Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Vietnam (online or onsite) targets intermediate-level participants who wish to explore 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 Vietnam addresses ROS-PLC integration and digital twins within industrial automation. You will learn to synchronize robotic systems with PLCs, develop digital replicas for simulation purposes, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led live training in Vietnam (online or on-site) is designed for engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

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

• Gain an overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the concepts of neural networks and different learning methods.
• Choose artificial intelligence approaches effectively for real-life problems.
• Implement AI applications in mechatronic engineering.

This instructor-led, live training in Vietnam (online or onsite) targets advanced robotics engineers and AI researchers aiming to leverage Multimodal AI. The course focuses on integrating diverse sensory data to build more autonomous and efficient robots that can see, hear, and touch.

Upon completion, participants will be able to:

• Implement multimodal sensing within robotic systems.
• Develop AI algorithms for sensor fusion and decision-making processes.
• Build robots capable of executing complex tasks in dynamic environments.
• Tackle challenges related to real-time data processing and actuation.

An advanced training in Vietnam focusing on deep learning applications in robotic manipulation. Master perception, grasp planning, and control leveraging neural networks and ROS 2. Practical simulation exercises equip you to successfully deploy intelligent, adaptable grasping solutions on real robotic arms.