FOCUS ON AI
AI : FROM PERCEPTION TO PHYSICAL REALITY
Image : Shutterstock . com .
“ The transformative potential of AI for industrial robotics comes under the spotlight .”
Generative AI is demonstrating its potential to revolutionise industrial robotics , paving the way for more intelligent , adaptable and autonomous machines . The journey from Perception AI to Physical AI , powered by Generative AI , is chronicled here and marks a pivotal moment in robotics and automation .
A
modern automotive assembly line is a marvel of modern engineering . Suddenly , it grinds to a halt . What happened ? It turns out that a misaligned car door caught the pre-programmed robots off guard . A simple anomaly , but one that is typical of today ’ s factories and highlights the current limitations of industrial robots , is that they excel in controlled environments , but can fall short in unexpected situations .
This is where Artificial Intelligence , especially Generative AI , comes in . It promises a new era of intelligent automation , potentially creating a new breed of intelligent , adaptable and autonomous industrial robots .
For decades , industrial robots have improved manufacturing efficiency . But so far , they have been limited to pre-determined actions in highly controlled environments .
By
Hannover Messe
They are sophisticated tools that lack the intelligence to truly understand and respond to the complexities of the real world . In a recent keynote , Jensen Huang ( CEO of leading AI chipmaker , NVIDIA ) outlined this transformative vision : AI evolving from mere perception to embodying physical action , a concept he calls “ Embodied AI ” or “ Physical AI ”.
Perception AI in industrial robotics
Perception AI , an earlier form of AI ( sometimes intertwined with ‘ classical AI ’) entailed giving machines the ability to sense and interpret their environment . It gave robots their ‘ eyes ’ and ‘ ears ’. For industrial applications , it manifested in several ways as detailed below .
■ Computer vision : As perhaps the most prominent example , camera-equipped robots could “ see ” and interpret images . This revolutionised quality control , with robots inspecting products faster and with more precision than humans .
■ Sensors for object recognition and localisation : Robots started using proximity sensors , laser scanners and RFID readers to identify and locate objects , crucial for pick-and-place and sorting tasks .
22 | ismr . net | ISMR February 2025