txt madeira


Machine And Deep learning in Industrial Environment with use of Augmented Reality

Financed by:

ministerio de ciencia innovacion y universidades

Funder Program: RETOS COLABORACION 2017

File number: RTC-2017-6418-6


  • Ceit

  • CT Ingenieros


The MADEIRA project represents an important step regarding the integration of new technologies in industrial processes. Its main objective is to develop a flexible software platform using machine learning technology for real-time control of an industrial assembly process.

This ambitious project has been proposed through overcoming three technological challenges that are:

  • Automated systems must understand the environment.

  • The process must have the ability to reconfigure based on its environment;

  • System learning has to be integrated at a high level in the global control of the industrial process.

These developments will allow the definition of an assembly methodology that is totally different from what exists, based on advanced digital tools and technologies that will open up a number of possibilities such as obtaining real-time and historical information on the variables that influence assembly processes or increasing the efficiency of process, increasing the competitiveness of companies.

Ceit's role in the project

Ceit's role in this project is the technological development of the product as an expert in VR, AR and Machine / Deep Learning technologies. For this, apart from development jobs, the equipment mentioned below and that Ceit makes available to the project will be used:

  • 3D VR headset and its controls (HTC Vice). A VR simulator is available, the result of a previous project, with which you can visualize and simulate complex industrial processes. This simulator uses the HTC helmet to achieve greater immersion for the user. This simulator will be used to simulate and test the ML algorithms designed to optimize this process.

  • Perception Neuron motion capture system. One parameter that may be interesting to optimize is the ergonomics of the process. To study it, use will be made of the mocap system that CEIT has to capture the movements of the operator and analyze its ergonomics.

  • Microsoft Hololens glasses for RA visualization