SOFTMANBOT · Project

Robots That Handle Soft, Flexible Materials in Factory Production Lines

manufacturingPilotedTRL 6

Imagine trying to get a robot to fold a shirt or handle a floppy piece of leather — most industrial robots can only deal with rigid, predictable objects. SOFTMANBOT built smart grippers with touch sensors and AI vision so robots can finally pick up, move, and manipulate soft materials like textiles, rubber, and foam without damaging them. They tested this in four real factory settings: toys, textiles, footwear, and tyres. The goal is to let robots work alongside people on the messy, hands-on tasks that have kept these industries dependent on manual labour.

By the numbers

pilot demonstrators in real industrial environments

manufacturing sectors covered (toy, textile, footwear, tyre)

consortium partners

countries in consortium

industry partners in consortium

total project deliverables

58%

industry ratio in consortium

The business problem

What needed solving

European manufacturers in labour-intensive sectors like textiles, footwear, toys, and tyres still rely heavily on manual handling of soft, flexible materials because conventional industrial robots cannot grip or manipulate deformable objects reliably. This drives up labour costs, limits production speed, and makes it harder to compete with low-wage manufacturing regions. The physical demands of repetitive contact-based tasks also create ergonomic problems for workers.

The solution

What was built

The project built a complete robotic system with three core components: a perception system using AI vision to track deformable objects and human operators, a multi-sensor control platform for shape and contact control, and smart dexterous grippers with embedded tactile sensors. These were integrated into first demonstrator prototypes that progressed from mock-ups to real industrial demonstrators, tested across 4 factory pilot sites in toy, textile, footwear, and tyre manufacturing. A total of 28 deliverables were produced.

Audience

Who needs this

Textile and garment manufacturers automating fabric handlingFootwear producers seeking to automate leather and flexible material assemblyTyre manufacturers handling heavy deformable rubber componentsToy manufacturers with labour-intensive soft-material processesSystem integrators building robotic solutions for soft-material industries

Business applications

Who can put this to work

Textile & Apparel Manufacturing

SME

Target: Textile factories and garment manufacturers handling fabric cutting, folding, and assembly

If you are a textile manufacturer dealing with high labour costs and difficulty automating fabric handling — this project developed smart robotic grippers with tactile sensors and AI vision that can grasp, manipulate, and position soft fabrics without damage. The system was demonstrated in a real textile production environment as one of 4 pilot demonstrators across 4 manufacturing sectors.

Footwear Production

mid-size

Target: Shoe manufacturers handling leather, rubber soles, and flexible upper materials

If you are a footwear producer struggling to automate assembly steps involving flexible leather and rubber components — this project built a robotic system with dexterous grippers specifically designed for contact-based tasks on deformable materials. The technology was piloted in a real footwear factory setting with human-robot collaboration, letting operators and robots share the workload safely.

Tyre Manufacturing

enterprise

Target: Tyre and rubber product manufacturers handling heavy deformable materials

If you are a tyre manufacturer where workers manually handle heavy, flexible rubber components in repetitive processes — this project created multi-sensor controlled robots that adapt grip and force in real time based on material deformation. One of the 4 industrial pilot demonstrators was specifically in the tyre sector, with 12 consortium partners contributing to the design.

Frequently asked

Quick answers

What would it cost to implement this robotic system in our factory?

The project data does not include specific pricing or implementation costs. As a research project with 12 partners across 5 countries, the technology was developed and demonstrated but commercial pricing has not been published. Contact the consortium for licensing or integration cost estimates.

Can this scale to a full production line, not just a lab demo?

SOFTMANBOT was specifically designed to move beyond lab conditions. Demonstrations were conducted in 4 real industrially relevant environments across toy, textile, footwear, and tyre sectors. The project explicitly aimed for transferability, scalability, and large-scale deployment assessment.

Who owns the IP and can we license this technology?

The consortium of 12 partners across 5 countries jointly developed the technology, with 7 industry partners and 2 SMEs involved. IP ownership follows the EU grant agreement terms. Licensing discussions would go through the coordinator, CLERMONT AUVERGNE INP in France.

Does this work safely alongside human workers?

Human-robot collaboration was a core design requirement, not an afterthought. The project integrated safety, ergonomics, adaptability, acceptance, and user experience from the start. The system is designed so robots assist operators on contact-based tasks rather than replacing them.

What types of soft materials can the robots actually handle?

The system was tested across 4 distinct material types in the pilot sectors: fabrics (textiles), leather and synthetics (footwear), rubber (tyres), and mixed soft materials (toys). The smart dexterous grippers use tactile sensors to detect contact state and adapt grip in real time to different material properties.

How long would integration take in an existing production line?

Based on available project data, the project ran from October 2019 to March 2023, producing 28 deliverables including first demonstrator prototypes that transitioned from mock-ups to real industrial demonstrators. Exact integration timelines for a specific factory would depend on the application and would require discussion with the consortium.

Consortium

Who built it

The SOFTMANBOT consortium is heavily industry-oriented, with 7 out of 12 partners (58%) coming from industry — a strong signal that this technology was built for real factory floors, not academic papers. The consortium spans 5 countries (Albania, Germany, Spain, France, Italy), coordinated by CLERMONT AUVERGNE INP in France, a higher education institution. With 2 SMEs in the mix alongside 3 research organizations and 2 universities, the project balances scientific depth with practical manufacturing know-how. The 4 distinct pilot sectors (toy, textile, footwear, tyre) suggest the technology was designed to be transferable rather than locked into a single application.

CLERMONT AUVERGNE INPCoordinator · FR
INDUSTRIA AUXILIAR JUEMA SLparticipant · ES
INSTITUTO TECNOLOGICO DEL CALZADO Y CONEXASparticipant · ES
ASOCIACION DE INVESTIGACION DE LA INDUSTRIA DEL JUGUETE CONEXAS Y AFINESparticipant · ES
FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIAparticipant · IT
MANUFACTURE FRANCAISE DES PNEUMATIQUES MICHELINparticipant · FR
STAM SRLparticipant · IT
SORBONNE UNIVERSITEparticipant · FR

How to reach the team

CLERMONT AUVERGNE INP (France) — higher education institution coordinating 12 partners. Use SciTransfer to get a warm introduction.

Order a report on this consortium See CLERMONT AUVERGNE INP profile →

Next steps

Talk to the team behind this work.

Want to explore how SOFTMANBOT's soft-material robotic handling could fit your production line? SciTransfer can arrange a direct introduction to the right consortium partner for your sector.

Order a report on this topic More in Manufacturing & Industry 4.0