Sewts

Assembly Line

🦾 Inside sewts’ textile-handling robots

📅 Date:

✍️ Author: Brianna Wessling

🔖 Topics: Industrial Robot, Convolutional Neural Network

🏭 Vertical: Textiles

🏢 Organizations: sewts, IDS Imaging


Traditionally, clothing has been a challenge for robots to handle because of its malleability. Currently, available software systems and conventional image processing typically have limits when it comes to easily deformable material, limiting the abilities of commercially available robots and gripping systems.

VELUM, sewts’ robotic system, is able to analyze dimensionally unstable materials like textiles and handle them. This means VELUM can feed towels and similar linen made of terry cloth easily and without creases into existing folding machines.

sewts developed AI software to process the data supplied by the cameras. This software uses features like the course of the seam and the relative position of seams to analyze the topology of the textiles. The program classifies these features according to textile type and class, and then translates these findings into robot commands. The company uses Convolutional Neural Networks (CNNs) and classical image processing to process the data, including IDS peak, a software development kit from IDS.

Read more at The Robot Report