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

Introduction to 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 environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Utilizing neural networks for visual recognition tasks
• Application of TensorFlow or PyTorch with robotic datasets
• Developing perception models for effective object tracking

Motion Planning and Path Optimization

• Planning approaches based on sampling and optimization methods
• Implementing motion planning using MoveIt
• Strategies for collision avoidance and dynamic route re-planning

Learning-Based Control Strategies

• Application of reinforcement learning to robotic control
• Embedding AI within low-level control loops
• Conducting simulations with 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
• Achieving adaptive behaviors and real-time responsiveness

System Integration and Deployment

• Interface design with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotic operations
• Data logging, performance monitoring, and issue resolution

Recap and Future Directions