LMO is a young and dynamic company tackling the challenges posed by the growing space industry and in-space economy. With operations in Luxembourg and UK LMO provides Innovative Solutions for Small Satellite & In-Orbit Servicing Missions. LMO’s core focus lies in the fields of Space Situational Awareness & Propulsion.
LUXEMBOURG (Luxembourg Space Agency PR) — In the last 2 years, LMO and the University of Luxembourg’s Interdisciplinary Centre for Security, Reliability and Trust (SnT) through its Computer Vision, Imaging and Machine Intelligence Research Group (CVI2), have been working together to bring computer vision-based autonomous technologies from ground up to space.
In the last decade, the use of space has grown exponentially, influencing our daily lives in communication, weather monitoring, localisation, and much more. To do this, hundreds of satellites were launched far from the human eye. However, once in space, satellites operate on their own – vulnerable and oblivious to the environment around them.
With this increased footprint in space, so has the amount of trash – known as space debris – and other threats towards satellites. With autonomous technology similar to that used in self-driving cars, LMO is providing the tools for satellites to look around them in space and make autonomous decisions based on this information, without the need for ground segment intervention; tools that are becoming ever more critical as space becomes more congested. At the core of these autonomous tasks are computer vision and artificial intelligence (AI) algorithms.
For its first product, LMO is combining space sensors with novel computer vision techniques into a dedicated single payload (SSA Payload), which can process images in space and provide insights of the surrounding area of a satellite, otherwise known as In-Situ Space Situational Awareness (SSA). The SSA payload will enable satellites to autonomously survey Space Resident Objects (SRO) around them, offering key information such as: “identification, classification, feature recognition and pose estimation, critical to enable safe navigation in space.
With the SSA Payload mounted on-board civil and defence satellites, these will be able to:
- Automate collision avoidance manoeuvres
- Offer autonomous surveillance
- Autonomously inspect other objects in space
- Capture and remove space junk
- Dock with other satellites and offer in-orbit services, such as repair and refuelling
- Collaborate with other SROs for in-orbit assembly and manufacturing
The increased autonomy and collaboration of satellites in space will enable the exponential growth of the in-space economy, enabling such aspirations as large space structures assemblies, deep-space logistics and planetary mining
To achieve its goal and build from a solid foundation in computer vision expertise, LMO partnered in 2020 with the Computer Vision, Imaging and Machine Intelligence Research Group (CVI2) at SnT, headed by Professor Djamila Aouada, a department with more than 12 years of expertise in the field of computer vision and AI.
The partnership has led to key advances in using computer vision for in-space autonomy, including testing of algorithms in dedicated facilities to simulate rendezvous scenarios and relative navigation, as well as testing of algorithms for image identification, classification and pose estimation in software embedded in space electronics architectures.
On the back of this success, LMO, together with SnT, signed a large development contract with ESA for the Development of In-Orbit servicing SSA (DIOSSA) applications. DIOSSA will allow the consortium to validate the performance of its SSA Payload in a dedicated in-orbit servicing facility developed at SnT. The programme is funded by the Luxembourg Government through an ESA Contract in the Luxembourg National Space Programme, LuxIMPULSE.