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

Foundational Introduction to Smart Robotics and AI Integration

• The landscape of robotics in Industry 4.0
• The critical role of AI in perception, planning, and control functions
• Essential software tools and simulation environments

Perception Systems and Advanced Sensor Fusion

• Robotic computer vision (utilising 2D/3D cameras and LiDAR)
• Techniques for sensor calibration and data fusion
• Object detection methodologies and environment mapping

Applying Deep Learning to Perception Tasks

• Utilising neural networks for visual recognition
• Implementing TensorFlow or PyTorch with robotic datasets
• Training perception models specifically for object tracking

Motion Planning and Path Optimisation Strategies

• Sampling-based and optimisation-based planning approaches
• Utilising MoveIt for robust motion planning
• Collision avoidance mechanisms and dynamic re-planning

Learning-Based Control Strategies

• Reinforcement learning applications in robotic control
• Embedding AI into low-level control loops
• Simulation practices using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) within Smart Manufacturing

• Safety standards and frameworks for human-robot collaboration
• Programming and integrating cobots with AI capabilities
• Developing adaptive behaviours and real-time responsiveness

System Integration and Deployment Processes

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

Summary and Strategic Next Steps