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

This live, instructor-led training in Romania offers intermediate robotics engineers practical expertise in autonomous navigation and SLAM via ROS 2. Participants will master integrating LiDAR sensors, deploying mapping algorithms, conducting simulations in Gazebo, and implementing real-world navigation stacks on physical robots.

This instructor-led session in Romania explores the integration of computer vision and deep learning for robotics through OpenCV. Learners will develop the skills to construct perception pipelines, incorporate advanced detection models, and deploy autonomous control systems on embedded platforms.

This instructor-led, live training in Romania (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 Romania explores the realms of voice, gesture, and collaborative control. Participants will learn to construct intuitive, multimodal interfaces that facilitate safe human-robot collaboration. The curriculum emphasizes practical design principles, speech recognition, gesture detection, and shared autonomy to elevate both usability and safety.

This hands-on training in Romania addresses ROS-PLC integration and digital twins within the scope of industrial automation. Learners will acquire the ability to synchronize robotic systems with PLCs, create digital replicas for simulation, and refine production workflows through real-time data exchange and sophisticated monitoring techniques.

This instructor-led live training in Romania (online or onsite) is designed for engineers who want to explore the application of artificial intelligence to mechatronic systems.

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

• Gain a broad overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the core concepts of neural networks and various learning methods.
• Select the most effective artificial intelligence approaches for solving real-world problems.
• Implement AI applications in the field of mechatronic engineering.

Advanced training in Romania that covers the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimize collaboration across agents through hands-on simulation using ROS 2 and Gazebo, preparing them for real-world applications.

This instructor-led training in Romania (online or onsite) is designed for advanced robotics engineers and AI researchers looking to leverage Multimodal AI. The goal is to integrate diverse sensory data to build more autonomous and efficient robots that can see, hear, and touch.

Upon completion, 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.

This live, instructor-led training in Romania (available online or on-site) is designed for intermediate-level professionals seeking to enhance 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 principles of Physical AI and its practical applications in robotics and automation.
• Design and program intelligent robotic systems suited for dynamic environments.
• Integrate AI models to enable autonomous decision-making in robots.
• Apply simulation tools for effective robotic testing and optimization.
• Manage challenges related to sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in Romania focuses on rapid prototyping for robotics utilizing ROS 2 and Docker. Participants gain practical skills in building, testing, and deploying modular robotic systems, with a strong emphasis on containerization, simulation, and version control for scalable development.

This live, instructor-led session in Romania explores reinforcement learning principles and deep RL techniques such as PPO and DDPG. Attendees will implement algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to tackle complex challenges.

An advanced training program on Romania focused on applying deep learning to robotic manipulation. Master perception, grasp planning, and control utilizing neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptable grasping solutions on real-world robotic arms.