Funded Projects

Funded Projects

Funded Projects

Datalogic is active in identifying the most suitable and available funding lines, at regional, national and European level, to co-finance its research and development activities. Through the systematic monitoring of the opportunities offered by the European Horizon 2020 program and the operational programs, both national (PON) and regional (POR), the company intends to preside over and participate in the moments of highest technological dialogue, at national and European level. By defining the role that it can take from time to time within the sub-programs (coordinator, end user, technology developer, etc.), Datalogic intends to support research on innovation, the creation of technological poles and the consequent increase in job openings , its own competitiveness and that of the system, and the economic growth and sustainable development of the reference market. The main co-financing funds that allow the company to pursue its investment policy in the fields of innovation and of the digital agenda are the European Regional Development Fund (ERDF) and the European Social Fund (ESF). Below are the projects in which the company took part.

The AIDA Project

Datalogic has received a contribution of 846,000 Euros for Research & Development activities from a project financed by the Emilia Romagna Region (POR FESR 2014-2020). The project presented by Datalogic, called AIDA (Adaptive Industrial Automation through cyber-physical vision systems), was top position of the "type B" ranking which includes research and development activities aimed at introducing new products or services in the market, or adoption of new production technologies that foresee new investments and production expansions in the regional territory and can have an impact on new employment in the reference sector.

The strong diffusion of digital technologies in factories is now a fact, but recent initiatives for Industry 4.0, have introduced a new element: the Cyber-Physical System (CPS), the integration of physical and IT devices not only at machine level but also at factory or even supply chain level.

The transition requires a real change of mentality. Products intended for industrial automation must "work in a group". They must perform and be flexible to adapt to different working conditions, to communicate with standard protocols of products from other vendors and to provide all the additional information needed to optimize the system and make it robust.

The goal of the AIDA project was to rethink many of our products in terms of CPS and to develop the technologies necessary for this purpose.

Among Datalogic's many products in the field of industrial automation, we have focused on some to make them increasingly adherent to the new paradigms, in particular: smart readers, vision sensors, vision systems and photocells and safety barriers.

The various prototypes developed within AIDA were used to build a CPS demonstrator. In the demonstrator all devices form a network and communicate with each other using the standard OPC-UA protocol.

The AIDA project is fully part of the “Industry 4.0” model, as it will allow Datalogic and manufacturers of automation solutions to equip themselves to meet the challenges of advanced manufacturing in terms of interconnection and exploitation of the potential of embedded systems.

The Rossini Project

Datalogic is the coordinator of the consortium created to participate in the European framework program Horizon 2020 on "Effective Industrial Human-Robot Collaboration" with the ROSSINI project (RObot enhanced SenSing, INtelligence and actuation to Improve job quality in manufacturing).

The ROSSINI project aims to develop a disruptive, inherently safe hardware-software platform for the design and deployment of human-robot collaboration (HRC) applications in manufacturing. By combining innovative sensing, actuation and control technologies (developed by world market leaders in their field), and integrating them in an open development environment, the ROSSINI platform will deliver a set of tools which will enable the spread of HRC applications where robots and human operators will become members of the same team, increasing job quality, production flexibility and productivity. Thanks to enhanced robot sensing capabilities, the deployment of artificial intelligence to optimise productivity and safety, and native collaborative manipulation technologies, ROSSINI will deliver high performance HRC workcells, combining the safety of traditional cobots with the working speed and payloads of industrial robots.

The five main objectives of the project are:

  1. Design an intelligent and safe sensor system (RS4) with high detection and localization capabilities for monitoring the working environment, and a "Safety-Graded" module for data processing.
  2. Develop a "Safety-Aware" control architecture of the cognitive perception of the robot to manage the planning and optimal execution of activities while guaranteeing operator safety.
  3. Develop a range of “Collaborative by Birth” robotic arms with new integrated safety features.
  4. Develop predictive algorithms that facilitate the adaptation of the robot to operator dynamics.
  5. Integrate all the technological components developed by ROSSINI into a single intrinsically safe platform for the development of HRC applications.

The NOLOSS Project

The target of this project is to prepare and train future engineers for the design challenges and opportunities provided by modern optics technology. Such challenges include lossless photon management, modelling at the system, components and feature levels, and the link between design and technology. Today all optical designs are often perceived to be following different approaches, namely geometrical optics, physical optics and nano-photonics. Traditionally these approaches are linked to the different lengths-scale that are important to the system.

A design for manufacture of next generation optical applications needs to bridge the gap between the different length-scales and to consider the design at a holistic level. At the core are optical simulation models developed and used in academic research and those used for optical designs in industry.

The SCaVa Project


Stereo Camera Validation - SCaVa is the name of the project won by CRIT, technology innovation centre in Vignola (Modena), and Datalogic, global leader in the automatic acquisition of data and industrial automation. The project, for a duration of 9 months, proposes a validation method to be applied to 2 stereocameras, able to detect the arm and body of a worker, in order to test them within an innovative protection system. This approach represents a keystone in the validation of safe human-robot interaction in the factory.

SCaVa completes the activity carried out in ROSSINI, a transnational project about collaborative robotics which involves both companies and where Datalogic designed and developed a first version of the 2 stereocameras.

In Scava the stereocameras will be tested in compliance with the existing safety standards at Datalogic’s labs, which will be adapted according to the methodologies offered by the COVR project and in collaboration with the STIIMA-CNR in Milan. This will allow to develop a new protocol to test and validate these devices, by interpreting the European standards: a significant step for all the actors involved in the field of collaborative robotics.

CRIT will lead the communication and dissemination of results that will be achieved in the project, by promoting them through targeted communications and the organisation of working groups and webinars, involving also ROSSINI and COVR partner organisations.

SCaVa is financed within the COVR Awards, a call promoted by the COVR project and financed by the Horizon 2020 programme, coordinated by the Danish Technology Institute with the participation of STIIMA-CNR. COVR deals with collaborative robots (cobot) safety in the industrial environment and it aims at developing tools and methodologies to test / measure / validate cobots in compliance with the existing safety standards.