CoboSort Project

CoboSort project aims to push the garment market toward a sustainable economy by means of circular and green actons enabled by the adopton of intelligent systems for effectve management of new, returned or used clothing.
Nowadays the sorting actions required to manage re/placing of garments involve teams of operators for picking and sorting operatons, that are repetitive, intentive and wearing. Adoption of a collaborative robotic assistant, mixing of vision sensors, grippers and artificial intelligence could be a feasible alternative.
CoboSort focuses on the development of machine learning models and robot grippers, as well as their integration within a reliable and inclusive collaborative robotic induction system that enable automated picking to support sorting of full/partally/not packaged pieces of clothes.
The proposed solution would provide a solution that positively impact on the spread of used item in fashion market opening for a more affordable business models with a limited environmental footprint.

The collaborative robotic solution developed in this project will enable fashion companies to embrace new business models, more sustainable, greener, and human-inclusive. To this aim, the cobotic system is expected to be able to sort a mixture and randomly arranged garment packages. Thanks to its limited footprint, modular architecture, intrinsic safety, and reconfigurable features, this cobotic system represents a moderate investment compared to current sorting solutions, which paves the way for decentralized and flexible redistribution systems to support the rise of new e-commerce forms for garments unused, unwanted, and new as well.
Thanks to this new approach, a synergic action between fashion companies and the final customers is possible that cuts the production costs of garments, and indirectly sustains the reduction of raw material consumption, minimization of waste production, and all those actions connected to the production of new clothes, such as new cultures, use of pesticide, textile treatments, just to cite a few.
This will have a beneficial impact also in social terms. The working force involved in the current sorting solutions is moved from repetitive, wearing operations to a proactive role to teach and enhance machine learning models (via an intuitive interface to be operated by non-experts in robotics) or to recover the cobot in case of failures. Basically, by the introduction of these cobotic systems, fashion companies will be able to embrace rising business models with affordable costs, more effective/resilient supply chains thanks to local redistribution points, reach more customers with limited economical resources with a reduced impact on the environment due to conƟnuous production of new garments of clothing.