The development is intended to support system integrators tasked with deploying and maintaining AI-powered automation in complex and highly variable warehouse environments.
According to ABB Robotics, the upgraded Fashion Inductor is designed to address the unique challenges of the fashion logistics sector, where the diversity of products, packaging types and operating conditions has historically complicated automation efforts.
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With the integration of the AI Robot Trainer, the company said the solution can reduce engineering and commissioning workloads by as much as 75%.
This is achieved through pre-trained AI vision models tailored for fashion logistics, specialised application tools, and rapid retraining capabilities.
The company explained that these new functions enable system integrators to adapt and optimise robotic cells as business needs change, without requiring advanced expertise in AI.
ABB Robotics business line industries managing director Craig McDonnell said: “Physical AI fundamentally changes what robots can do in industrial applications. Some of the greatest opportunities for physical AI are in applications that have traditionally been difficult to automate because of high variability.
“Fashion Inductor with AI Robot Trainer is our first end-to-end vision-based physical AI solution, demonstrating how intelligent automation can be deployed, operated and continuously optimised at industrial scale, helping system integrators accelerate deployment, reduce project risk and maintain performance over time.”
Key technical upgrades include a new digital twin capability, a virtual replica of the module’s software environment, that connects ABB’s Application Controller Platform, Automatic Path Planning system, AI Robot Trainer, and RobotStudio software.
ABB Robotics stated this digital twin feature is intended to speed up commissioning and offer greater setup flexibility, including integration with third-party hardware such as grippers. The solution also facilitates continuous improvement over the lifecycle of the automation cell.
According to the company, the AI Robot Trainer uses a closed-loop workflow to monitor robot performance, flag anomalies, generate new training data, and roll out updated models back to the physical robots. This loop supports continuous alignment with operational targets as conditions and product flows evolve.
The system lifecycle is supported by ABB Robotics’ core platforms, including the RobotStudio for virtual design, simulation and validation, and the OmniCore robot controller for production execution.
Fashion Inductor is the first application in ABB Robotics’ wider deployment of vision-based physical AI, which the company links to its development of Autonomous Versatile Robotics (AVR).
The company plans to extend the AI Robot Trainer approach to other vision-based applications through the first quarter of 2027.
