Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Australia (online or onsite) targets intermediate-level participants interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

By the end of this training, participants will be able to:

• Understand the principles of Human-Centric Physical AI and its applications.
• Explore the role of collaborative robots in enhancing workplace productivity.
• Identify and address challenges in human-machine interactions.
• Design workflows that optimize collaboration between humans and AI-driven systems.
• Promote a culture of innovation and adaptability in AI-integrated workplaces.

This practical training in Australia explores ROS-PLC integration and digital twins for industrial automation. Learn to synchronise robotic systems with PLCs, create digital replicas for simulation, and enhance production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led, live training in Australia (online or onsite) is designed for engineers looking to explore the application of artificial intelligence within mechatronic systems.

Upon completion of this training, participants will be able to:

• Gain a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the fundamental concepts of neural networks and various learning methodologies.
• Effectively select appropriate artificial intelligence approaches for solving real-world problems.
• Implement AI applications in the field of mechatronic engineering.

This instructor-led, live training in Australia (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

By the end of this training, participants will be able to:

• Implement multimodal sensing in robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots that can perform complex tasks in dynamic environments.
• Address challenges in real-time data processing and actuation.

An advanced training in Australia focused on deep learning for robotic manipulation. Learn perception, grasp planning, and control using neural networks and ROS 2. Hands-on exercises in simulation prepare you to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.