Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
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.
Recommended Citation
Combs, Kara; Bihl, Trevor; and Pennington, James, "Interoperability for Autonomy" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 9.
https://aisel.aisnet.org/hicss-57/da/big_data_and_analytics/9
Interoperability for Autonomy
Hilton Hawaiian Village, Honolulu, Hawaii
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.
https://aisel.aisnet.org/hicss-57/da/big_data_and_analytics/9