Making the textile industry more sustainable is the aim of the transnational CoboSort research project: garments are sorted automatically with the help of a robotic system. It doesn’t matter whether they are fully, partially, or not packed. The workers train the robot via an intuitive interface. This can lead to new business models that reduce the consumption of raw materials and the amount of waste generated by fashion. The DIGITAL Institute at JOANNEUM RESEARCH is responsible for developing the software.
Sorting returned and no longer used collected garments is repetitive, strenuous, and tiring for workers. The introduction of a collaborative robot assistant (cobot), which combines image processing sensors, grippers, and artificial intelligence, represents a viable alternative. It is also expected to positively impact the distribution of second-hand items on the fashion market and the possibility of affordable business models with a limited environmental footprint.
CoboSort: recognizing, gripping, discarding, and learning
CoboSort focuses on developing machine learning models and robotic grippers and their integration into a reliable and comprehensive collaborative robot system. This enables automated picking to support the sorting of fully, partially or unpacked garments. “This is becoming increasingly important in times of online retail because returns are generated in large quantities and are often no longer properly packaged,” reports Olaf Kähler from DIGITAL. An intelligent image recognition system including AI for recognition and a gripper system for gripping the garments work together. All of this takes place in an environment in which humans and robots work together directly. “Our institute’s contribution is the software, the ‘brain’ so to speak, which tells the robot arm where to reach next,” continues Kähler. “The difficulty here is that items of clothing are soft and – if they are not packed in a plastic bag like new items – cannot simply be gripped with a suction gripper. It is also important that garments are picked up individually and placed on the conveyor belt, as double gripping can lead to a backlog later on.”
Environmentally friendly business models
The collaborative robot system sorts mixed and randomly arranged clothing packages, requires little space, is modular, and safe and its functions can be reconfigured. Compared to current sorting solutions, it represents a moderate investment and paves the way for decentralized and flexible redistribution systems that support the emergence of new forms of e-commerce for unused or previously worn garments and recycling. By reducing the continuous production of new garments, the impact on the environment is also reduced.
Change in the fashion industry
This new approach enables synergies between fashion companies and end customers, reducing the production costs of garments and indirectly reducing raw material consumption and waste. Positive effects can also be expected in social terms: instead of performing repetitive, wear-and-tear activities, the labor force is given a proactive role. Using an intuitive interface that can also be operated by non- experts, they train the machine learning models and support the cobot in the event of an error. Major international fashion chains have already shown interest.
Further information:
Dr Olaf Kähler
JOANNEUM RESEARCH DIGITAL
Steyrergasse 17, 8010 Graz
Tel: +43 664 602 876 2035
Mail: olaf.kaehler@joanneum.at
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