SIMLOG - A bit of CRIM all around the world


The ATREF project (Application of robotic technologies on forestry equipment) was launched by CRIM in the 1990's. This project was a collaboration between university partners and private companies, led by CRIM. Its conclusion was the elaboration of a simulator for operating heavy forestry machinery. 

This first software enabled students to learn and practice how to operate a single-grip harvester, with no risks or monetary losses in case of mistake. SIMLOG, the second independent company derived from CRIM's applied research to commercialize this simulator, has been working in building simulators for heavy machinery in four industrial fields all around the planet. 

Read the full story here (French version)

 

SIMLOG president Paul Freedman tells the story of the foundation of his company that specializes in creating products that help train equipment operators in industrial sectors such as forestry, mining, construction and handling.

Presented during the Journée Techno du CRIM  - Célébrons 30 ans de recherche appliquée et d'innovation - November 23, 2015

Presentation [video in French - duration 11:10]

 

Recent news

  • COVID-19 : Suivi de la situation
    25/03/2020

    Notre équipe maintient ses opérations à distance et est toujours là pour vous servir.

    +

Upcoming event

  • Assemblée générale des membres du CRIM - 18 juin 2020
    18 June 2020 0:00
    CRIM (405, avenue Ogilvy, bureau 101, Montréal)
    Les membres du CRIM sont convoqués à l'Assemblée générale annuelle qui se tiendra le 18 juin 2020. Ne manquez pas cette importante réunion et l'occasion de vous tenir au fait de plusieurs dossiers qui vous concernent.
    +
  • Prompt RT @Prompt_Innov: [ WEXPERT ?La Ville intelligente Nos intervenants : Philippe Beaudoin, co-fondateur d’ @element_ai Stéphane Barbier, di…
  • CEIM RT @CEIM_Qc: Bonne nouvelle! Le gala de l' @ADRIQ_RCTi aura bien lieu, que ce soit en présentiel ou en virtuel! Ne passez pas à côté de cet…

Recent Publications

  • An ensemble Based Approach for Generalized Detection of Spoofing Attacks to Automatic Speaker Recognizers

    +
  • Generalized End-to-End Detection of Spoofing Attacks to Automatic Speaker Recognizers

    +