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A Marine Autonomous Systems Digital Twin; Bringing value to researchers, data users and vehicle operations

Buck, Justin J.H.; Lopez, Alvaro Lorenzo; Hawes, Nick; Allsup, Benjamin; Dobra, Tom; Ferreira, Tobias; Kokkinaki, Alexandra; Morris, Ashley; Lacerda, Bruno; Patmore, Ryan; Polton, Jeff ORCID: https://orcid.org/0000-0003-0131-5250; Williams, Charlotte; Woodward, Stephen. 2024 A Marine Autonomous Systems Digital Twin; Bringing value to researchers, data users and vehicle operations. In: OCEANS 2024 - Halifax, Halifax, NS, Canada, 23 - 26 September 2024. IEEE, 1-4.

Abstract
The upscaling of the use of autonomous ocean observing platforms in line with Whitt et al. (2020) has created the requirements for improved interfaces to enable efficient and interactive piloting of marine autonomous platforms. Such interfaces will enable scalable operations that make use of pilots who are accountable for the operation of platforms, enabling more interactive control of the platforms to facilitate researchers to be closer to vehicle operations, and maximize the value of observations for different user types e.g. synoptic surveys for blue skies research versus the needs of operational ocean models Independently of the evolution in autonomous ocean platforms, the concept of digital twins has emerged and has attained prominence within ocean oceanography by activities like the UN Decade for sustainable ocean development digital twin of the ocean programme. Thus, digital twins have the potential to facilitate efficient and interactive operations of platforms with a low technical barrier for users, and be interoperable with related tools such as digital twins for decision making by policy makers. These developments and concepts are being brought together in the Marine Autonomous Systems Digital Twin (MAS-DT) project with three goals: 1. Enable researcher to have more control of ocean glider operations on projects while retaining pilot accountability. 2. Increase the value of ocean glider observations to operational ocean models. 3. Make the operation of increasingly complex ocean glider missions more efficient for autonomous vehicle pilots MAS-DT will bring together visualization of operations, AI to aid decision making and develop a work flow that meets the needs of researcher and platform pilots. MAS-DT will develop the digital twin within the NOC Command and Control systems (C2) for autonomous platforms incorporating new AI based decision making tools developed by the Oxford Robotics Institute. This paper will present the design of MAS-DT prior to formal trials on exemplar glider deployments later in 2024.
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Programmes:
NOC Programmes > Marine Autonomous Robotic Systems
NOC Research Groups 2025 > Marine Autonomous Robotic Systems
NOC Programmes > Digital Ocean
NOC Programmes > Marine Physics and Ocean Climate
NOC Programmes > Marine Systems Modelling
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