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

Foundations of Smart Robotics and AI Integration

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

Perception Systems and Advanced Sensor Fusion

• Computer vision applications in robotics (utilizing 2D/3D cameras and LiDAR)
• Techniques for sensor calibration and data fusion
• Object detection and real-time environment mapping

Deep Learning Applications in Perception

• Leveraging neural networks for visual recognition tasks
• Implementing TensorFlow or PyTorch frameworks with robotic datasets
• Training and optimizing perception models for dynamic object tracking

Advanced Motion Planning and Path Optimization

• Sampling-based versus optimization-based planning methodologies
• Practical application of MoveIt for complex motion planning
• Strategies for collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Applying reinforcement learning principles to robotic control
• Embedding AI algorithms within low-level control loops
• Simulation and testing using OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Compliance with safety standards and human-robot collaboration protocols
• Programming and integrating cobots with AI capabilities
• Designing adaptive behaviors for real-time responsiveness

System Integration and Production Deployment

• Interfacing robotic systems with industrial controllers (PLC, SCADA)
• Deploying Edge AI solutions for low-latency robotics operations
• Implementing data logging, monitoring, and troubleshooting workflows