Autonomous Navigation & SLAM with ROS 2 Training Course

This instructor-led training in Mexico focuses on robotics computer vision utilizing OpenCV and deep learning. Participants will master the implementation of perception pipelines, integration of detection models, and deployment of systems on embedded platforms for autonomous control.

This live training in Mexico guides intermediate engineers in deploying TinyML models for robotics. It covers optimizing inference for speed and energy, integrating AI into control systems, and developing autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led, live training in Mexico (online or onsite) is tailored for intermediate-level participants interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern work environments.

Upon completing this training, participants will be able to:

• Grasp the core principles of Human-Centric Physical AI and its practical applications.
• Analyze how collaborative robots contribute to enhancing workplace efficiency.
• Recognize and resolve issues related to human-machine interaction.
• Create workflows that maximize collaboration between employees and AI-driven systems.
• Foster a culture of innovation and adaptability within organizations using AI technology.

This practical HRI course in Mexico explores voice, gesture, and collaborative control. It teaches you to build intuitive, multimodal interfaces for safe human-robot collaboration, emphasizing practical design principles, speech recognition, gesture detection, and shared autonomy to improve usability and safety.

This practical training in Mexico addresses ROS-PLC integration and digital twins for industrial automation. It covers how to synchronize robotic systems with PLCs, create digital replicas for simulation, and enhance production workflows through real-time data exchange and advanced monitoring methods.

This instructor-led, live training in Mexico (online or onsite) is aimed at engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

By the end 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 program in Mexico focused on the architecture and coordination of multi-robot teams. Learners will master swarm intelligence modeling, distributed decision-making, and agent collaboration through hands-on simulations in ROS 2 and Gazebo, preparing them for real-world deployment.

This instructor-led, live training in Mexico (online or onsite) is designed for advanced robotics engineers and AI researchers who want to leverage Multimodal AI to integrate diverse sensory data. The goal is to build more autonomous and efficient robots that can perceive through sight, sound, and touch.

Upon completion of this training, 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 Mexico (available online or onsite) is designed for intermediate professionals looking to strengthen their skills in the design, programming, and deployment of intelligent robotic systems for automation and other domains.

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

• Comprehend the foundational principles of Physical AI and their role in robotics and automation.
• Develop and program intelligent robotic systems suited for dynamic operational environments.
• Deploy AI models that facilitate autonomous decision-making in robots.
• Apply simulation tools for effective robotic testing and performance optimization.
• Navigate complex challenges such as sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in Mexico focuses on rapid prototyping for robotics utilizing ROS 2 and Docker. Participants learn to efficiently build, test, and deploy modular robotic systems, developing hands-on expertise in containerization, simulation, and version control for scalable development.

This live, instructor-led training in Mexico explores the core principles of Reinforcement Learning and advanced deep RL methods such as PPO and DDPG. Participants will learn to implement these algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to handle complex operational tasks.

Explore this advanced Mexico training focused on applying deep learning to robotic manipulation. Master perception, grasp planning, and control systems using neural networks and ROS 2. Through hands-on simulation exercises, you will be prepared to effectively deploy intelligent, adaptable grasping solutions on real-world robotic arms.