Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Mexico (online or onsite) is tailored for intermediate-level participants interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern work environments.

Upon completing this training, participants will be able to:

• Grasp the core principles of Human-Centric Physical AI and its practical applications.
• Analyze how collaborative robots contribute to enhancing workplace efficiency.
• Recognize and resolve issues related to human-machine interaction.
• Create workflows that maximize collaboration between employees and AI-driven systems.
• Foster a culture of innovation and adaptability within organizations using AI technology.

This hands-on training in Mexico covers ROS-PLC integration and digital twins for industrial automation. Participants will learn to synchronize robotic systems with PLCs, develop digital replicas for simulation, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led, live training in Mexico (online or onsite) is aimed at 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 Mexico (online or onsite) is designed for advanced robotics engineers and AI researchers who want to leverage Multimodal AI to integrate diverse sensory data. The goal is to build more autonomous and efficient robots that can perceive through sight, sound, and touch.

Upon completion 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 Mexico focusing on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control utilizing neural networks and ROS 2. Practical simulation exercises prepare you to deploy intelligent, adaptable grasping solutions on real robotic arms with effectiveness.