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

Foundations of Smart Robotics and AI Integration

• The landscape of robotics in Industry 4.0
• The contribution of AI to perception, planning, and control processes
• Essential software tools and simulation platforms

Perception Architectures and Sensor Fusion

• Robotics computer vision (utilizing 2D/3D cameras and LiDAR)/li>
• Techniques for sensor calibration and data fusion
• Identifying objects and mapping the surrounding environment

Applying Deep Learning to Perception

• Leveraging neural networks for visual recognition tasks
• Applying TensorFlow or PyTorch to robotic datasets
• Developing perception models focused on object tracking

Motion Planning and Path Efficiency

• Planning approaches based on sampling and optimization
• Utilizing MoveIt for effective motion planning
• Managing collision avoidance and dynamic path adjustments

Learning-Driven Control Mechanisms

• Applying reinforcement learning to robotic control systems
• Embedding AI within low-level control loops
• Conducting simulations using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety regulations and principles of human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Implementing adaptive behaviors for real-time responsiveness

System Integration and Operational Deployment

• Connecting with industrial control systems (PLC, SCADA)/li>
• Deploying Edge AI for immediate robotic response
• Managing data logging, system monitoring, and troubleshooting