Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Norway (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 training in Norway addresses ROS-PLC integration and digital twins within industrial automation. You will learn to synchronize robotic systems with PLCs, build digital replicas for simulation, and streamline production workflows through real-time data exchange and advanced monitoring strategies.

This instructor-led live training in Norway (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 Norway (online or onsite) is designed for advanced robotics engineers and AI researchers seeking to leverage Multimodal AI to integrate diverse sensory inputs. The objective is to build more autonomous and efficient robots that possess the ability to see, hear, and touch.

Upon completion of this training, participants will be able to:

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

Advanced training in Norway focusing on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control using neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptable grasping solutions on real-world robotic arms.