Autonomous Navigation & SLAM with ROS 2 Training Course

This instructor-led training in New Zealand explores the application of computer vision in robotics through OpenCV and deep learning. Participants will master the creation of perception pipelines, the integration of detection models, and the deployment of systems on embedded platforms to achieve autonomous control.

This live training in New Zealand 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 instructor-led, live training in New Zealand (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:

• Grip 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 hands-on HRI course in New Zealand explores voice, gesture, and collaborative control. Participants will learn to build intuitive, multimodal interfaces that support safe human-robot collaboration, with a focus on practical design principles, speech recognition, gesture detection, and shared autonomy to improve both usability and safety.

This hands-on training in New Zealand covers ROS-PLC integration and digital twins for industrial automation. Learn to synchronize robotic systems with PLCs, develop digital replicas for simulation, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led, live training in New Zealand (available online or on-site) is designed for engineers who wish to explore how artificial intelligence can be applied to mechatronic systems.

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

• Gain a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the fundamental concepts of neural networks and various learning methodologies.
• Select appropriate artificial intelligence approaches to effectively address real-world problems.
• Implement AI-driven applications within mechatronic engineering contexts.

An advanced training in New Zealand focusing on the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimise agent collaboration through hands-on simulation in ROS 2 and Gazebo, preparing them for real-world applications.

This instructor-led, live training in New Zealand (available online or onsite) is designed for advanced-level robotics engineers and AI researchers who wish to leverage Multimodal AI to integrate diverse sensory data, creating more autonomous and efficient robots that can see, hear, and touch.

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

• Implement multimodal sensing within robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots capable of performing complex tasks in dynamic environments.
• Tackle challenges related to real-time data processing and actuation.

This instructor-led, live training on New Zealand (available online or onsite) is tailored for intermediate-level professionals aiming to strengthen their skills in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the principles of Physical AI and its role in robotics and automation.
• Design and programme intelligent robotic systems for dynamic environments.
• Implement AI models to support autonomous decision-making in robots.
• Apply simulation tools for robotic testing and optimisation.
• Tackle challenges such as sensor fusion, real-time processing, and energy efficiency.

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

This instructor-led live training in New Zealand delves into reinforcement learning principles and deep RL techniques such as PPO and DDPG. Participants will apply these algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to resolve complex tasks.

An advanced training module on New Zealand focused on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control using neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.