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

Foundations of Smart Robotics and AI Integration

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

Perception Architectures and Sensor Fusion

• Applying computer vision to 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 for robotic datasets
• Training models specifically for object tracking

Motion Planning and Path Optimization

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

Learning-Driven Control Strategies

• Applying reinforcement learning to robotic control
• Embedding AI within low-level control loops
• Simulating environments using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Navigating safety standards and human-robot interaction
• Programming and integrating cobots with AI capabilities
• Designing adaptive behaviors for real-time responsiveness

System Integration and Deployment

• Interfacing with industrial control systems (PLC, SCADA)
• Deploying Edge AI for low-latency robotic operations
• Monitoring, data logging, and diagnostic troubleshooting