Machine and deep learning in industrial environments with the 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 in integrating 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 aims to overcome three technological challenges:

  • Automated systems must understand the environment.

  • The process must have the ability to reconfigure as a function of its environment.

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

These developments will allow a totally new assembly methodology to be defined based on advanced digital tools and technologies that will open up a number of possibilities such as obtaining real-time and historical information for the variables that influence assembly processes or increase the efficiency of process, thereby 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. In addition to having the necessary development space, Ceit also has the following equipment at its disposal:

  • 3D VR headset and controls (HTC Vice). A VR simulator is available (the result of a previous project) and which can be used to visualize and simulate complex industrial processes. This simulator uses an HTC helmet to achieve greater immersion for the user. This simulator will be used to simulate and test the machine learning 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 this possibility, Ceit will use its mocap system to capture the movements of the operator and analyze the ergonomics.

  • Microsoft Hololens glasses for RA visualization.