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 pivotal role of AI in perception, planning, and control.
• Essential software and simulation tools.

Perception Systems and Sensor Fusion

• Application of computer vision in robotics (2D/3D cameras, LiDAR).
• Techniques for sensor calibration and data fusion.
• Advances in object detection and environmental mapping.

Deep Learning for Enhanced Perception

• Utilizing neural networks for visual recognition.
• Implementing TensorFlow or PyTorch with robotic datasets.
• Training perception models for accurate object tracking.

Motion Planning and Path Optimization

• Exploring sampling-based and optimization-based planning methods.
• Leveraging MoveIt for robust motion planning.
• Implementing collision avoidance and dynamic re-planning strategies.

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control.
• Embedding AI into low-level control loops.
• Simulating behaviors using OpenAI Gym and Gazebo.

Collaborative Robots (Cobots) in Smart Manufacturing

• Compliance with safety standards and human-robot collaboration protocols.
• Programming and integrating AI capabilities into cobots.
• 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.
• Effective data logging, monitoring, and troubleshooting practices.