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DEEPCUBE

The goal of the project was to develop a service as a product to simplify fitting DNN (Deep Learning Neural Networks) in on board HW to make better use of AI on space missions The role of the service is to support data processing engineers in reducing HW resources requirement of powerful DNN for image analysis to be executed onboard. 

France

GT27-048ED

Agenium Space
Artificial Intelligence for Terrain relative Navigation in Unknown Environment (ATENA)

Space missions benefit greatly by the capability of the on-board GNC system to adapt rapidly to unknown environment. Autonomous vision-based navigation is a particular technology under implementation in several ESA missions. One of the most interesting applications in that field is the proximity operations around a small asteroid, like those in HERA.
The goal of this activity was to develop a navigation algorithm with the capability to fly over an unknown terrain and achieve better navigation performances than current vision-based techniques based on unknown feature tracking.

Spain

20-D-O-TEC-01

GMV
Smart Resource Management based on Internet of Things to support Off-Earth Manufacturing of Lunar Infrastructures (SMARTIE)

SMARTIE (Smart Resource Management based on Internet of Things to support Off-Earth Manufacturing of Lunar Infrastructures) is an ESA study to assess the requirements, architecture, hardware and software needs and costs for implementation of an Internet of Manufacturing Things (IoMT) for a lunar human base and associated infrastructure. 

Austria

20-D-S-TEC-03-g

Liquifier Systems Group
Enhanced Surrounding Awareness and Navigation for Autonomous Vessels

Autonomous Surface Vessels (ASVs) are rapidly approaching market-readiness, with numerous partly-autonomous and teleoperated systems either under development or already performing operational demonstrations for applications such as bathymetric surveying (SEA-KIT Maxlimer, Deep BV), maintenance of offshore installations (Thales Halcyon), and commercial shipping (Yara Birkeland, Maersk VISTULA-Class).

UK

20-D-T-TEC-02-d

Deimos
Real-time optimal control of quadrocopters using deep representations of the optimal state feedback

A major challenge in the field of control is to achieve reliable, aggressive, high-speed control of autonomous vehicles. In space, this may involve spacecraft that need to land under harsh conditions, or even – in an extreme scenario – negotiating asteroid debris fields at high speeds. On Earth, the exemplar task that draws most attention currently is high-speed autonomous flight of drones. The application of optimal control on board limited platforms has been severely hindered by the large computational requirements of current state-of-the-art implementations.

The Netherlands

18-8510

TU DELFT

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