Pilot for Optimized Detection and Sorting of fruit

PODS

Proposing Institution: Big Data Innovation & Research Excellence - BI-REX

Name of the project’s Scientific Coordinator: Francesco Meoni

E-mail address of the project’s Scientific Coordinator: francesco.meoni@bi-rex.it

Other ECOSISTER partners involved in the project: Università di Bologna "Alma Mater Studiorum" (UNIBO), MISTER Smart Innovation S.C.R.L. (MISTER)

Coordinating Spoke: Spoke 3

Other Spokes involved in the project: Spoke 1

Name of partners based in the South: Bi-Rex (Palermo)

Project duration (in months): 13

Starting TRL: 4

End TRL: 6

ATECO/industrial sector of potential reference: Crop and animal production, hunting and related service activities

Smart Specialization Strategy: Agrifood

EU Taxonomy: Climate change adaptation

Abstract

The project "Pilot for Optimized Detection and Sorting of Fruit" (PODS) aims to design, develop, and prototype a pilot line featuring a collaborative system equipped with soft grippers and electro-adhesive pads. These grippers will gently manipulate fruits without causing damage.

Expected outcomes include:

increased efficiency
enhanced quality control
scalability of the pilot line

Automation will significantly reduce time and labor requirements, while real-time monitoring and precise handling will improve the overall quality of sorted fruit. The line will be designed to scale easily with growing demand, without compromising efficiency or quality.

Limitations of current technologies:

Mechanical jaws: bulky, heavy, slow, often damaging fruits due to crushing forces, and requiring complex force sensors and control algorithms.
Vacuum cups: energetically inefficient, unreliable, and prone to causing damage through high localized pressure.

Advantages of soft grippers with electro-adhesive pads:

gentle, efficient, and reliable handling
mild attractive forces distributed over wide areas
capacitive devices requiring minimal power
resilience to dust and dirt
compact, lightweight, and easily fabricated via additive manufacturing

Project structure (Work Packages):

WP1 (BI-REX): project management and impact generation, with a focus on Southern Italian regions.
WP2 (BI-REX): setup, technical coordination, and system integration of the pilot line at BI-REX Palermo. Activities include redesign of grippers, fabrication via additive manufacturing, laboratory validation, and integration into the sorting line.
WP3 (MISTER): development of a fruit quality monitoring system, including sensorized stations for ripeness assessment (e.g. ethylene detection). Tasks include sensor selection, calibration, optimization, and integration.
WP4 (UNIBO): development and integration of optimized electro-adhesive pads, building on research results from Spoke 1 (TRL4).

Expected impact:

Scientific: demonstration of the superiority of soft grippers with electro-adhesive pads in handling fruit quickly, reliably, and efficiently.
Technological: pilot line at BI-REX will validate the solution in a relevant environment, reaching TRL5–6, and showcasing collaborative productivity and safety in robot-human interaction.
Industrial: system adaptable to a wide variety of fruits (sizes, shapes, types). SMEs and companies, particularly in Southern Italian regions, will benefit from access to this technology, enabling them to transform production lines, reduce waste, improve product quality, and lower operational costs.

Beyond technical demonstration, the pilot line will serve as a practical platform for SMEs to evaluate and adopt the technology, fostering regional innovation and competitiveness.

Expected Results

Design, development and prototyping of a pilot line including a collaborative system with a soft gripper equipped with electro-adhesive pads capable of gently grasping and manipulating fruits without damaging them.

Expected Results

Increased efficiency: automation of the sorting process will significantly reduce the time and labor required.
Enhanced quality control: real-time monitoring and precise handling will improve the overall quality of the sorted fruit.
Scalability: the pilot line will be designed to scale up easily, accommodating increased demand without compromising efficiency or quality.

Final Results

Robotic Manipulation System:

Prototyping of a gripping system with flexible fingers and electro-adhesive fingertips to optimise delicate and versatile fruit handling.
Final results: improved gripping force; adaptability to different fruit sizes and shapes; and greater system reliability and durability.

Ripeness monitoring:

Development of a monitoring module based on embedded sensors with machine learning algorithms for data processing.
The final results are an optimised selection of target fruit based on ripeness level and the ability to differentiate between fruit.

Next Steps

Further developments and future collaborations

Improving the monitoring module by using high-resolution cameras.
Digital infrastructure and data analysis: creation of a cloud-HPC infrastructure to enable the advanced processing of data collected from the pilot line for AI analysis and real-time decision support in fruit and vegetable selection. This will allow differentiation between fruit to be shipped, stored, or sold locally.
Industrial testing for functional and performance validation and process optimization, with high market proximity, guaranteed by validated sensors, optimized grippers, and active industrial agreements, as well as strong technological relevance and competitive impact in Southern Italy.