_Our research and development projects

The project is focused on performing industrial research leading to the creation of new technologies allowing utilization of sensor-equipped mobile devices for building a 3D mesh of the environment and interpretation of object geometry in near-real-time for the purpose of rapid development of worlds for Augmented (AR), Mixed (MR) and Virtual Reality (VR) games based on real-world environments. Creation of new heuristic methods ensuring a high level of accuracy of object recognition in a 3D space, including utilizing multiple area scanning devices simultaneously, is vital in order to achieve the aforementioned goals. Usage of Artificial Neuron Networks for object recognition based on a 3D mesh will be validated through the course of the research. Existing 2D image recognition algorithms will not be of direct use in these activities, but will be utilized as the starting point. Optimization of performance of the technology will be a significant issue – thus heuristics instead of precise algorithms, which allows for cooperation between multiple users immersed in the same virtual environment. The influence of given elements (algorithms, number of scanning devices, connection throughput) will be evaluated for their influence on accuracy and effectiveness of object recognition, providing insight as to optimal methods combining satisfactory recognition with dynamic collaboration between multiple users in near-realtime.

Synchronization of heuristic algorithms with the ability to dynamically and simultaneously model the environment by multiple devices, including a 3D developmnet environment in AR/MR/VR as well as desktops, will be one of key topics.

The project is focused on performing industrial research leading to the creation of new technologies allowing utilization of sensor-equipped mobile devices for building a 3D mesh of the environment and interpretation of object geometry in near-real-time for the purpose of rapid development of worlds for Augmented (AR), Mixed (MR) and Virtual Reality (VR) games based on real-world environments. Creation of new heuristic methods ensuring a high level of accuracy of object recognition in a 3D space, including utilizing multiple area scanning devices simultaneously, is vital in order to achieve the aforementioned goals. Usage of Artificial Neuron Networks for object recognition based on a 3D mesh will be validated through the course of the research. Existing 2D image recognition algorithms will not be of direct use in these activities, but will be utilized as the starting point. Optimization of performance of the technology will be a significant issue – thus heuristics instead of precise algorithms, which allows for cooperation between multiple users immersed in the same virtual environment. The influence of given elements (algorithms, number of scanning devices, connection throughput) will be evaluated for their influence on accuracy and effectiveness of object recognition, providing insight as to optimal methods combining satisfactory recognition with dynamic collaboration between multiple users in near-realtime.

Synchronization of heuristic algorithms with the ability to dynamically and simultaneously model the environment by multiple devices, including a 3D developmnet environment in AR/MR/VR as well as desktops, will be one of key topics.

INEDIT creates an open innovation European DIT ecosystem for sustainable furniture co-creation. It channels the
creativity of consumers, shapes it through designers’ professional skills, and makes it viable by leveraging on the
expertise of production specialists in order to deliver sustainable, smart and personalized new products in a shorter
time to market. INEDIT intends to demonstrate the capacity to turn the well-known ‘Do It Yourself’ (DIY) approach
applied by individuals within FabLabs into a professional approach named ‘Do It Together’ (DIT). The DIT approach will
be applied by customers and professional producers, especially SMEs, for conveying higher customer satisfaction through
customer-driven production. DIT is a novel approach capitalizing on the knowledge, creativity and ideas of design and
engineering conceptualized by interdisciplinary stakeholders and sometimes even new actors. It is powered by existing
European innovation ecosystems shaping new products across EU countries. INEDIT demonstrates the approach through four
cross use cases with high societal impact: sustainable wood panels manufacturing and 3D-printing of wood, 3D printing of
recycled plastic and Smartification. Sustainability and consideration of individual preferences, especially of women and
men, will be our guiding thread. INEDIT address societal challenges such as contribution to reduce the amount of
produced CO2 in focusing on European-wide production, creation and maintenance of EU-wide job opportunities. This will
lead to new business opportunities supported by business model innovation.  Moreover, these innovative networked local
manufacturing competences and production facilities across the EU will solve ethical concerns within the manufacturing
network. INEDIT intends to demonstrate, through its twin – digital and physical – platform, the potential innovation
around social manufacturing within the circular economy in designing global while producing local.

Project website

COVID-19 has drastically changed the existing rules on cooperation in the manufacturing, service and utilities sectors. Hands-on support, frequent delegations and stable workforce must give way to social distancing, flight restrictions and changes in employment. Collaboration, training, supervision and support for “first-line” workers require solutions that enable remote collaboration, immediate upskilling, and independence in accessing the information. These needs are addressed by augmented reality (AR) and communication technologies, democratizing access to knowledge, transferring it at a distance, and collaborative problem solving. However, they are subject to limitations in the context of their professional and industrial applications:

• Lack of support for industrial wearable devices – current solutions are convenient for casual use on smartphones, but not when working with machines, infrastructure, service provision and tasks requiring having both hands free
• Dependency on ArCore and ArKit libraries – mobile device like the class of Samsung Galaxy S7, iPhone 7 and better is hard to find on employees’ equipment, which limits the adoption of AR in professional conditions
• Small scale of the mapped space – AR content is applied to a image markers, floor planes or single objects being detected – it is impossible to map a space larger than several m2, understanding the location of the employee at the scale of the entire factory / building and ones interaction with the real world
• Short battery life – AR calculations are computationally expensive when it comes to battery consumption – real use of AR is limited to approx. 2-3h

We offer an innovative AR solution for remote cooperation, which will map spaces above 1000 m2, will work on devices that are saturated and incompatible with the libraries ArCore (from Google) and ArKit (from Apple) and thanks to the use of 5G and cloud for AR calculations, it will extend the working time with AR one battery charge.