2026-09-19T10:46:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1558762024-08-02T03:09:25Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Benjamin, Michael Richard
Becker, Kevin
Massachusetts Institute of Technology. Department of Mechanical Engineering
2024-08-01T19:02:57Z
2024-08-01T19:02:57Z
2024-05
2024-06-13T16:46:07.625Z
https://hdl.handle.net/1721.1/155876
Batch testing simulations of autonomy software make verification and optimization much easier and more robust. The ability to verify and optimize code is particularly important for large, expensive assets, such as marine vessels, where the cost of any failure is high. This thesis discusses the architecture, implementation, and use of an expandable simulation toolbox for MOOS-IvP. The toolbox utilizes Monte Carlo simulations since these are incredibly flexible for differing scenarios. A distributed architecture improves robustness since a single failure does not bring the cluster down. Additionally, personal computers may be added to the cluster during off hours, thus increasing the average computing power.
S.M.
Massachusetts Institute of Technology
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Copyright retained by author(s)
https://creativecommons.org/licenses/by-nc-nd/4.0/
Development of a Distributed Simulation Cluster for MOOS-IvP
Thesis
application/pdf
Master
Master of Science in Mechanical Engineering
Publication
unknown
unknown
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<Abstract>Batch testing simulations of autonomy software make verification and optimization much easier and more robust. The ability to verify and optimize code is particularly important for large, expensive assets, such as marine vessels, where the cost of any failure is high. This thesis discusses the architecture, implementation, and use of an expandable simulation toolbox for MOOS-IvP. The toolbox utilizes Monte Carlo simulations since these are incredibly flexible for differing scenarios. A distributed architecture improves robustness since a single failure does not bring the cluster down. Additionally, personal computers may be added to the cluster during off hours, thus increasing the average computing power.</Abstract>
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