Print Email Facebook Twitter Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms Title Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms Author Mitchell, Daniel (Heriot-Watt University) Blanche, Jamie (Heriot-Watt University) Zaki, Osama (Heriot-Watt University) Roe, Joshua (Heriot-Watt University) Kong, Leo (Heriot-Watt University) Harper, Samuel (Heriot-Watt University) Robu, Valentin (TU Delft Algorithmics; Heriot-Watt University; Centrum Wiskunde & Informatica (CWI)) Lim, Theodore (Heriot-Watt University) Flynn, David (Heriot-Watt University) Date 2021 Abstract To reduce Operation and Maintenance (OM) expenditure on offshore wind farms, wherein 80% of the cost relates to deploying personnel, the offshore wind sector looks to advances in Robotics and Artificial Intelligence (RAI) for solutions. Barriers to residential Beyond Visual Line of Sight (BVLOS) autonomy as a service, include operational challenges in run-time safety compliance, reliability and resilience, due to the complexities of dealing with known and unknown risk in dynamic environments. In this paper we incorporate a Symbiotic System Of Systems Approach (SSOSA) that uses a Symbiotic Digital Architecture (SDA) to provide a cyber physical orchestration of enabling technologies. Implementing a SSOSA enables Cooperation, Collaboration and Corroboration (C3), as to address run-time verification of safety, reliability and resilience during autonomous missions. Our SDA provides a means to synchronize distributed digital models of the robot, environment and infrastructure. Through the coordinated bidirectional communication network of the SDA, the remote human operator has improved visibility and understanding of the mission profile. We evaluate our SSOSA in an asset inspection mission within a confined operating environment. Demonstrating the ability of our SSOSA to overcome safety, reliability and resilience challenges. The SDA supports lifecycle learning and co-evolution with knowledge sharing across the interconnected systems. Our results evaluate both sudden and gradual faults, as well as unknown events, that may jeopardize an autonomous mission. Using distributed and coordinated decision making, the SSOSA enhances the analysis of the mission status, which includes diagnostics of critical sub-systems within the resident robot. This evaluation demonstrates that the SSOSA provides enhanced run-time operational resilience and safety compliance to BVLOS autonomous missions. The SSOSA has the potential to be a highly transferable methodology to other mission scenarios and technologies, providing a pathway to implementing scalable autonomy as a service. Subject Artificial intelligenceautonomous systemsdigital twinnon-destructive evaluationresilient roboticssafety compliancesensorssymbiotic systemssystem ontology To reference this document use: http://resolver.tudelft.nl/uuid:ea788894-f3f9-4631-956b-ca702c704b2d DOI https://doi.org/10.1109/ACCESS.2021.3117727 ISSN 2169-3536 Source IEEE Access, 9, 141421-141452 Part of collection Institutional Repository Document type journal article Rights © 2021 Daniel Mitchell, Jamie Blanche, Osama Zaki, Joshua Roe, Leo Kong, Samuel Harper, Valentin Robu, Theodore Lim, David Flynn Files PDF Symbiotic_System_of_Syste ... _Farms.pdf 5.7 MB Close viewer /islandora/object/uuid:ea788894-f3f9-4631-956b-ca702c704b2d/datastream/OBJ/view