Trajectory optimization of a satellite for multiple active space debris removal based on a method for the traveling serviceman problem

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Space debris removal is currently a critical issue for space development. It has been reported that five pieces of debris should be removed each year to avoid further increasing the amount of debris in orbit. To remove multiple pieces of debris, one idea is to deliver multiple satellites that can each remove one target debris from orbit. The benefit of this approach is that target debris can be removed without orbit transition, so the satellite can be developed by using simple satellite mechanics. However, multiple satellites need to be launched. Another idea is to use one satellite to remove multiple pieces of space debris. This approach can reduce the launch cost and remove space debris efficiently. However, the satellite must change its orbit after each debris removal, and a technique for optimizing the orbit transition is required. In this study, we focused on the latter strategy and developed a satellite trajectory optimization method for efficient space debris removal. We considered the similarity between the problem of multiple space debris removal and the traveling serviceman problem (TSP) and applied the TSP solution of an evolutionary algorithm (EA) to the former. To improve the efficiency of the multiple debris removal, we maximized the total radar cross-section (RCS), which indicates the amount of space debris, and minimized the total thrust of the satellite. We extended the TSP solution method to multiple objectives by coupling it with a satellite trajectory simulation. To evaluate the developed method, a set of 100 pieces of space debris was selected from a database. The results indicated a tradeoff between the total RCS and total thrust.