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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 windsector looks to Robotics and Artificial Intelligence (RAI) for solutions.Barriers to Beyond Visual Line of Sight (BVLOS) robotics include operationalsafety compliance and resilience, inhibiting the commercialization ofautonomous services offshore. To address safety and resilience challenges wepropose a Symbiotic System Of Systems Approach (SSOSA), reflecting thelifecycle learning and co-evolution with knowledge sharing for mutual gain ofrobotic platforms and remote human operators. Our novel methodology enables therun-time verification of safety, reliability and resilience during autonomousmissions. To achieve this, a Symbiotic Digital Architecture (SDA) was developedto synchronize digital models of the robot, environment, infrastructure, andintegrate front-end analytics and bidirectional communication for autonomousadaptive mission planning and situation reporting to a remote operator. Areliability ontology for the deployed robot, based on our holistichierarchical-relational model, supports computationally efficient platform dataanalysis. We demonstrate an asset inspection mission within a confined spacethrough Cooperative, Collaborative and Corroborative (C3) governance (internaland external symbiosis) via decision-making processes and the associatedstructures. We create a hyper enabled human interaction capability to analyzethe mission status, diagnostics of critical sub-systems within the robot toprovide automatic updates to our AI-driven run-time reliability ontology. Thisenables faults to be translated into failure modes for decision-making duringthe mission.

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