TESTE

GRIPIT addresses a long-standing problem in the textile industry: handling flexible textile materials that have no rigidity of their own. This is still a manual operation, which results in quality that varies from piece to piece and higher operating costs.
The project sets out to develop an intelligent robotic gripper, with enhanced adhesion and active vacuum generation, able to handle textile structures of different types, densities and fibre compositions.
The gripper will be controlled by machine learning algorithms developed specifically within this project, allowing it to adapt more efficiently to the characteristics of each material processed.
Synere's role in this project is to turn concept into machine. It covers the mechanical engineering of the gripper, the prototype build and the test campaign with real materials, the stage where the solution leaves the drawing board and meets production conditions.