Asteroid mining: ACT&Friends’ results for the GTOC12 problem  

作　　者：Dario Izzo Marcus Märtens Laurent Beauregard Max Bannach Giacomo Acciarini Emmanuel Blazquez Alexander Hadjiivanov Jai Grover Gernot Heißel Yuri Shimane Chit Hong Yam 

机构地区：[1]European Space Technology and Research Center,Noordwijk,2201 AZ,the Netherlands [2]European Space Operations Centre,Darmstadt,64293,Germany [3]Surrey Space Center,University of Surrey,Guildford,GU27XH,UK [4]School of Aerospace Engineering,Georgia Institute of Technology,Atlanta,Georgia,30332,USA [5]Mission Design and Operations Group,ispace inc.,Sumitomo Fudosan Hamacho Building 3F,3-42-3,Nihonbashi Hamacho,Chuo-ku,Tokyo,103-0007,Japan

出　　处：《Astrodynamics》2025年第1期19-40,共22页航天动力学(英文)

摘　　要：In 2023, the 12th edition of Global Trajectory Competition was organized around the problem referred to as “Sustainable Asteroid Mining”. This paper reports the developments that led to the solution proposed by ESA’s Advanced Concepts Team. Beyond the fact that the proposed approach failed to rank higher than fourth in the final competition leader-board, several innovative fundamental methodologies were developed which have a broader application. In particular, new methods based on machine learning as well as on manipulating the fundamental laws of astrodynamics were developed and able to fill with remarkable accuracy the gap between full low-thrust trajectories and their representation as impulsive Lambert transfers. A novel technique was devised to formulate the challenge of optimal subset selection from a repository of pre-existing optimal mining trajectories as an integer linear programming problem. Finally, the fundamental problem of searching for single optimal mining trajectories (mining and collecting all resources), albeit ignoring the possibility of having intra-ship collaboration and thus sub-optimal in the case of the GTOC12 problem, was efficiently solved by means of a novel search based on a look-ahead score and thus making sure to select asteroids that had chances to be re-visited later on.

关 键 词：GTOC low thrust asteroid mining machine learning mixed-integer linear programming nonlinear programming 

分 类 号：V476[航空宇航科学与技术—飞行器设计]