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

Introduction to Smart Robotics and AI Integration

• The landscape of robotics in Industry 4.0
• The contribution of AI to perception, planning, and control
• Relevant software and simulation platforms

Perception Systems 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 for Perception

• Neural network architectures for visual recognition
• Leveraging TensorFlow or PyTorch with robotic datasets
• Training perception models for effective object tracking

Motion Planning and Path Optimization

• Planning approaches based on sampling and optimization
• Utilizing MoveIt for motion planning tasks
• Strategies for collision avoidance and dynamic re-planning

Learning-Based Control Strategies

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

Collaborative Robots (Cobots) in Smart Manufacturing

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

System Integration and Deployment

• Interfacing with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotics applications
• Procedures for data logging, monitoring, and troubleshooting