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
• How AI drives 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 mapping of the environment

Deep Learning for Perception

• Neural networks for visual recognition tasks
• Leveraging TensorFlow or PyTorch with robotic datasets
• Training perception models specifically for object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning methods
• Utilising MoveIt for robust motion planning
• Collision avoidance and dynamic re-planning strategies

Learning-Based Control Strategies

• Reinforcement learning applied to robotic control
• Integrating AI into low-level control loops
• Simulation 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
• Achieving adaptive behaviours and real-time responsiveness

System Integration and Deployment

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

Conclusion and Future Directions