Training Physical AI with the Digital Twin: A Faster Path to Flexible Robotics

Automation has been a key part of manufacturing for over a century now, from the simple assembly lines of the past to the advanced, autonomous robotics of today. As the stresses placed on manufacturing systems continue to increase, however, the abilities of automated systems must increase as well. To meet the manufacturing demands of the 21st century, factory robotics must move beyond inflexible, hard-coded orders and gain the ability to quickly adapt to changing conditions — whether they be sudden business demands or new production requirements. This level of flexibility requires artificial intelligence (AI) certainly, but not just any AI; rather AI that can understand and interact with the real world. In other words, physical AI.