ARTIFICIAL INTELLIGENCE
From code to context: How spatial AI is powering the next leap in manufacturing
Dijam Panigrahi, Co-founder and COO, GridRaster Inc.
Beyond the data-driven efficiencies of Industry 4.0, a new paradigm is emerging for manufacturers across every industry: Industry 5.0. This next evolution emphasises a human-centric, resilient, and sustainable approach, calling for a more symbiotic relationship between human workers and intelligent machines.
The goal is to leverage the precision and tireless nature of automation while keeping human ingenuity, judgment, and creativity at the core of the operation. This vision promises greater flexibility, higher quality, and improved safety, yet a massive, persistent hurdle stands in the way, particularly for small to mid-sized manufacturers: the high cost and debilitating complexity of industrial robotics.
For decades, deploying and reprogramming industrial robots has been a task reserved for highly specialised, six-figure engineers. Setting up a new task, be it an inspection route or a part manipulation sequence, can take hours, days, or even weeks of meticulous, line-by- line coding and calibration. This lengthy, expensive process makes automation uneconomical for short-run production cycles or high-mix, low-volume scenarios, effectively creating a technological moat that keeps advanced automation out of reach for a vast segment of the industrial market.
However, a confluence of technologies, namely Spatial AI and Mixed Reality (XR), is poised to shatter this
8
status quo, fundamentally changing the economics and accessibility of industrial automation and shrinking a multi-hour robotics setup to mere minutes.
The shift to “Spatial Intelligence” The core limitation of traditional industrial robotics is a lack of real-world context. A robot knows where its own joints are, but it doesn’t intuitively “know” the factory floor. It operates in a rigid, pre-programmed void. This is where the powerful combination of Artificial Intelligence and Mixed Reality steps in to create a new layer of capability known as Spatial AI.
Spatial AI goes far beyond a static digital twin. It involves creating a persistent, dynamic, and real-time map of the physical factory environment, a living digital blueprint. Mixed Reality devices, such as industrial-grade headsets or powerful tablets, use an array of cameras and sensors to rapidly ingest and process three-dimensional data from the real world. AI algorithms then process this data to understand the semantic meaning of the physical space. This process gives the robot its crucial missing piece:
LUBE MAGAZINE AR TIFICIAL INTELLIGENCE DECEMBER 2025
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28
