Physical AI for Robotics and Automation Training Course

This instructor-led, live training in France (online or onsite) is aimed at 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 hands-on training in France explores ROS-PLC integration and digital twins within the context of industrial automation. It guides learners in synchronizing robotic systems with PLCs, creating digital replicas for simulation purposes, and enhancing production workflows through real-time data exchange and sophisticated monitoring techniques.

This instructor-led live training in France (online or onsite) is designed for engineers interested in learning how to apply artificial intelligence to mechatronic systems.

Upon completing this training, participants will be able to:

• Obtain a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Grasp the core concepts of neural networks and various learning methodologies.
• Select appropriate artificial intelligence approaches to address real-world challenges.
• Deploy AI solutions within mechatronic engineering contexts.

This instructor-led, live training in France (online or onsite) targets advanced robotics engineers and AI researchers who wish to utilize Multimodal AI. The goal is to integrate various sensory data streams to create more autonomous and efficient robots capable of visual, auditory, and tactile interaction.

Upon completion, participants will be able to:

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

Advance your expertise with this specialized training in France, focusing on deep learning for robotic manipulation. Master perception, grasp planning, and control using neural networks and ROS 2. Through hands-on simulation exercises, you will be prepared to effectively deploy intelligent and adaptable grasping solutions on real robotic arms.