# Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms

arXiv: https://arxiv.org/abs/2101.09491 · HTML: https://mlsanity.com/paper/2101.09491/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 139 references that are in the map.
- First posted on arXiv 23 Jan 2021.

## Builds on (most cited first, 8 of 8)

- [A Survey on Natural Language Processing for Fake News Detection](https://mlsanity.com/paper/1811.00770/) (2018)
- [Assessing the Safety and Reliability of Autonomous Vehicles from Road Testing](https://mlsanity.com/paper/1908.06540/) (2019)
- [Formal Specification and Verification of Autonomous Robotic Systems: A Survey](https://mlsanity.com/paper/1807.00048/) (2018)
- [Assessing Safety-Critical Systems from Operational Testing: A Study on Autonomous Vehicles](https://mlsanity.com/paper/2008.09510/) (2020)
- [Resilience in multi-robot multi-target tracking with unknown number of targets through reconfiguration](https://mlsanity.com/paper/2004.07197/) (2020)
- [Predictive Modeling of Periodic Behavior for Human-Robot Symbiotic Walking](https://mlsanity.com/paper/2005.13139/) (2020)
- [Trustworthy Digital Twins in the Industrial Internet of Things with Blockchain](https://mlsanity.com/paper/2010.12168/) (2020)
- [Challenges in Collaborative HRI for Remote Robot Teams](https://mlsanity.com/paper/1905.07379/) (2019)

## Built on by (most cited first, 2 of 2)

- [Coupling Machine Learning with Ontology for Robotics Applications](https://mlsanity.com/paper/2407.02500/) (2024)
- [The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review](https://mlsanity.com/paper/2606.12423/) (2026)

## Abstract (arXiv)

To reduce Operation and Maintenance (O&M) costs on offshore wind farms, wherein 80% of the O&M cost relates to deploying personnel, the offshore wind sector looks to Robotics and Artificial Intelligence (RAI) for solutions. Barriers to Beyond Visual Line of Sight (BVLOS) robotics include operational safety compliance and resilience, inhibiting the commercialization of autonomous services offshore. To address safety and resilience challenges we propose a Symbiotic System Of Systems Approach (SSOSA), reflecting the lifecycle learning and co-evolution with knowledge sharing for mutual gain of robotic platforms and remote human operators. Our novel methodology enables the run-time verification of safety, reliability and resilience during autonomous missions. To achieve this, a Symbiotic Digital Architecture (SDA) was developed to synchronize digital models of the robot, environment, infrastructure, and integrate front-end analytics and bidirectional communication for autonomous adaptive mission planning and situation reporting to a remote operator. A reliability ontology for the deployed robot, based on our holistic hierarchical-relational model, supports computationally efficient platform data analysis. We demonstrate an asset inspection mission within a confined space through Cooperative, Collaborative and Corroborative (C3) governance (internal and external symbiosis) via decision-making processes and the associated structures. We create a hyper enabled human interaction capability to analyze the mission status, diagnostics of critical sub-systems within the robot to provide automatic updates to our AI-driven run-time reliability ontology. This enables faults to be translated into failure modes for decision-making during the mission.