Optimal trajectory planning for multiple asteroid tour mission by means of an incremental bio-inspired tree search algorithm

Aram Vroom, Marilena Di Carlo, Juan Manuel Romero Martin, Massimiliano Vasile

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

In this paper, a combinatorial optimisation algorithm inspired by the Physarum Polycephalum mould is presented and applied to the optimal trajectory planning of a multiple asteroid tour mission. The Automatic Incremental Decision Making And Planning (AIDMAP) algorithm is capable of solving complex discrete decision making problems with the use of the growth and exploration of the decision network. The stochastic AIDMAP algorithm has been tested on two discrete astrodynamic decision making problems of increased complexity and compared in terms of accuracy and computational cost to its deterministic counterpart. The results obtained for a mission to the Atira asteroids and to the Main Asteroid Belt show that this non-deterministic algorithm is a good alternative to the use of traditional deterministic combinatorial solvers, as the computational cost scales better with the complexity of the problem.

Original languageEnglish
Title of host publication2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)9781509042401
DOIs
Publication statusPublished - 9 Feb 2017
Event2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 - Athens, Greece
Duration: 6 Dec 20169 Dec 2016

Conference

Conference2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
CountryGreece
CityAthens
Period6/12/169/12/16

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    Vroom, A., Di Carlo, M., Martin, J. M. R., & Vasile, M. (2017). Optimal trajectory planning for multiple asteroid tour mission by means of an incremental bio-inspired tree search algorithm. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 [7850108] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/SSCI.2016.7850108