Solar for Ice to Thrust

Overview

The growing number of satellite launches, the emergence of in-orbit servicing (IOS) and the need for active debris removal (ADR) demand reliable, affordable and scalable solutions for in-space mobility.

Ice2Thrust (S4I2T) develops an innovative solar electric water propulsion system and builds around it a self-sustaining mobility infrastructure in space. Water is green, cheap, easy to store and transfer, and abundant on other celestial bodies, which makes it the core of the three technology pillars of the project:

• Solar-electric water electrolysis propulsion — an electrolyser decomposes water in flight into hydrogen and oxygen that feed hot-gas, cold-gas and electric thrusters from a common propellant supply.
• Autonomous proximity operations, docking and propellant refilling — enabling reliable, large-scale in-orbit servicing, debris removal and on-orbit assembly.
• In-space water extraction and utilisation — extracting water from icy regolith to refill spacecraft, closing the loop from ice to thrust.

Research Activities at SpaceR

Autonomous Proximity Technologies

SpaceR leads the development of learning-based guidance and control for close-proximity operations, docking and propellant transfer of small spacecraft. Reinforcement learning (RL) policies are trained to navigate a servicer to the docking point while satisfying thrust, attitude and safety constraints, such as approach corridors and range-dependent closing-velocity limits, and to keep the stack controlled while transferred propellant shifts its centre of mass and inertia.

RL Training Environment for Docking and Refuelling

A massively parallel, GPU-accelerated six-degree-of-freedom simulation environment with orbital dynamics is developed to train and benchmark classical, model-free and model-based RL controllers for docking and refuelling scenarios across a range of spacecraft platforms. Additionally, a 6-DoF simulation environment for sim-to-real transfer of policies on the platforms and robots in Zero-G laboratory is also utilized.

Docking and Refilling Hardware-in-the-Loop Demonstration

Trained policies will be transferred zero-shot to the floating platforms of SpaceR's Zero-G Lab, with a goal of hardware-in-the-loop demonstration of autonomous in-orbit servicing operations.

Consortium

Technical University of Munich (TUM) Project coordination, water extraction and water electrolysis propulsion.

University of Luxembourg — SnT / SpaceR Autonomous proximity technologies, RL training environment, and docking and refilling hardware-in-the-loop demonstration.

EnduroSat Spacecraft technologies and CubeSat mission analysis.

TechTour Communication, dissemination, market analysis and commercialisation.

Publications

• A. Arora, R. Marsal i Castan, M. El-Hariry, and M. Olivares-Mendez. "SCoCaT: Success Conditioned Constrained Reinforcement Learning for Spacecraft Docking." Accepted at CoRL 2026. arXiv
• A. Arora, P. Lima, and M. Olivares-Mendez. "Massively GPU-Accelerated Reinforcement Learning with Constraints for Autonomous Spacecraft Docking and Fuel-Transfer Alignment." Presented at the ESA GNC & ICATT Conference 2026.