Sewts
Canvas Category Machinery : Industrial Robot : Textiles
At sewts, we are bridging one of the last gaps of automation and opening up entirely new spheres of application for robotics. By providing robots with human-like perception skills, we make the automatic handling of easily deformable materials possible.
Assembly Line
👖 Sewts secures €7M Series A funding to transform the processing of easily deformable materials
Robotics startup sewts has successfully completed a €7 million Series A funding round. Founded in 2019 and based in Munich, sewts GmbH provides cutting-edge AI-embedded perception software, pushing the boundaries of robotics in the processing of easily deformable materials such as textiles and fois. The company has developed and demonstrated a unique technology that uses high-precision simulations to train machine learning algorithms efficiently. Combined with suitable hardware, it enables countless applications in industrial automation, like handling textiles in industrial laundries or manufacturing garments.
Sewts will use this fresh capital to progress with our growth targets internationally. These include launching further VELUM systems in international large-scale laundries and, as a next step, refining our prototype for the automated handling of returns in online shopping.”
🦾 Inside sewts’ textile-handling robots
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.