Research Program
Bilateral Contracts and Grants with Industry
Research Program
Bilateral Contracts and Grants with Industry

Section: Partnerships and Cooperations

National Initiatives

eTAC: Tangible and Augmented Interfaces for Collaborative Learning:

  • Funding: EFRAN

  • Duration: 2017-2021

  • Coordinator: Université de Lorraine

  • Local coordinator: Martin Hachet

  • Partners: Université de Lorraine, Inria, ESPE, Canopé, OpenEdge,

  • the e-TAC project proposes to investigate the potential of technologies ”beyond the mouse” in order to promote collaborative learning in a school context. In particular, we will explore augmented reality and tangible interfaces, which supports active learning and favors social interaction.

  • website: http://e-tac.univ-lorraine.fr/index


ANR Project EMBER:

  • Duration: 2020-2023

  • Partners: Inria/AVIZ, Sorbonne Université

  • Coordinator: Pierre Dragicevic (Inria Saclay)

  • Local coordinator: Martin Hachet

  • The goal of the project will be to study how embedding data into the physical world can help people get insights into their own data. While the vast majority of data analysis and visualization takes place on desktop computers located far from the objects or locations the data refers to, in situated and embedded data visualizations, the data is directly visualized near the physical space, object, or person it refers to.

  • website: https://ember.inria.fr

ANR Project REBEL:

  • Duration: 2016-2019

  • Partners: Potioc, Handicap Activity Cognition Health lab (Univ. Bordeaux)

  • Coordinator: Fabien Lotte

  • Brain-Computer Interfaces (BCI) are communication systems that enable their users to send commands to computers through brain activity only. While BCI are very promising for assistive technologies or human-computer interaction (HCI), they are barely used outside laboratories, due to a poor reliability. Designing a BCI requires 1) its user to learn to produce distinct brain activity patterns and 2) the machine to recognize these patterns using signal processing. Most research efforts focused on signal processing. However, BCI user training is as essential but is only scarcely studied and based on heuristics that do not satisfy human learning principles. Thus, currently poor BCI reliability is probably due to suboptimal user training. Thus, we propose to create a new generation of BCI that apply human learning principles in their design to ensure the users can learn high quality control skills, hence making BCI reliable. This could change HCI as BCI have promised but failed to do so far.

  • website: https://team.inria.fr/potioc/collaborative-projects/rebel/

Inria Project Lab AVATAR:

  • Duration: 2018-2022

  • Partners: Inria project-teams: GraphDeco, Hybrid, Loki, MimeTIC, Morpheo

  • Coordinator: Ludovic Hoyet (Inria Rennes)

  • Local coordinator: Martin Hachet

  • This project aims at designing avatars (i.e., the user’s representation in virtual environments) that are better embodied, more interactive and more social, through improving all the pipeline related to avatars, from acquisition and simulation, to designing novel interaction paradigms and multi-sensory feedback.

  • website: https://avatar.inria.fr