TinyML for Autonomous Systems and Robotics Training Course

This live, instructor-led program in Hungary provides intermediate robotics engineers with practical expertise in autonomous navigation and SLAM through ROS 2. The curriculum covers integrating LiDAR sensors, applying mapping algorithms, simulating scenarios in Gazebo, and deploying navigation stacks on real-world robotic hardware.

This instructor-led training in Hungary delves into computer vision for robotics through the use of OpenCV and deep learning. Attendees will gain the skills to build perception pipelines, integrate detection models, and deploy systems on embedded platforms to achieve autonomous control.

This live training in Hungary guides intermediate engineers in deploying TinyML models for robotics. Learn to optimize inference for speed and energy, integrate AI into control systems, and build autonomous, low-latency robotic solutions directly on embedded hardware.

This live, instructor-led session in Hungary (available online or on-site) is designed for intermediate-level participants seeking to understand the role of collaborative robots (cobots) and other human-centric AI systems in today’s workplaces.

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

• Understand the fundamentals of Human-Centric Physical AI and its real-world uses.
• Explore how collaborative robots drive improvements in workplace productivity.
• Identify and manage challenges related to human-machine interaction.
• Develop workflows that enhance cooperation between humans and AI-driven systems.
• Cultivate an environment of innovation and adaptability in AI-enabled workplaces.

This hands-on HRI course in Hungary focuses on voice, gesture, and collaborative control. Participants will learn to build intuitive, multimodal interfaces for safe human-robot collaboration, with a strong emphasis on practical design principles, speech recognition, gesture detection, and shared autonomy to optimize usability and safety.

This practical training in Hungary focuses on ROS-PLC integration and digital twins for industrial automation. Participants will learn to synchronize robotic systems with PLCs, create digital replicas for simulation, and enhance production workflows through real-time data exchange and sophisticated monitoring techniques.

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

By the conclusion of this training, participants will be capable of:

• Obtaining a broad perspective on artificial intelligence, machine learning, and computational intelligence.
• Understanding the underlying concepts of neural networks and diverse learning methods.
• Effectively selecting artificial intelligence approaches to solve real-world problems.
• Developing and deploying AI applications in mechatronic engineering contexts.

An advanced course on Hungary that covers the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimize agent collaboration through hands-on simulation using ROS 2 and Gazebo, targeting real-world applications.

This instructor-led live training, delivered in Hungary (either online or onsite), is tailored for senior robotics engineers and AI researchers. It equips them to harness Multimodal AI for integrating multifaceted sensory data, thereby enabling the creation of more autonomous and efficient robots that can see, hear, and touch.

By the conclusion of this program, attendees will be equipped to:

• Implement multimodal sensing mechanisms in robotic systems.
• Develop AI algorithms optimized for sensor fusion and decision-making processes.
• Build robots capable of performing complex operations in dynamic settings.
• Overcome challenges related to real-time data processing and actuation.

This live, instructor-led training in Hungary, offered online or onsite, is tailored for intermediate-level participants seeking to advance their capabilities in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the fundamentals of Physical AI and its role in robotics and automation.
• Engineer and code intelligent robotic systems suited for dynamic settings.
• Deploy AI models that facilitate autonomous decision-making in robots.
• Leverage simulation platforms for effective robotic testing and optimization.
• Manage key challenges including sensor fusion, real-time data processing, and energy efficiency.

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

This instructor-led live training in Hungary explores the principles of reinforcement learning and deep RL techniques such as PPO and DDPG. Participants will gain practical experience implementing algorithms using Python and PyTorch, integrating them with ROS 2 and OpenAI Gym, and training autonomous robots to resolve complex tasks.

In Hungary, this live training empowers advanced engineers with AI competencies focused on robotic perception, planning, and control. Learners will apply sensor fusion techniques, develop motion algorithms, and implement learning-based strategies to effectively integrate intelligent systems into smart manufacturing workflows.