Industrial Robotics Automation: ROS-PLC Integration & Digital Twins Training Course

This instructor-led, live training in Serbia (online or onsite) is designed for intermediate-level participants interested in exploring 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:

• Grasp the core principles of Human-Centric Physical AI and its practical applications.
• Examine how collaborative robots contribute to enhancing workplace productivity.
• Recognize and resolve challenges related to human-machine interactions.
• Develop workflows that maximize collaboration between humans and AI-driven systems.
• Foster a culture of innovation and adaptability in workplaces utilizing AI.

This practical HRI course in Serbia focuses on voice, gesture, and collaborative control. Participants will learn to create intuitive, multimodal interfaces that facilitate safe human-robot collaboration, with a focus on practical design principles, speech recognition, gesture detection, and shared autonomy to improve usability and safety.

This instructor-led live training in Serbia (online or onsite) is designed for engineers seeking to understand how artificial intelligence can be applied to mechatronic systems.

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

• Acquire a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Comprehend the principles of neural networks and various learning methodologies.
• Select appropriate artificial intelligence strategies to address real-world challenges.
• Apply AI solutions within the field of mechatronic engineering.

A specialized training in Serbia focused on the design and coordination of multi-robot systems. Participants will master modeling swarm intelligence, implementing distributed decision-making, and optimizing agent collaboration through hands-on simulation in ROS 2 and Gazebo, preparing for real-world applications.

This instructor-led, live training in Serbia (online or onsite) targets advanced robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

By the end 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.

This instructor-led live training, held Serbia (online or onsite), is designed for intermediate-level automation engineers and control system designers who aim 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 Serbia (online or onsite) is designed for automation engineers and control system designers who wish to configure, program, and commission Omron Sysmac systems, including NJ/NX controllers, EtherCAT networking, G5/1S/1SA servo drives, NA Series HMI, and NX safety hardware.

This live, instructor-led training on Serbia—offered online or on-site—targets intermediate-level participants aiming to strengthen their capabilities in designing, programming, and deploying intelligent robotic systems for automation and beyond.

Upon completing this training, participants will be able to:

• Understand the core principles of Physical AI and their application in robotics and automation.
• Design and program intelligent robotic systems for dynamic environments.
• Implement AI models for autonomous decision-making in robots.
• Utilize simulation tools for robotic testing and optimization.
• Address challenges related to sensor fusion, real-time processing, and energy efficiency.