Physical AI describes intelligent systems that can sense, interpret, and act in real environments. Think of self-driving cars navigating busy streets, robotic arms assembling machinery with precision, or smart grids adapting in real time to energy demands.

Claire chatted to Amir Patel from University College London about designing robots with the agility and manoeuvrability of a cheetah.

Amir Patel is an Associate Professor of Robotics & AI in the Department of Computer Science at University College London (UCL). His research uses robotics methods—sensor fusion, computer vision, mechanical modelling, and optimal control—to understand and quantify animal locomotion, especially high-speed predators such as the cheetah, and to translate these insights into bio-inspired machines. Previously, he served on the faculty of Electrical Engineering at the University of Cape Town, where he founded and directed the African Robotics Unit (ARU).

Equipped with advanced mapping, multi-sensor vision and zone-based safety, the system navigates real-job sites with confidence—handling up to 6,000 sq ft/hour and supporting pressure-wash rigs up to 12 GPM and 4,500 PSI.