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

Introduction to Smart Robotics and AI Integration

• Overview of robotics in the context of Industry 4.0
• The role of AI in perception, planning, and control
• Introduction to relevant software and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Utilizing neural networks for visual recognition
• Working with robotic data using TensorFlow or PyTorch
• Training perception models for object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning methods
• Implementing motion planning with MoveIt
• Collision avoidance strategies and dynamic re-planning

Learning-Based Control Strategies

• Applying reinforcement learning 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 behaviors and real-time responsiveness

System Integration and Deployment

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

Summary and Next Steps