Space Based Solar Power concepts promise the generation of large amounts of renewable power by launching vast Solar Power Satellites (SPS) into space and beaming the power back to rectennas on Earth. Due to diffraction physics, large scale arrays delivering 2GW of power to the ground will be on the order of a kilometre in length and have masses between 2,000 and 10,000 tonnes. As of January 2020, the amount of debris orbiting the Earth exceeded 8,000 metric tonnes. A decommissioned SPS would therefore have the potential to create a step change in the mass of debris humanity has created.

Space debris is mainly constituted by small items which cannot be de-orbited by using specific satellites launched from the Earth due to costs and difficulty in miniaturizing robotic arms or other rigid actuation systems. In a long-period vision, small cleaning satellites, with a size comparable with the debris to remove, can be manufactured in Space. Traditional robotic systems would be extremely expensive and some also would have problems in grabbing objects with undefined shape.

The goal of this study was to develop a design for a lunar habitat in the close vicinity of one of the lunar poles and to demonstrate the feasibility of the suggested design in view of the available resources. The habitat should operate self-sufficiently in the long term by producing and recycling its own oxygen and food inside large greenhouses and almost exclusively by using solar irradiation power. The proposed  concept features a combination of:

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.

The OPS-SAT MBSE activity had the 3 main objectives:

Electrical, Electronic and Electro-mechanical (EEE) components play an essential role in the functional performance, quality, life cycle and costs of space systems. EEE components are fundamental building blocks of any spacecraft and major drivers in determining their performances. Guaranteeing access to EEE components able to provide the necessary performances to comply with the requirements of future satellite missions is of paramount importance to maintain a successful and autonomous satellite manufacturing capabilities.

The focus of study is to build near-IR capability onto Si CCDs for Time-Delay-Integration (TDI) applications, with the main requirement being charge domain summation, which allows the lowest noise performance on these types of devices. Currently there is no product that exists to do this. Si CCDs are a well-established technology which, whilst being an “old” technology, are still world leading in certain applications up to a wavelength of ~1μm.

The main objective of the project is the reverse engineering of the OPS-SAT system, creating a model of the existing system design. The model aims to be built in a way that it is most useful for OPS-SAT engineers to understand and discuss the existing design and use this as a basis for further development of the OPS-SAT system.

Nowadays, human Moon exploration, and the consequent desire to establish a permanent settlement on its surface, represents one of the most fascinating challenge to face. The permanent presence of a human outpost very far from Earth raises the problem of the huge amount of payload required for the settlement, as well as the need of rapid and in-time supply of material and spare parts useful for all the activities carried out in-situ, including the realization of medicals tools and patient-specific back-up implants.

Quantum algorithms process information stored in qubits, the basic memory unit of quantum processors, and quantum operations (called gates) are the building blocks of quantum algorithms. In order to be run on quantum computing hardware, quantum algorithms must be compiled into a set of elementary machine instructions (i.e., quantum gates).