Identifying near-earth asteroid targets for human exploration using particle swarm optimization

Near-Earth Asteroids;Particle Swarm Optimization

Stanley, Aishwarya ; Conway ; Bruce A.

关键词: Near-Earth Asteroids;    Particle Swarm Optimization;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/44435/Aishwarya_Stanley.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The goal of this thesis is to identify potential Near-Earth Asteroids (NEAs) that are viable candidates for human exploration. The computational method incorporated to help identify these targets is the particle swarm optimization (PSO) technique, a metaheuristic swarming algorithm. The optimizer that was developed minimizes the total mission delta-V, given a particular epoch date, whilst optimizing four time parameters, namely, the ideal time to launch from Earth, the outbound flight time from Earth to an asteroid, the stay time at the asteroid and the inbound flight time from the asteroid to Earth. Studies have been done to identify NEAs suitable for human exploration. However, such studies involved the computation of millions of combinations of launch dates, flight times and wait times at an asteroid in order to determine the specific combination that yields the lowest cost, i.e. the lowest delta-V value. The use of PSO eliminates the need to take such a ‘brute-force’ approach and offers a less-cumbersome way of solving the problem and is computationally inexpensive. The optimizer was applied to NEAs representing all three asteroid belts and identified 365 day (or less) round trip missions which can be accomplished with modest and reasonable delta-V values.