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 pivotal role of AI in perception, planning, and control
• Essential software and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Utilizing neural networks for visual recognition
• Integrating TensorFlow or PyTorch with robotic data
• Training perception models for object tracking

Motion Planning and Path Optimization

• Sampling-based versus optimization-based planning approaches
• Leveraging MoveIt for motion planning tasks
• Collision avoidance and dynamic re-planning mechanisms

Learning-Based Control Strategies

• Reinforcement learning applied to robotic control
• Embedding AI within low-level control loops
• Simulation practices using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and principles of human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Adaptive behaviors and real-time responsiveness

System Integration and Deployment

• Interfacing with industrial controllers (PLC, SCADA)
• Edge AI deployment for real-time robotics applications
• Data logging, monitoring, and troubleshooting processes