Artificial Intelligence (AI) for Robotics Training Course

This live, instructor-led session in Taiwan provides intermediate robotics engineers with practical expertise in autonomous navigation and SLAM using ROS 2. Participants will master the integration of LiDAR sensors, the implementation of mapping algorithms, simulation in Gazebo, and the deployment of navigation stacks on real-world physical robots.

This instructor-led training in Taiwan focuses on applying computer vision to robotics through OpenCV and deep learning. Learners will master the implementation of perception pipelines, integration of detection models, and deployment of systems on embedded platforms to achieve autonomous control.

This live session in Taiwan supports intermediate engineers in deploying TinyML models for robotics. Participants will learn to optimize inference for speed and energy efficiency, integrate AI into control systems, and develop autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led, live training in Taiwan (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 Taiwan addresses voice, gesture, and collaborative control. It guides learners in building intuitive, multimodal interfaces for secure human-robot collaboration, emphasizing practical design principles, speech recognition, gesture detection, and shared autonomy to boost usability and safety.

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

This instructor-led live training in Taiwan (online or onsite) is tailored for engineers interested in applying artificial intelligence to mechatronic systems.

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

• Obtain a comprehensive understanding of artificial intelligence, machine learning, and computational intelligence.
• Grasp the fundamental concepts of neural networks and various learning methodologies.
• Effectively select appropriate artificial intelligence approaches for real-world challenges.
• Implement AI solutions within mechatronic engineering contexts.

An advanced program in Taiwan that focuses on the design and coordination of multi-robot systems. Learners will acquire the skills to model swarm intelligence, implement distributed decision-making, and enhance inter-agent collaboration through hands-on simulation using ROS 2 and Gazebo, applicable to real-world contexts.

This instructor-led, live training in Taiwan (online or onsite) is designed for advanced robotics engineers and AI researchers who aim to leverage Multimodal AI to integrate diverse sensory data, creating more autonomous and efficient robots capable of seeing, hearing, and touching.

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 performing complex tasks in dynamic environments.
• Address challenges associated with real-time data processing and actuation.

This live, instructor-led training in Taiwan, offered online or onsite, is tailored for intermediate-level participants seeking to refine their skills in designing, programming, and deploying intelligent robotic systems for automation and advanced use cases.

Upon completion, participants will be equipped to:

• Grasp the foundational principles of Physical AI and its practical applications in robotics and automation.
• Engineer and code intelligent robotic systems tailored for dynamic environments.
• Integrate AI models to enable autonomous decision-making capabilities in robots.
• Utilize simulation platforms for rigorous robotic testing and system optimization.
• Navigate complex challenges, including sensor fusion, real-time processing, and energy efficiency.

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

This live, instructor-led session at Taiwan delves into the core principles of reinforcement learning and advanced deep RL techniques such as PPO and DDPG. Learners 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 in Taiwan focusing on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control using neural networks and ROS 2. Hands-on exercises in simulation prepare you to deploy intelligent, adaptable grasping solutions on real robotic arms effectively.