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Organization

DATALOGIC IP TECH SRL

Italian industrial automation company providing laser scanners, machine vision, and safe human-robot collaboration technology to manufacturing consortia.

Large industrial companymanufacturingITNo active H2020 projectsThin data (2/5)
H2020 projects
2
As coordinator
0
Total EC funding
€315K
Unique partners
25
What they do

Their core work

Datalogic IP Tech is the intellectual property and technology subsidiary of the Datalogic Group, a major Italian manufacturer of industrial automation equipment — including barcode readers, laser scanners, machine vision cameras, and industrial safety sensors. Their H2020 participation spans optical manufacturing design and human-robot collaboration safety systems, both of which map directly onto their commercial product lines. In research consortia they function as an industrial technology provider, contributing field-proven sensor and vision hardware rather than conducting foundational research. Their role in projects like ROSSINI — covering laser-based safety, robotic manipulators, and vision-guided automation — is an extension of the kind of technology they already deploy in factories across Europe.

Core expertise

What they specialise in

Machine vision and laser scanning systemsprimary
1 project

ROSSINI project lists vision system and laser scanner as core keywords, consistent with Datalogic's commercial sensor product portfolio.

Human-robot collaboration safetyprimary
1 project

ROSSINI explicitly covers safe automation, risk assessment, and robotic manipulator integration in manufacturing environments.

Optical design for manufacturingsecondary
1 project

NOLOSS focused on lossless photon management and optical design at different length scales, linked to their laser and optics manufacturing capabilities.

Validation and risk assessment for automationsecondary
1 project

ROSSINI keywords include validation and risk assessment, reflecting industrial-grade safety certification work typical of sensor manufacturers entering the collaborative robotics space.

Evolution & trajectory

How they've shifted over time

Early focus
Optical design, photon management
Recent focus
Human-robot collaboration safety

Their H2020 footprint spans only two projects between 2016 and 2018, so the keyword history is thin, but the directional shift is clear. Their first project (NOLOSS, 2016) had no descriptive keywords in the data and focused on optical manufacturing science — fundamental research adjacent to their photonics and optics product line. By 2018, with ROSSINI, every keyword in their profile points to applied industrial automation: human-robot collaboration, safe automation, laser scanners, risk assessment, robotic manipulators. This is a move from research-adjacent optical science toward practical factory-floor robotics safety — a shift that mirrors the broader Industry 4.0 transition happening across European manufacturing during that period.

They are moving their sensor and vision technology toward collaborative robotics safety — a high-growth area where their commercial laser scanner and machine vision products have direct application in certifying human-robot workspaces.

Collaboration profile

How they like to work

Role: specialist_contributorReach: European8 countries collaborated

Datalogic IP Tech has not coordinated any H2020 project, joining both times as a non-leading participant — once as a full partner and once as a third party. This is the pattern of a large industrial company that contributes proprietary hardware and know-how rather than driving academic research agendas. Despite only two projects, they have engaged with 25 unique partners across 8 countries, which means they were embedded in large, multi-partner consortia where their role was to provide industrial validation environments or technology access rather than research leadership.

With 25 unique consortium partners across 8 countries from just two projects, DLIPTECH has been placed inside large, geographically diverse research programs. Their network is European in scope, consistent with their position as an industrial technology provider sought out to give research consortia access to commercial-grade sensor hardware and manufacturing environments.

Why partner with them

What sets them apart

Datalogic IP Tech is a rare type of H2020 participant: a non-SME industrial company whose core commercial products — laser scanners, vision systems, safety sensors — are themselves the subject of the research. This means partners get more than a collaborator; they get access to production-grade hardware and a company with established manufacturing and certification pipelines. For consortium builders working in robotics safety, collaborative automation, or machine vision, Datalogic IP Tech brings industrial credibility and deployment realism that a university or research institute simply cannot provide.

Notable projects

Highlights from their portfolio

  • ROSSINI
    Directly reflects their commercial product portfolio — laser scanners, vision systems, and safe human-robot interaction — making this their most strategically coherent EU project and the clearest signal of where their technology fits in collaborative manufacturing.
  • NOLOSS
    Their only directly funded H2020 participation (EUR 315,408), covering optical design for manufacturing — a scientifically adjacent area to their core photonics and laser optics hardware.
Cross-sector capabilities
industrial safety and worker protectionmachine vision for quality controloptical sensing and photonicsrobotics and autonomous systems
Analysis note: Profile is based on only two H2020 projects over a narrow window (2016–2018), one of which was as a third party with no direct EC funding recorded. The organization appears to be the IP and technology subsidiary of the Datalogic Group, a well-established Italian industrial automation company — contextual knowledge of their commercial activities helps interpret what is otherwise a sparse project record. Treat sector and expertise conclusions as directionally reliable but not statistically robust.
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