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Open AccessArticle

Simulation and Analysis of Self-Replicating Robot Decision-Making Systems

Department of Computer Science, North Dakota State University, Fargo, ND 58108, USA
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Computers 2021, 10(1), 9; https://doi.org/10.3390/computers10010009
Received: 13 December 2020 / Revised: 31 December 2020 / Accepted: 1 January 2021 / Published: 6 January 2021
(This article belongs to the Special Issue Feature Paper in Computers)
Self-replicating robot systems (SRRSs) are a new prospective paradigm for robotic exploration. They can potentially facilitate lower mission costs and enhance mission capabilities by allowing some materials, which are needed for robotic system construction, to be collected in situ and used for robot fabrication. The use of a self-replicating robot system can potentially lower risk aversion, due to the ability to potentially replenish lost or damaged robots, and may increase the likelihood of mission success. This paper proposes and compares system configurations of an SRRS. A simulation system was designed and is used to model how an SRRS performs based on its system configuration, attributes, and operating environment. Experiments were conducted using this simulation and the results are presented. View Full-Text
Keywords: self-replicating robots; simulation; autonomous command; decision-making; robot foraging; additive manufacturing fabrication self-replicating robots; simulation; autonomous command; decision-making; robot foraging; additive manufacturing fabrication
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MDPI and ACS Style

Jones, A.; Straub, J. Simulation and Analysis of Self-Replicating Robot Decision-Making Systems. Computers 2021, 10, 9. https://doi.org/10.3390/computers10010009

AMA Style

Jones A, Straub J. Simulation and Analysis of Self-Replicating Robot Decision-Making Systems. Computers. 2021; 10(1):9. https://doi.org/10.3390/computers10010009

Chicago/Turabian Style

Jones, Andrew; Straub, Jeremy. 2021. "Simulation and Analysis of Self-Replicating Robot Decision-Making Systems" Computers 10, no. 1: 9. https://doi.org/10.3390/computers10010009

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