Artificial Intelligence (AI) for Robotics 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 HRI course in Vietnam focuses on voice, gesture, and collaborative control strategies. Participants will learn to construct intuitive, multimodal interfaces that facilitate safe human-robot cooperation, with an emphasis on real-world design principles, speech recognition, gesture detection, and shared autonomy to bolster both usability and safety standards.

This practical training on Vietnam addresses ROS-PLC integration and digital twins within industrial automation. It guides you in synchronizing robotic systems with PLCs, creating digital replicas for simulation, and enhancing production workflows through real-time data exchange and advanced monitoring methods.

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.

An advanced course in Vietnam dedicated to the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, deploy distributed decision-making, and optimize agent collaboration through hands-on simulation in ROS 2 and Gazebo, tailored for real-world applications.

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.

This instructor-led live course in Vietnam, offered online or onsite, targets intermediate-level professionals aiming to boost their proficiency in designing, programming, and deploying intelligent robotic systems for automation and broader applications.

By the end of the program, participants will be able to:

• Comprehend the fundamentals of Physical AI and its utility in robotics and automation.
• Design and program intelligent robotic systems for dynamic settings.
• Apply AI models to facilitate autonomous decision-making in robots.
• Leverage simulation tools for robust robotic testing and optimization.
• Manage critical issues such as sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in Vietnam focuses on rapid robotics prototyping using ROS 2 and Docker. Participants gain hands-on expertise in building, testing, and deploying modular systems, with a strong emphasis on containerization, simulation, and version control to support scalable development efforts.

An advanced training module in Vietnam focusing on the application of deep learning to robotic manipulation. Master the fundamentals of perception, grasp planning, and control utilizing neural networks and ROS 2. Engage in hands-on simulation exercises that prepare you to effectively deploy intelligent, adaptable grasping solutions on real-world robotic arms.