Enhancing autonomy for close-proximity operations: the MSCA-funded project CASTOR

The space industry is rapidly growing with missions planned for the future, both in commercial ventures and scientific exploration. As demand for space-based services and deep space exploration increases, autonomous deep-space probes are needed. Reliance on ground-based personnel for spacecraft operations poses challenges in terms of cost, scalability, and communication delays. Autonomous probes with guidance and control capabilities would simplify operations, reduce costs, and facilitate space exploration. However, current spacecraft autonomy is limited, and on-board trajectory optimization algorithms face computational constraints. The CASTOR (Challenging Autonomous Spacecraft through Trajectory Optimization with Robustness) project, funded under Marie Skłodowska-Curie Actions, aims to develop a framework for robust autonomous guidance and control for spacecraft operating near minor bodies, considering on-board power and computational limitations. It includes an autonomous guidance algorithm with sequential convex programming and polynomial chaos expansion for uncertainty propagation. The algorithm will be implemented on spacecraft-compatible hardware and tested in RAFFAELLO, a laboratory environment simulating conditions near a minor body. The successful implementation of CASTOR will have significant implications for space operations, enabling cost reduction, enhancing scientific exploration, and democratizing space for new operators.