyTorch with robotic data to support government missions
- Training perception models for object tracking in secure and regulated environments
Motion Planning and Path Optimization for Government Operations
- Sampling-based and optimization-based planning methods for efficient task execution in government scenarios
- Working with MoveIt to develop motion plans that align with public sector requirements
- Strategies for collision avoidance and dynamic re-planning to ensure safety and reliability in government applications
Learning-Based Control Strategies for Government Robotics
- Reinforcement learning techniques for robotic control, adapted for government use cases
- Integrating AI into low-level control loops to enhance performance and efficiency in public sector operations
- Simulation environments using OpenAI Gym and Gazebo to prepare robots for real-world government tasks
Collaborative Robots (Cobots) in Smart Manufacturing for Government
- Safety standards and human-robot collaboration protocols specific to government settings
- Programming and integrating cobots with AI to support public sector manufacturing processes
- Developing adaptive behaviors and real-time responsiveness for enhanced mission support
System Integration and Deployment for Government Operations
- Interfacing with industrial controllers (PLC, SCADA) to ensure seamless integration in government facilities
- Deploying edge AI solutions for real-time robotics applications in public sector environments
- Implementing data logging, monitoring, and troubleshooting practices to maintain system integrity and reliability for government use
Summary and Next Steps for Government
Requirements
- An understanding of robotic systems and kinematics for government applications.
- Experience with Python programming for government projects.
- Familiarity with AI or machine learning concepts for government use.
Audience
- Robotics engineers in the public sector
- Systems integrators for government initiatives
- Automation leads for government agencies
21 Hours
