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

Introduction to Smart Robotics and AI Integration

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

Perception Systems and Sensor Fusion

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

Deep Learning for Perception

• Applying neural networks to visual recognition
• Leveraging TensorFlow or PyTorch with robotic datasets
• Training perception models for object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning methods
• Utilizing MoveIt for motion planning tasks
• Collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control
• Integrating AI into low-level control loops
• Simulating scenarios with OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and protocols for human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Adaptive behaviors and real-time responsiveness

System Integration and Deployment

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