Computer Vision for Robotics: Perception with OpenCV & Deep Learning Training Course

This live, instructor-led training in Latvia provides intermediate robotics engineers with practical skills in autonomous navigation and SLAM using ROS 2. The curriculum covers LiDAR sensor integration, mapping algorithm implementation, Gazebo simulation, and the deployment of real-world navigation stacks on physical robots.

This live training in Latvia 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 training on Latvia, delivered either online or on-site, is tailored for intermediate-level participants interested in exploring the influence of collaborative robots (cobots) and human-centric AI systems on modern workplaces.

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

• Understand the fundamental principles of Human-Centric Physical AI and its real-world applications.
• Explore the contribution of collaborative robots to enhancing operational productivity.
• Identify and resolve key challenges in human-machine interaction.
• Design workflows that foster optimal collaboration between humans and AI-driven systems.
• Champion a culture of innovation and adaptability in environments integrated with AI.

Explore this practical HRI course in Latvia, focusing on voice, gesture, and collaborative control. Build intuitive, multimodal interfaces that foster safe human-robot collaboration, with an emphasis on practical design, speech recognition, gesture detection, and shared autonomy to enhance both usability and safety.

This practical training in Latvia addresses ROS-PLC integration and digital twins within 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, conducted Latvia (either online or on-site), is designed for engineers looking to explore the application of artificial intelligence within mechatronic systems.

By the end of the session, participants will be equipped to:

• Develop a broad perspective on artificial intelligence, machine learning, and computational intelligence.
• Comprehend the principles of neural networks and distinct learning techniques.
• Effectively select AI methodologies for solving real-world issues.
• Integrate AI applications into mechatronic engineering practices.

An advanced training program in Latvia that focuses on the design and coordination of multi-robot systems. Participants will gain the ability to model swarm intelligence, implement distributed decision-making, and optimize agent collaboration through hands-on simulation using ROS 2 and Gazebo, preparing them for real-world applications.

This live, instructor-led training, offered in Latvia via online or on-site sessions, targets advanced robotics engineers and AI researchers aiming to apply Multimodal AI for the integration of varied sensory inputs. The objective is to enable the creation of more autonomous and efficient robotic systems that possess the capabilities to see, hear, and touch.

By the conclusion of this training, participants will be equipped to:

• Integrate multimodal sensing into robotic systems.
• Formulate AI algorithms for effective sensor fusion and decision-making.
• Develop robots that can manage complex tasks in fluid, dynamic environments.
• Overcome obstacles related to real-time data handling and actuation.

This instructor-led, live training in Latvia (available online or on-site) is designed for intermediate-level professionals aiming to strengthen their capabilities in designing, programming, and deploying intelligent robotic systems for automation and broader applications.

By the conclusion of this training, participants will have the ability to:

• Comprehend the fundamentals of Physical AI and its practical applications in robotics and automation.
• Design and program intelligent robotic systems suited for dynamic settings.
• Integrate AI models to support autonomous decision-making in robots.
• Employ simulation tools to enhance robotic testing and optimization processes.
• Tackle key challenges such as sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led session in Latvia focuses on rapid robotics prototyping via ROS 2 and Docker. Participants will acquire the ability to construct, test, and deploy modular robotic systems efficiently, while gaining practical experience in containerization, simulation, and version control for scalable development.

This instructor-led live training in Latvia delves into the principles of reinforcement learning and advanced deep RL methods such as PPO and DDPG. Participants will implement algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to tackle complex tasks.

An advanced training program in Latvia focusing on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control by utilizing neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent and adaptable grasping solutions on physical robotic arms.