Human-Robot Interaction (HRI): Voice, Gesture & Collaborative Control Training Course

This instructor-led, live training in the UK equips intermediate robotics engineers with hands-on skills in autonomous navigation and SLAM using ROS 2. Learn to integrate LiDAR sensors, implement mapping algorithms, simulate in Gazebo, and deploy real-world navigation stacks on physical robots.

This instructor-led training in the UK explores computer vision for robotics through OpenCV and deep learning. Learners will acquire the skills to build perception pipelines, integrate detection models, and deploy systems on embedded platforms to achieve autonomous control.

This live training in the UK guides intermediate engineers in deploying TinyML models for robotics. Learn to optimise 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 course in the UK (available online or on-site) is designed for intermediate-level learners who want to explore the function of collaborative robots (cobots) and other human-centric AI systems within modern professional environments.

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

• Understand the core principles of Human-Centric Physical AI and where it applies.
• Investigate the role of collaborative robots in driving workplace productivity.
• Identify and manage the complexities of human-machine interaction.
• Create workflows that enhance cooperation between human staff and AI-driven tools.
• Cultivate an environment that supports innovation and adaptability in AI-enhanced workplaces.

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

This instructor-led live training in the UK (available online or onsite) is tailored for engineers who wish to explore the applicability of artificial intelligence to mechatronic systems.

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

• Acquire an overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the concepts underlying neural networks and diverse learning methods.
• Select artificial intelligence approaches effectively to address real-life challenges.
• Implement AI applications in the field of mechatronic engineering.

An advanced training in the UK covering the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimise collaboration across agents through hands-on simulation in ROS 2 and Gazebo for real-world applications.

This instructor-led, live course delivered in the UK (online or on-site) targets senior robotics engineers and AI researchers. It focuses on utilising Multimodal AI to integrate heterogeneous sensory data, aiming to produce robots that are both more autonomous and efficient, with the ability to see, hear, and touch.

By the conclusion of this programme, 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 instructor-led, live training in the UK (available online or onsite) is tailored for intermediate-level participants aiming to elevate their capabilities in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Understand the principles of Physical AI and its role in robotics and automation.
• Design and programme intelligent robotic systems for dynamic settings.
• Implement AI models for autonomous decision-making in robots.
• Leverage simulation tools for robotic testing and optimisation.
• Address key challenges including sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in the UK covers rapid prototyping for robotics using ROS 2 and Docker. Participants will learn to build, test, and deploy modular robotic systems efficiently, acquiring hands-on skills in containerisation, simulation, and version control to support scalable development.

This instructor-led live training in the UK explores the core principles of reinforcement learning alongside deep RL techniques 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 resolve complex tasks.

An advanced training in the UK covering deep learning for robotic manipulation. Learn 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.

In the UK, this live training provides advanced engineers with the AI skills necessary for robotic perception, planning, and control. Learners will apply sensor fusion, develop motion algorithms, and deploy learning-based strategies to successfully integrate intelligent systems into smart manufacturing workflows.