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

Perception Systems and Sensor Fusion

• Computer vision applications for robotics (2D/3D cameras, LiDAR)
• Techniques for sensor calibration and data fusion
• 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 robust object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning methodologies
• Utilizing MoveIt for advanced motion planning
• Collision avoidance strategies and dynamic re-planning

Learning-Based Control Strategies

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

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and frameworks for human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Developing adaptive behaviours and real-time responsiveness

System Integration and Deployment

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

Summary and Next Steps