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

Fundamentals of Smart Robotics and AI Integration

• The landscape of robotics within Industry 4.0
• The impact of AI on perception, planning, and control functions
• Available software and simulation platforms

Perception Systems and Sensor Data Fusion

• Computer vision applications in robotics (2D/3D cameras, LiDAR)
• Techniques for sensor calibration and data fusion
• Identifying objects and mapping the environment

Deep Learning Applications in Perception

• Neural networks for visual recognition tasks
• Utilizing TensorFlow or PyTorch for robotic data processing
• Training perception models for continuous object tracking

Motion Planning and Path Optimization Strategies

• Planning approaches based on sampling and optimization
• Utilizing MoveIt for robotic motion planning
• Avoiding collisions and executing dynamic re-planning

Control Strategies Based on Machine Learning

• Applying reinforcement learning to robotic control
• Embedding AI into low-level control loops
• Conducting simulations with OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Intelligent Manufacturing

• Safety protocols and human-robot interaction standards
• Programming and integrating cobots with AI capabilities
• Implementing adaptive behaviors and real-time responsiveness

System Integration and Operational Deployment

• Connecting with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotic operations
• Logging data, monitoring performance, and troubleshooting issues

Course Summary and Recommended Next Steps