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A Comparative Study Of High-Level And Low-Level Implementations Of Deep Learning Models For Spacecraft

Mission Control deployed a low-level implementation of the OPS-SAT SmartCam model using a Field Programmable Gate Array (FPGA), comparing against a high-level CPU model using Tensorflow Lite. Experiments showed that the FPGA implementation reproduced the precision and accuracy of the high-level model, while running at a slower speed. Further optimizations of the FPGA are expected to close the gap in timing and unlock new methods for deploying deep learning on spacecraft.

Canada

21-D-S-OPS-02-e

Mission Control Space...
MoBaTe – Enabling Model-Based Testing and Automated Test Case Generation for Ground Segment Data Systems

The driver behind the MoBaTe activity was to propose ways to improve the current software development and validation lifecycle using MBSE techniques to shift some of the system validation activities to the early stages of development. The roadmap to achieve this included identifying strategies, required model properties, modelling tools and languages needed to move from a requirements-based approach to a model-based approach. All this considering existing and established workflows and tools currently used by the Agency.

Germany

21-D-T-OPS-01

Etamax Space GmbH
AI AT THE EDGE : DEEP CUBE SERVICE IOD/IOV

OPS-SAT mission is a key element for operational validation in flight (or IOD/IOV) of the DeepCube service of Deep Learning at the edge that our company is preparing with the support of the GSTP programme (GSTP Make, ESA-CNES) and the R&D performed in the CORTEX project (Permanent Open Call EOEP-4, ESA/Phi-Lab, https://esacortexproject.agenium-space.com). The goal of the proposed experiment is to execute on-board the inference of the simplified models defined in those projects.

France

21-D-S-OPS-02-i

Agenium Space
HOPAS (Hybrid online policy adaptations strategy) on OPS-SAT

While AI technologies have shown promise in various applications in the space industry, their adoption on spacecraft flight software has yet to happen in a significant manner. This is due to a number of factors, including the relatively low computing power available on board of traditional spacecrafts, the long development process required in the industry and the lack of opportunities for in-orbit demonstrations. Airbus teams have identified in ESA OPS-SAT a unique opportunity to quickly test promising algorithms in-orbit as it seeks to resolve the issues listed above.

United Kingdom

21-D-S-OPS-02-a

Airbus Defence &...
Beyond the Mission Paradigm: Federated Reconfigurable Infrastructure via Edge Devices in Space (FRIENDS)

Early space missions consisted of bespoke components communicating with facilities on Earth. Today this model has been updated with off-the-shelf components and reusable launch systems that lower mission cost into low-earth orbit. Extending this model to develop a sustainable off-earth economy requires bringing the concept of reconfigurable computing agents to deep space.

Canada

EISI_I-2022-00378

Mission Control Space...
Model Based Avionics

SAVOIR has produced a set of generic specification under the form of documents, based on some physical architecture of equipment that was state of the art at that time. The new functional model based approach is more based on functional chains and models. It is expected that modelling the SAVOIR avionics architecture and generic specification using the MBSE techniques, in particular Arcadia method and Capella tool, will allow to have an innovative standpoint on the SAVOIR standardisation.

France

20-D-T-TEC-05

Thales Alenia Space
Space Weather Impact on Arctic Navigation (SWAN)

The objective of the Space Weather impact on Arctic Navigation (SWAN) project has been to
develop and demonstrate new techniques, which are expected to improve on the current
state-of-the-art space weather forecasting techniques and products related to space weather
effects for Positioning, Navigation and Timing (PNT) systems in the Arctic, with particular
attention to the Greenland area.

Denmark

19-P-O-NAV-01-a

DTU Space
Artificial intelligence (AI) and natural language processing (NLP) to support space engineering activities

Model based approaches have proved to be efficient in supporting engineering activities, models replacing traditional document-based approaches. Nevertheless even in most advanced deployments, a lot of engineering artifacts are textual either because the return on investment of introducing models is too low on this particular case or because the information is more efficiently expressed in natural language even if consistency and correctness issues appears.

France

20-D-T-TEC-04-n

Thales Alenia Space
MBSE Deployment for EnVision Science Mission Study
  • Enforce the use of the physical engineering model that TAS-F already has by sub-system architects in order to have the model as a central source of truth
  • Produce an interactive representation of the model allowing its consultation without having to install dedicated modelling tools
  • Produce trend graphs on system budgets
  • Produce document generation capability to export graphs and tables to the system and subsystem budget reports
France

20-P-M-SCI-02

Thales Alenia Space
OMAR – On orbit manufactured spacecraft

The objective of this activity is to assess the system level and design impacts of optimising a satellite design for on-orbit manufacturing and assembly, as well as preparing it to be refurbished, reused or recycled on orbit afterwards, and to identify the technologies needed.

Italy

19-D-S-TEC-05

Thales Alenia Space

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