Industrial Robotics Automation: ROS-PLC Integration & Digital Twins 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 practical HRI course in France focuses on voice, gesture, and collaborative control. It guides learners in building intuitive, multimodal interfaces for secure human-robot collaboration, emphasizing hands-on design principles, speech recognition, gesture detection, and shared autonomy to boost usability and safety.

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.

A specialized training program on France that focuses on the architecture and synchronization of multi-robot systems. Learners acquire the skills to model swarm intelligence, execute distributed decision-making, and enhance inter-agent collaboration through practical simulation in ROS 2 and Gazebo, targeting real-world implementation.

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.

This instructor-led live training in France (online or onsite) is aimed at intermediate-level automation engineers and control system designers who wish to implement motion control solutions using Omron PLCs.

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

• Understand fundamental motion control concepts and their applications.
• Configure motion hardware and software in Sysmac Studio.
• Program and optimize single-axis and multi-axis motion control.
• Implement coordinated motion strategies, including interpolation and synchronization.

This instructor-led live training in France (available online or onsite) targets automation engineers and control system designers seeking to configure, program, and commission Omron Sysmac systems, including NJ/NX controllers, EtherCAT networking, G5/1S/1SA servo drives, NA Series HMIs, and NX safety hardware.

This live, instructor-led training in France (online or onsite) is designed for intermediate-level professionals aiming to elevate their capabilities in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the principles of Physical AI and its role in robotics and automation.
• Design and program intelligent robotic systems suited for dynamic environments.
• Apply AI models to enable autonomous decision-making in robots.
• Employ simulation tools for effective robotic testing and optimization.
• Tackle key challenges such as sensor fusion, real-time processing, and energy efficiency.