The Virtual Mission Control Room (VMCR) is an attempt to free operators from the need to travel
to and stay within the same physical Mission Control Room (MCR).

Background and justification:

The work carried out reports on a new machine learning-based software prototype for designing and optimising phased array antennas. The prototype can rapidly and accurately compute excitation coefficients for large-scale antenna arrays across diverse configurations and far-field requirements. The prototype relies on tailored neural networks integrating structural physics and domain knowledge using an encoder-decoder structure.

The SPOTTED project addresses the critical issue of marine debris, particularly plastic pollution, by enhancing detection and monitoring capabilities. Utilizing advanced spatio-temporal fusion (STF) techniques and Artificial Intelligence (AI) with high-resolution satellite imagery from Sentinel-2 (S2) and PlanetScope (PS), the project aims to refine S2 data and develop AI algorithms for identifying landfills and floating debris.

In this study we explore the potential of Large Language Models (LLMs) to interact with Earth Observation (EO) data with some promising first results. We source a first testing set for the BIG Bench framework. With 20+ subtasks, we aim for a large variety of questions which are currently beyond the capabilities of LLM and other models. Further, we implement a methodology to test proprietary state of the art models where token distribution may not be available.

The “16U4SBSP” mission concept is a fundamental technology demonstration step for the realization of kW-/MW-/GW-scale Space-Based Solar Power (SBSP) based on flight formation, a distributed or aggregated swarm of small satellites contrary to conventional concepts of monolithic giant SBSP satellites. In this mission, a swarm of 16U CubeSats collaboratively supply wireless power via Radio-Frequency waves to end-users in different locations on the ground, for instance to provide backup power for emergency situations, and also for space-to-space commercial use-cases.

RaCERS is a swarm of eight small satellites that will fly in close formation to exploit the enormous power of cooperating radars to boost the quantity and resolution of environmental observations from space. This will transform the science of Earth environmental monitoring and forecasting applied to such vital concerns as severe weather, natural hazards, snow/ice cover, soil moisture, vegetation canopy, surface winds, ocean circulation and much more.

The outer space is commonly perceived as one of the most hazardous environments for human beings. Nowadays, the training of astronauts relies on a wide range of courses and facilities to prepare them for any situation they may encounter in space. The combination of these training technologies has successfully prepared multiple generations of astronauts. However, these assets lack flexibility to customise the training process, and are limited in scalability to accommodate an increasing number of trainees.