Adrian Tejeda Canellada
Missions for Removal of Orbital Debris.
Rel. Lorenzo Casalino. Politecnico di Torino, Master of science program in Aerospace Engineering, 2019
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Abstract
During the last 40 years, the number of artificial objects in orbit increased quite steadily, leading to a big problem to be dealt at present and in near future. Most of these objects correspond to space debris in LEO which represent a latent threat to all the missions performed in such a region. Current studies suggest that to mitigate this problem as effective as possible, active debris removal (ADR) must be carried out in the following years. In this line, this strategy of debris removal needs to be done in the most efficient way, needing deep analysis of each mission. This thesis analyses the validity and versatility of an algorithm capable of finding optimal solutions for the manoeuvres involved in the active debris removal missions.
Due to the great number of possibilities that the mission could have, the algorithm has been developed as a genetic algorithm
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