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

Introduction to Smart Robotics and AI Integration

• Overview of robotics within Industry 4.0
• The role of AI in perception, planning, and control
• Essential software and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

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

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning approaches
• Utilizing MoveIt for motion planning tasks
• Strategies for collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control
• Integrating AI into low-level control loops
• Simulation practices 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
• Developing 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 techniques