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

Introduction to Smart Robotics and AI Integration

• Landscape of robotics in Industry 4.0
• The role of AI in perception, planning, and control
• Exploring software and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Utilizing neural networks for visual recognition
• Applying TensorFlow or PyTorch to robotic datasets
• Training perception models for accurate object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning approaches
• Implementing motion planning with MoveIt
• Strategies for collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Reinforcement learning applications in robotic control
• Integrating AI into low-level control loops
• Simulation exercises using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and effective human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Achieving adaptive behaviors and real-time responsiveness

System Integration and Deployment

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

Summary and Next Steps