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

Fundamentals of Intelligent Robotics and AI Integration

• The role of robotics in Industry 4.0.
• How AI contributes to perception, planning, and control.
• Exploration of software and simulation environments.

Perception Systems and Sensor Fusion

• Computer vision applications in robotics, including 2D/3D cameras and LiDAR.
• Techniques for sensor calibration and data fusion.
• Identifying objects and mapping environments.

Deep Learning Applications in Perception

• Leveraging neural networks for visual recognition tasks.
• Utilizing TensorFlow or PyTorch for processing robotic data.
• Training perception models specifically for object tracking.

Motion Planning and Path Optimization

• Comparing sampling-based versus optimization-based planning methods.
• Utilizing MoveIt for advanced motion planning.
• Managing collision avoidance and dynamic re-planning.

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control.
• Embedding AI into low-level control loops.
• Conducting simulations with OpenAI Gym and Gazebo.

Collaborative Robots (Cobots) in Smart Manufacturing

• Adhering to safety standards and facilitating human-robot collaboration.
• Programming and integrating cobots with AI capabilities.
• Implementing adaptive behaviors for real-time responsiveness.

System Integration and Deployment

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

Conclusion and Future Directions