Mobile Edge Computing for 5G DROne Systems

MICRO5G focuses on industrial research on URRLC and MEC with the objective of acquiring new skills and knowledge related to the deployment and support of drone services in 5G.mURRLC will allow drone service providers to extend the flight time by reliably moving complicated processing tasks to the mobile edge. In parallel, MEC will support crowdsourcing data from multiple drones, which can be consolidated and utilized as a traffic management tool. The synergy out of combing these capabilities shall not only enable innovative services such as safe flight beyond visual line of sight (BVLOS) and dynamic guidance/geofencing, but also promote an interactive, rather than independent, integration of different 5G technologies.

Project Details


Modular Perception and Autonomy for Light-weight On-Orbit Robotic Manipulators

Advanced robotic capabilities and operational autonomy are crucial enabling technologies for the advent of industrialization in space. A key advantage of using robots in space is their capability of operating continuously in harsh environments. This enables applications that exceed the reach of possible human intervention. Redwire/Made in Space Europe is developing state-of-the-art light-weight low-cost robotic arms for space, to enable a commercial revolution in-orbit, on-surface, and beyond. To realize ambitious technology architectures for sustainable utilization, commercialization, and exploration of space, advanced in-space robotic capabilities are required. Operational and algorithmic autonomy is a core challenge in that direction. Together, SpaceR and Redwire/Made In Space Europe are working on frameworks, methods and algorithms for incrementally developing autonomy with focus on advanced robot vision and perception.

Project Details


High-fidELity tEsting enviroNment for Active Space Debris Removal

Space debris is caused by millions of non-functional, human-made objects left in space that become a hazard for current and future space missions. Yet, no Active Space Debris Removal (ASDR) systems currently exist. Many methods have been proposed, but most of them are still in the technology development stages. Thus, on-ground experimental facilities for the test, verification and validation of ASDR will be critical for pushing the technology to the operational stage. SpaceR and Spacety target to explore, within the HELEN project, the potential of the 2D micro-gravity facility (Zero-G lab) for validating FlexeS, a small Flexible Capture System for debris removal. Advanced computational methods will be developed combining HIL and SIL to recreate high-fidelity in orbit scenarios. The integration of virtual and physical systems will enable close-to real testing, speeding up the transition between the development and deployment stages of ASDR systems.

Project Details


Zero-G Lab - Multi-Purpose Zero Gravity Lab facility

Zero-G Lab is designed to allow students and researchers to test the movement of in-orbit robotics, satellites and other spacecraft in a micro-gravity environment – similar in concept to an air hockey platform. On Earth, we take gravity for granted, but moving in its absence presents a number of challenges for in-orbit operations. For instance, a small push between two orbiting systems could make one or both to tumble and get out of control. Seeing how spacecraft and orbital robotics can be controlled or perform with decoupled systems in this environment provides students the unique chance of understanding and forecasting their behaviour in space

Project Details


Vision-Based Navigation system (VBN) for autonomous satellite navigation in space

The goal of this project is to develop a fully functioning VBN system prototype at technology readiness level (TRL 7) that would be representative of the future commercial off-the-shelf product for the space industry. This means the system should be completed and tested in a laboratory environment that is representative of the operational environment in orbit. The result of this project - the VBN prototype will be a standalone hardware system running custom navigation software algorithms, including AI and computer vision, to perform complex autonomous relative navigation maneuvers necessary to rendezvous and/or dock with an uncooperative target that does not have any active or passive aids for such maneuvers. In addition to that, skills and processes for product development and testing will be created during this project. This will be achieved by building necessary partnerships with academia and the industry for gaining access to state-of-the-art research, current technology and technological processes as well as the necessary testing facilities for validation. Algorithms will be coded and tested in the simulation environment using software-in-the-loop (SITL) approach. Once the algorithm performance matches or exceeds the performance in the requirements definition document, the algorithms will then be ported to a chosen embedded system and tested for efficiency using hardware-in-the-loop (HITL) simulations.

Project Details


Reinforcement Learning based GNC for a high-fideLity emUlator module of eXtraterrestrial body LANDER

Descent and landing (D&L) are arguably among the most critical phases for the success of upcoming space exploratory missions. They can face difficult challenges due to extremely uncertain and variable physical environments of the target planet or asteroid bodies. These challenges require fully autonomous Guidance, Navigation and Control (GNC) algorithms to achieve mission success. Reinforcement Learning (RL) is a promising technique that has the advantage over traditional engineering GNC systems to adapt to unknown situations and circumstances that are hard to account for manually. The integration of RL with the GNC subsystem in a realistic infrastructure (such as LUXLANDER) could be a game-changer for upcoming space-exploration missions. Indeed, using RL-based algorithms in the real world it is crucial to develop a suit of the trained control policies for the given problem in a highly accurate simulation environment and to demonstrate their robustness with a realistic Verification& Validation (V&V) test-bench.

Project Details


FinTech/RegTech in Space for Trustful Autonomous Robotic Interaction

FiReSpARX’ objective is to use distributed ledger technologies as well as intelligent agent technologies to develop space robots that follow a given governance (RegTech) and make autonomous economic decisions (FinTech) to jointly create collaborative MRS. This form of dynamic collaboration between space robots could lower market barriers in the space sector and thus transform the whole industry. This topic hence perfectly fits Luxembourg’s national research priorities “Autonomous and intelligent systems and robotics for earth and space“ as well as “Fintech/RegTech and transformative applications of distributed ledger technologies“.

Project Details


CollAborative Exploration and Structural Analysis using heterogenous multi-Robot system in eXtreme enviRonments

Nowadays, we are using more and more robots to replace the tedious, difficult, or even impossible tasks to be done by humans. This is especially true in the undergrounds, where the walls can be damaged by water, vibration, seismic waves or any aggression through time. The CAESAR-XR project allows, through all its dangers, to send entire fleets of robots to map, explore and discover points of interest in long-abandoned mines and caves. For such systems to work autonomously, they must 'see' and 'understand' the environment through different components. In the CAESAR-XR project, robots of all types can be used. Some sensors allow the robot to make a 3D map, while others use colour cameras or calculate the distance between the robot and the various obstacles in front of the robot. These fleets of intelligent robots will not always be connected with a human pilot, which is why they must communicate and make decisions by themselves when exploring the underground. CAESAR-XR aims to develop a simulated environment based on a randomised generation of underground environments to facilitate the validation and verification of the developed algorithms before accessing underground environments. Experts can then use the data collected by the robots to help identify potential weaknesses in the internal structure of the explored areas. The use of this information can be used in the mining industry as well as in space with potential explorations of lunar lava tubes that could serve as protection for a base against radiation and extreme temperatures.

Project Details