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

Introduction to Smart Robotics and AI Integration

• Overview of robotics within the Industry 4.0 framework.
• The role of AI in perception, planning, and control processes.
• Essential software and simulation environments.

Perception Systems and Sensor Fusion

• Robotics computer vision, including 2D/3D cameras and LiDAR.
• Techniques for sensor calibration and data fusion.
• Object detection and environment mapping methods.

Deep Learning for Perception

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

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning approaches.
• Leveraging MoveIt for robust motion planning.
• Strategies for collision avoidance and dynamic re-planning.

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control.
• Integrating AI into low-level control loops.
• Simulation exercises using OpenAI Gym and Gazebo.

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and principles of human-robot collaboration.
• Programming and integrating cobots with AI capabilities.
• Developing adaptive behaviors and real-time responsiveness.

System Integration and Deployment

• Interfacing with industrial controllers such as PLC and SCADA.
• Deploying Edge AI for real-time robotic operations.
• Effective data logging, monitoring, and troubleshooting practices.

Summary and Next Steps