If you are a packaging plant dealing with perishable fruits that bruise easily — this project developed a Smart Sensing Suite that grades quality and a self-adaptive handling system that picks up soft products without causing damage.
AI-Driven Robotic Handling and Packaging for Soft and Deformable Products
Imagine trying to pick up a ripe tomato or a piece of clothing with a rigid metal claw; you'd likely crush or drop it. This project creates 'smart hands' and sensors that can feel and adjust their grip for delicate items. It also uses AI to reorganize factory lines on the fly so they can switch between different products without stopping for hours.
What needed solving
Robots struggle to handle soft, deformable, or delicate items like food and clothes without damaging them. Additionally, production lines are often too rigid to quickly adapt to changing product mixes or fresh market demands.
What was built
Three technology suites: Smart Sensing (for quality grading), Self-Adaptive Handling (for damage-free picking), and Agile Reconfigurable Tech (AI for flow synchronization).
Who needs this
Who can put this to work
If you are a warehouse operator dealing with diverse, deformable fabric items — this project developed robotic manipulation systems that can re-orient soft products in a human-oriented environment to speed up sorting.
If you are a logistics provider dealing with a high variability of product mixes — this project developed AI-based solutions for adaptive control and synchronization of flows to improve customer response time.
Quick answers
What is the cost or price of these solutions?
Based on available project data, specific pricing for the suites is not provided, although the project aims to create a cost-effective sensing solution for grading delicate products.
Can this be implemented at an industrial scale?
Yes, the project validates its solutions through 4 industrial pilots involving different product surfaces and consistencies to ensure scalability in real-world factory settings.
How is the IP and licensing handled?
Based on available project data, the project has identified three Key Exploitable Results (KERs) in the form of 'AGILEHAND SUITES' which are the primary targets for commercial exploitation.
How does this integrate with existing production lines?
The project provides a Reference Architecture for smart manufacturing that covers business, usage, functional, and implementation viewpoints to facilitate integration.
What is the timeline for deployment?
The project period runs from 2023-01-01 to 2025-12-31, suggesting that the final validated solutions will be available by the end of 2025.
Who built it
The consortium is well-balanced for commercialization, featuring 22 partners across 8 countries. With a 32% industry ratio (7 industrial partners) and 10 SMEs, there is a strong bridge between academic research (5 universities, 4 research centers) and market application, ensuring the technology is grounded in industrial needs.
Contact Università Politecnica delle Marche for technical specifications on the AGILEHAND SUITES.
Talk to the team behind this work.
Contact us to connect with the AGILEHAND consortium for pilot integration.