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 landscape
• The role of AI in perception, planning, and control
• Relevant software and simulation environments

Perception Systems and Sensor Fusion

• Robotics-oriented computer vision (2D/3D cameras, LiDAR)
• Techniques for sensor calibration and fusion
• Object detection and environmental mapping

Deep Learning for Perception

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

Motion Planning and Path Optimisation

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

Learning-Based Control Strategies

• Applying reinforcement learning to robotic control
• Integrating AI into low-level control loops
• Simulation 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
• Adaptive behaviours and real-time responsiveness

System Integration and Deployment

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