Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Bulgaria (online or onsite) targets intermediate-level professionals interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

By the conclusion 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 Bulgaria addresses ROS-PLC integration and digital twins within industrial automation. Learners will master the synchronization of robotic systems with PLCs, the development of digital replicas for simulation, and the optimization of production workflows via real-time data exchange and advanced monitoring methods.

This instructor-led live training in Bulgaria (online or onsite) is designed for 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 Bulgaria (online or onsite) is designed for advanced robotics engineers and AI researchers aiming to utilize Multimodal AI. The objective is to integrate various sensory inputs to develop highly autonomous and efficient robots capable of seeing, hearing, and touching.

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.

An advanced training program in Bulgaria that focuses on applying deep learning to robotic manipulation. Participants will master perception, grasp planning, and control through the use of neural networks and ROS 2. Practical exercises in simulated environments equip you to effectively deploy intelligent and adaptable grasping solutions on physical robotic arms.