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

Foundations of Smart Robotics and AI Integration

• Overview of robotics in the context of Industry 4.0
• The function of AI in perception, planning, and control
• Relevant software and simulation environments

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Neural networks applied to visual recognition
• Utilizing TensorFlow or PyTorch with robotic datasets
• Training perception models for object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning approaches
• Motion planning using MoveIt
• Collision avoidance and dynamic re-planning capabilities

Learning-Based Control Strategies

• Reinforcement learning for robotic control systems
• Embedding AI into low-level control loops
• Simulation using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and human-robot interaction protocols
• Programming and integrating cobots with AI frameworks
• Achieving 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, monitoring, and troubleshooting procedures

Summary and Future Directions