Trajectory optimisation with Ant Colony Optimisation algorithm for multiple debris removal missions

The intensification of space activity has led to a significant increase in orbital debris, posing a growing threat to the sustainability of orbital operations. With the expansion of satellite constellations, the phenomenon is set to worsen, making it essential to adopt Active Debris Removal (ADR) missions to mitigate collision risk and prevent the Kessler Syndrome, which could compromise entire orbital regions. The effectiveness of an ADR mission is closely related to the amount of debris removed in a single operation, a problem similar to the Travelling Salesman Problem (TSP). In this context, trajectory optimisation is addressed using an algorithm based on Ant Colony Optimisation (ACO), which emulates the stigmergy mechanisms observed in the cooperative behaviour of ants to identify optimal solutions to complex combinatorial problems.