Recently concluded Texprocess exhibition in Frankfurt, workwear
manufacturer Alsico EU and design software specialist Style3D/
Assyst attracted considerable attention by demonstrating two hu
manoid robots in protective clothing developed as part of its Robotic
Garment Design project.
The aim of the project is to create garments specifically for robots
operating in modern workplaces such as factories, logistics centres,
offices, corporate environments and public spaces.
Such robots, much like human workers, need protection against
environmental factors and workplace conditions, as well as improved
visibility and identification. Using Style3D’s digital design tools, Alsico
aims to bring new garment concepts to life in a virtual environment
using customised robot avatars.
“With Style3D, Alsico can prototype the next generation of workwear – garments designed not only for people, but also for robots,” says
Vincent Siau, managing director of Alsico EU, which is headquartered
in Ronse, Belgium.
By applying AI to pattern generation and garment construction,
Style3D/Assyst is helping to automate elements of the design process
that have historically relied on manual expertise. Fabric behaviour, fit
and motion can all be simulated with precision, giving designers
greater control while significantly reducing development time.
Designing apparel for robots, however, introduces new challenges – from accommodating mechanical joints to integrating durability and
performance features – and also opens up opportunities to rethink
garment architecture and explore new forms of expression.
SynReal: In parallel, SynReal is a Style3D specialised technology
platform developed in China and operating within the fast-evolving
field of physical artificial intelligence. As such, its represents a
notable extension of the company’s established expertise in high
fidelity simulation, moving beyond its origins in digital fashion and
textile modelling into the broader domain of robotics and embodied
AI.At its core, SynReal aims to address one of the most persistent
challenges in robotics development – the shortage of high-quality
training data. Unlike purely digital AI systems, robots that interact
with real-world environments require vast amounts of data reflecting
physical interactions, material behaviours and environmental
variability. Gathering such data in the real world is both time
consuming and expensive and SynReal aims to bypass this through
the generation of synthetic data within highly realistic simulated
environments.The platform combines advanced physics engines with
detailed digital environments, enabling the simulation of both rigid
and deformable materials.
This is important, since while many simulation platforms handle rigid
body dynamics effectively, modelling soft materials such as textiles
or flexible surfaces remains a significant technical hurdle. SynReal
leverages Style3D’s heritage in fabric simulation, applying similar
principles to broader physical scenarios. The result is a system
capable of replicating nuanced interactions that are essential for
training robots to operate reliably in complex, real-world conditions