Physical AI for Robotics and Automation Training Course

This live, instructor-led training in the Netherlands empowers intermediate robotics engineers with practical skills in autonomous navigation and SLAM using ROS 2. Learn to integrate LiDAR sensors, deploy mapping algorithms, conduct simulations in Gazebo, and implement real-world navigation stacks on physical robots.

This instructor-led training in the Netherlands focuses on applying computer vision to robotics using OpenCV and deep learning. Learners will develop skills in creating perception pipelines, integrating detection models, and deploying systems on embedded platforms to enable autonomous control.

This live training in the Netherlands helps intermediate engineers deploy TinyML models for robotics. You will learn to optimize inference for speed and energy efficiency, integrate AI into control systems, and develop autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led live training in the Netherlands (online or onsite) is designed for intermediate-level participants eager to explore the role of collaborative robots (cobots) and other human-centric AI systems in contemporary 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.
• Identify and tackle challenges inherent in human-machine interactions.
• Design workflows that optimize collaboration between humans and AI-driven systems.
• Foster a culture of innovation and adaptability within AI-integrated workplaces.

This practical HRI course in the Netherlands focuses on voice, gesture, and collaborative control techniques. Participants will learn to design intuitive, multimodal interfaces that facilitate safe human-robot collaboration, with an emphasis on practical design principles, speech recognition, gesture detection, and shared autonomy to enhance both usability and safety.

This practical training in the Netherlands covers ROS-PLC integration and digital twins for industrial automation. Discover how to synchronize robotic systems with PLCs, develop digital replicas for simulation, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led, live training in the Netherlands (online or onsite) is designed for engineers seeking to understand the applicability of artificial intelligence to mechatronic systems.

Upon completing this training, participants will be capable of:

• Gaining a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Understanding the fundamental concepts of neural networks and various learning methodologies.
• Selecting the most effective artificial intelligence approaches for practical, real-world problems.
• Implementing AI applications within the field of mechatronic engineering.

An advanced training on the Netherlands focused on the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and enhance inter-agent collaboration through hands-on simulation in ROS 2 and Gazebo, preparing them for real-world applications.

This instructor-led, live training in the Netherlands (online or onsite) is designed for advanced robotics engineers and AI researchers who wish to utilize Multimodal AI to integrate various sensory data. The aim is to create more autonomous and efficient robots that can see, hear, and touch.

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

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

This practical, instructor-led training in the Netherlands focuses on rapid prototyping for robotics using ROS 2 and Docker. Learners acquire hands-on skills to efficiently build, test, and deploy modular robotic systems, gaining expertise in containerization, simulation, and version control for scalable development.

This live, instructor-led training in the Netherlands explores the principles of reinforcement learning and advanced techniques such as PPO and DDPG. Participants will apply algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to resolve complex tasks.

Advanced training in the Netherlands focused on applying deep learning to robotic manipulation. Acquire skills in perception, grasp planning, and control utilizing neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptive grasping solutions on physical robotic arms.