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

Fundamentals of Smart Robotics and AI Integration

• Overview of robotics within the context of Industry 4.0
• The role of AI in perception, planning, and control processes
• Relevant software tools and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning Applications in Perception

• Utilizing neural networks for visual recognition tasks
• Implementing TensorFlow or PyTorch with robotic datasets
• Training perception models for effective object tracking

Motion Planning and Path Optimization

• Planning approaches based on sampling and optimization techniques
• Utilizing MoveIt for advanced motion planning
• Strategies for collision avoidance and dynamic re-planning

Control Strategies Based on Machine Learning

• Applying reinforcement learning to robotic control
• Integrating AI models into low-level control loops
• Simulation exercises using OpenAI Gym and Gazebo

The Role of Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and principles of human-robot collaboration
• Programming cobots and integrating them with AI systems
• Achieving adaptive behaviors and real-time responsiveness

System Integration and Deployment

• Interfacing with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotic operations
• Data logging, system monitoring, and troubleshooting procedures

Conclusion and Path Forward