Smart Robotics in Manufacturing: AI for Perception, Planning, and Control Training Course

Foundations of Smart Robotics and AI Integration

• The role of robotics in the Industry 4.0 landscape
• The contribution of AI to perception, planning, and control functions
• Essential software tools and simulation platforms

Perception Frameworks and Sensor Fusion

• Applying computer vision in robotics (utilizing 2D/3D cameras and LiDAR)
• Methods for sensor calibration and data fusion
• Techniques for object detection and environmental mapping

Applying Deep Learning to Perception

• Employing neural networks for visual recognition tasks
• Processing robotic data using TensorFlow or PyTorch
• Training models for robust object tracking

Motion Planning and Path Optimization Techniques

• Exploring sampling-based and optimization-based planning approaches
• Utilizing MoveIt for advanced motion planning
• Implementing collision avoidance and dynamic re-planning

Learning-Based Control Methodologies

• Applying reinforcement learning to robotic control systems
• Incorporating AI into low-level control loops
• Conducting simulations with OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Navigating safety standards and human-robot interaction protocols
• Programming and integrating cobots with AI capabilities
• Designing adaptive behaviors for real-time responsiveness

System Integration and Real-World Deployment

• Interfacing with industrial control systems (PLC, SCADA)
• Deploying Edge AI for real-time robotic operations
• Managing data logging, system monitoring, and troubleshooting