DATA FUSION FOR NON GNSS LOCALIZATION

5G (ENCQOR) Technology Development Challenge for SMEs

DATA FUSION FOR NON GNSS LOCALIZATION

Challenge Launch Date:

January 24, 2020

Challenge Deadline:

February 9, 2020 (expired)

Challenge Statement:

In different verticals, Thales is providing critical solutions for autonomous or semi-autonomous systems. For instance, in the Transportation domain, autonomous trains and enhanced Artificial Intelligence (AI) capabilities are coming faster than we think.

In this challenge, we are focusing on semi-autonomous or autonomous vehicles, in a position where GNSS localization is not available. Imagine dense urban environments, underground railwails, or « hostile » or « controlled » environments where GNSS signal is not available or is jammed.

We are looking for solutions in AI that will be able to contribute – in a trustable manner – to the overall situational awareness of the system, by providing an accurate and trustable position.

Project Partner:

Thales Canada Inc.

Timeline:

6 months

Available Funding:

100 000$ CAD

Applicant Type:

SME with less 500 employees registered in Quebec.

Location:

At SME location in Quebec with 5G testing in one of ENCQOR 5G Hubs in MTL or QC.

Project Details:

We are looking for a scalable, trustable and resilient solution to revolutionize the localisation of autonomous or semi-autonomous vehicles in environment where GNSS localisation is not available. The solution is expected to make the best of 5G and Artificial Intelligence technologies to increase the reliability of the system.

Project Goals/Outcomes:

• Establish a long partnership between Thales and a future champion of 5G.
• Deliver a functional proof of concept solution addressing the challenge and its associated documentation.

Applicant Capabilities:

• Experience in positioning, data fusion and computer-vision algorithms.
• Good understanding of trustability and certification of algorithms.
• Experience in performance comparative analysis of algorithms under nominal or degraded mode (speed, consumption, etc.).
• Experience in developing data applications executing on the Edge.
• Previous experience developing and deploying application on public cloud Azure.

Additional Information:

• Interested SMEs must submit a (max) 10 pages document (in .pdf) with the Statement of interest describing its expertise and capabilities
• Selected SMEs will be invited for a live demo/presentation with the project owners
• It is highly recommended that interested SMEs participate to one of the free 5G trainings offered by ENCQOR (https://quebec.encqor.ca/formations/)