Fast Accessibility Evaluation of the Main-Belt Asteroids Manned Exploration Mission Based on a Learning Method
Yuehe Zhu, Ya-Zhong Luo, Wen Yao · 2018
Accessibility evaluation is the primary step for the selection of the visiting target before the implementation of the main-belt asteroids manned exploration mission. Optimal transfer velocity increments from the earth to the asteroids and back to the earth must be obtained for the accessibility evaluation and analysis. Optimizing them one by one for all the candidate asteroids is extremely inefficient because of the great time consuming caused by the optimization process. In this paper, a learning-based method is applied to overcome this issue. Some optimal solutions are first produced as the training samples and the estimation model is trained to quickly obtain the optimal velocity increments of all the candidate asteroids. The experimental result shows the superiority of the learning-based method for solving this problem. No more than 1/50 simulation time is enough compared with the optimization-based method with an acceptable average relative error of 1.2%.