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

Introduction to Smart Robotics and AI Integration

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

Perception Systems and Sensor Fusion

• Robotics computer vision (2D/3D cameras, LiDAR)
• Techniques for sensor calibration and fusion
• Environment mapping and object detection

Deep Learning for Perception

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

Motion Planning and Path Optimization

• Planning via sampling-based and optimization-based methods
• Utilizing MoveIt for motion planning
• Dynamic re-planning and collision avoidance

Learning-Based Control Strategies

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

Collaborative Robots (Cobots) in Smart Manufacturing

• Human-robot collaboration and safety standards
• Programming and integrating cobots with AI
• Real-time responsiveness and adaptive behaviors

System Integration and Deployment

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

Summary and Next Steps