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Robotic Satellite Servicing Trade Space Down‐Selection
Author(s) -
Knizhnik Jessica,
Austin Mark,
Carignan Craig
Publication year - 2017
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2017.00442.x
Subject(s) - satellite , computer science , task (project management) , set (abstract data type) , selection (genetic algorithm) , graph , transformation (genetics) , systems engineering , variety (cybernetics) , space (punctuation) , engineering , artificial intelligence , aerospace engineering , operating system , biochemistry , chemistry , theoretical computer science , gene , programming language
As remote robotic space satellite servicing technologies develop, each servicer satellite will need to account for a number of servicing scenarios and consider a variety of alternate design solutions to best meet the most servicing scenario requirements. This paper presents a graph transformation method for systematically down‐selecting the number of design options available, and highlighting trade‐offs in sets of design solutions which best meet satellite servicing task requirements while also reducing total mass, maximum power needed and servicing time. In the test case examined, the proposed method successfully identifies for further consideration, seven best design solutions from a set of over 100,000 potential solutions.