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

Foundations of Smart Robotics and AI Integration

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

Perception Architectures and Sensor Fusion

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

Deep Learning Applications in Perception

• Utilizing neural networks for visual recognition tasks
• Implementing TensorFlow or PyTorch with robotic datasets
• Training models for precise object tracking

Advanced Motion Planning and Path Optimization

• Exploring sampling-based versus optimization-based planning methods
• Practical use of MoveIt for complex motion planning
• Strategies for collision avoidance and dynamic re-planning

Control Strategies Driven by Machine Learning

• Applying reinforcement learning to robotic control systems
• Embedding AI into low-level control loops
• Simulating scenarios using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety protocols and frameworks for human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Designing adaptive behaviors and ensuring real-time responsiveness

System Integration and Industrial Deployment

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