Interoperability for Autonomy
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Date
2024-01-03
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903
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Abstract
Autonomous systems aim to augment human capabilities with machine-based decision-making in the absence of a user. Ideally, autonomy hardware and software would be modular, having the ability to swap components in and out as needed based on necessary capabilities. However, many legacy systems in use utilize proprietary software with specific standards and components, reducing the system’s ability to be interoperable. Currently, the literature’s definition of interoperability is vague and often mistaken for other similar terms. We distinguish the uniqueness of interoperability and codify it through a taxonomy. Next, we extend this framework to understand autonomy and its hardware/software components through a proposed unified autonomy stack. We then evaluate the similarity between four autonomy architectures based on 29 stack components that are later presented in the “interchangeability matrix.” Thus, we demonstrate the necessity to unify autonomy hardware/software under the proposed taxonomy in the development of future autonomous systems.
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Big Data and Analytics: Pathways to Maturity, artificial intelligence, autonomy, evaluation, interoperability, pathway to maturity
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10 pages
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Proceedings of the 57th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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