This application domain comprises 3 main areas:

• Space Weather services – monitoring space weather conditions
• Space Traffic Management services – tracking and detecting near earth objects to mitigate or reduce the hazards of a collision
• Space Intelligence services – tracking and surveillance of objects in the Earth’s orbit

Amending initially planned missions, in-orbit servicing covers areas such as:

• Orbit raising and positioning
• Relocation and positioning
• Station keeping
• Deorbiting
• Refuelling
• Delivery of units and in-orbit assembly
• (Close) Inspection, repair
• Active Debris Removal

We will address the following challenges in this domain:

• Reduce costs per launch/kg and improve lifecycle cost effectiveness
• Better system design choices
• Supporting own-controlled access to space for countries
• Short time-to-launch and availability on demand

Our focus will be on supporting the operations of uncrewed and crewed Scientific/Commercial Space Exploration, from LEO/Moon orbits to Moon surface services (e.g. rovers, landing/ascending vehicles, cis-lunar transport vehicles) and beyond.

To make humanity's presence in outer space sustainable, a very high degree of automation and autonomous systems are required. In-situ resource utilisation (ISRU) and space-based manufacturing and assembly will be fundamental technologies.

Unmanned flying objects bring new opportunities and new challenges. There will be drones for a broad variety of use cases – including search and rescue, delivery of critical goods, remote inspection and many more.

Millions of flying drones will create new traffic management needs. They require compliance with new regulations, as well as new ways of operating these autonomous flight systems as swarms.

Telespazio Germany has a heritage of providing high-performance, high-reliability software to the most demanding customers. It is our goal to keep and even improve upon our track record of reliability, while using far fewer resources in the process.

We will achieve this by leveraging new software technologies that have reliability at their core. Programming languages such as Elixir, Rust will enable us to deliver even better value to our customers.

Like many others, we see Artificial Intelligence and Machine Learning (AI/ML) as one of the key technologies of the 21st century. We will leverage our reliable software infrastructure and Explainable AI (xAI) techniques to increase the confidence in AI/ML models and make them adaptable to the domains of our customers.

These systems will take many different shapes and forms: From small surrogate models of physical systems to fully virtual agents and assistants.

Sensor fusion is important to ensure we are using the best information source at the moment, in order to complement and validate different inputs to make decisions accordingly, even if conditions are uncertain. To interact with the real world, we need to have a way to always "view it". Telespazio Germany will be using optical sensors and systems that use light, both visible and other wavelengths, as the input: RGB cameras, Infra-red, multispectral, hyperspectral, lasers (Lidars and ToF  - time-of-flight).

Artificial Intelligence and Machine Learning (AI/ML) is only one part of the bigger whole that is needed to enable truly autonomous systems. We will also work on a number of other related topics, such as:

• Sensor fusion
• Staying in contact with autonomous assets via satellite links
• Precise positioning via GNSS signals or optical navigation
• Management of autonomous assets

Building on Artificial Intelligence and Machine Learning (AI/ML) and autonomous systems, AI-powered Virtual Intelligent Agents will provide support with a “human touch”. Virtual Experts will augment our knowledge and guide us in our work, making learning curves much smaller and easier.

While a simulation is usually disconnected from real events during execution, a digital real-time twin allows us to connect real-time events from the physical asset, process or system to the existing simulation environment. As a result, engineers can perform tests, assessments and analysis using real-world conditions that will improve/adapt future execution based on the "real-time" data processing.