Abstract
Assembly of large scale structural systems in space is understood as critical to serving applications that cannot be deployed from a single launch. Recent literature proposes the use of discrete modular structures for in-space assembly and relatively small scale robotics that are able to modify and traverse the structure. This paper addresses the algorithmic problems in scaling reconfigurable space structures built through robotic construction, where reconfiguration is defined as the problem of transforming an initial structure into a different goal configuration. We analyze different algorithmic paradigms and present corresponding abstractions and graph formulations, examining specialized algorithms that consider discretized space and time steps. We then discuss fundamental design trades for different computational architectures, such as centralized versus distributed, and present two representative algorithms as concrete examples for comparison. We analyze how those algorithms achieve different objective functions and goals, such as minimization of total distance traveled, maximization of fault-tolerance, or minimization of total time spent in assembly. This is meant to offer an impression of algorithmic constraints on scalability of corresponding structural and robotic design. From this study, a set of recommendations is developed on where and when to use each paradigm, as well as implications for physical robotic and structural system design.
Original language | English |
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Title of host publication | 2019 IEEE Aerospace Conference, AERO 2019 |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Number of pages | 8 |
ISBN (Electronic) | 978-1-5386-6854-2 |
DOIs | |
Publication status | Published - 6 Dec 2019 |
Event | 2019 IEEE Aerospace Conference - Big Sky, United States Duration: 2 Mar 2019 → 9 Mar 2019 |
Conference
Conference | 2019 IEEE Aerospace Conference |
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Country/Territory | United States |
City | Big Sky |
Period | 2/03/19 → 9/03/19 |
Funding
This research was supported by the Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project through NASA STMD Game Changing Development (GCD) Program, the NASA Space Technology Research Fellowship (NSTRF) Grant NNX14AM40H, the NASA International Internship program, the MIT International Science and Technology Initiative (MISTI), and the Center for Bits and Atoms (CBA) consortia funding.