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

Introduction to Smart Robotics and AI Integration

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

Perception Systems and Sensor Fusion

• Robotics-oriented computer vision (2D/3D cameras, LiDAR)
• Methods for sensor calibration and data fusion
• Techniques for object detection and environmental mapping

Deep Learning for Perception

• Applying neural networks to visual recognition tasks
• Leveraging TensorFlow or PyTorch with robotic datasets
• Training models specifically for object tracking

Motion Planning and Path Optimization

• Exploring sampling-based and optimization-based planning methods
• Utilizing MoveIt for effective motion planning
• Implementing collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control
• Integrating AI into low-level control loops
• Simulating scenarios using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Understanding safety standards and human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Designing adaptive behaviors and real-time responsiveness

System Integration and Deployment

• Connecting with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotic operations
• Managing data logging, monitoring, and troubleshooting processes