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

Introduction to Intelligent Robotics and AI Integration

• The role of robotics in Industry 4.0
• How AI contributes to perception, planning, and control
• Relevant software and simulation platforms

Perception Systems and Sensor Fusion

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

Deep Learning Applications in Perception

• Utilizing neural networks for visual recognition
• Working with TensorFlow or PyTorch on robotic datasets
• Training models for effective object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning methods
• Practical use of MoveIt for motion planning
• Collision avoidance and dynamic re-planning capabilities

Learning-Based Control Strategies

• Reinforcement learning applied to robotic control
• Embedding AI into low-level control loops
• Simulations using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety protocols and human-robot interaction standards
• Programming and integrating AI with cobots
• Achieving adaptive behavior and real-time responsiveness

System Integration and Deployment

• Connecting with industrial controllers (PLC, SCADA)
• Deploying Edge AI for real-time robotics tasks
• Data logging, monitoring, and troubleshooting processes

Recap and Future Directions