Edge AI for Robots: TinyML, On-Device Inference & Optimization Training Course

This live, instructor-led training in Czech Republic empowers intermediate-level robotics engineers with practical expertise in autonomous navigation and SLAM utilizing ROS 2. The curriculum guides learners through integrating LiDAR sensors, implementing advanced mapping algorithms, simulating scenarios in Gazebo, and deploying robust navigation stacks on real-world physical robots.

This instructor-led training in Czech Republic covers computer vision for robotics using OpenCV and deep learning. Participants will learn to implement perception pipelines, integrate detection models, and deploy systems on embedded platforms for autonomous control.

This instructor-led, live training in Czech Republic (online or onsite) is aimed at 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 HRI course in Czech Republic focuses on voice, gesture, and collaborative control. It guides you in building intuitive, multimodal interfaces for safe human-robot collaboration, with an emphasis on practical design principles, speech recognition, gesture detection, and shared autonomy to boost both usability and safety.

This practical training in Czech Republic addresses ROS-PLC integration and digital twins within industrial automation. You will learn to synchronize robotic systems with PLCs, create digital replicas for simulation, and optimize production workflows via real-time data exchange and sophisticated monitoring methods.

This instructor-led live training in Czech Republic (online or onsite) targets engineers interested in learning how artificial intelligence applies to mechatronic systems.

By the conclusion 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.

An advanced training module in Czech Republic that covers the design and coordination of multi-robot systems. Learners will model swarm intelligence, implement distributed decision-making, and optimize inter-agent collaboration through hands-on simulations in ROS 2 and Gazebo, targeting practical real-world applications.

This instructor-led, live training in Czech Republic (online or onsite) targets advanced robotics engineers and AI researchers looking to leverage Multimodal AI. The course focuses on integrating diverse sensory data to build 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.
• Build robots capable of executing complex tasks in dynamic environments.
• Overcome challenges related to real-time data processing and actuation.

This live, instructor-led session in Czech Republic (conducted online or on-site) is tailored for intermediate-level participants seeking to refine their skills in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the fundamentals of Physical AI and its role in robotics and automation.
• Design and code intelligent robotic systems for dynamic environments.
• Implement AI models that facilitate autonomous decision-making in robots.
• Employ simulation tools to enhance robotic testing and optimization.
• Tackle key challenges, including sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in Czech Republic covers rapid prototyping for robotics using ROS 2 and Docker. Participants learn to build, test, and deploy modular robotic systems efficiently, gaining hands-on skills in containerization, simulation, and version control for scalable development.

This live, instructor-led training in Czech Republic explores the core principles of reinforcement learning along with advanced deep RL techniques such as PPO and DDPG. Participants will gain practical skills in implementing algorithms using Python and PyTorch, integrating them with ROS 2 and OpenAI Gym, and training autonomous robots to tackle complex operational challenges.

An advanced training program on Czech Republic focusing on deep learning for robotic manipulation. Master perception, grasp planning, and control using neural networks and ROS 2. Through hands-on simulation exercises, gain the skills to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.