Symbiotic System of Systems design for safe and resilient autonomous robotics in offshore wind farms

Mitchell, D., Blanche, J., Zaki, O., Roe, J., Kong, L., Harper, S., Robu, V., Lim, T. and Flynn, D. (2021) Symbiotic System of Systems design for safe and resilient autonomous robotics in offshore wind farms. IEEE Access, 9, pp. 141421-141452. (doi: 10.1109/ACCESS.2021.3117727)

Abstract

To reduce Operation and Maintenance (O and M) 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 (C 3 ), 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.

• Item Type: Articles
• Additional Information: This work was supported in part by the Offshore Robotic for Certification of Assets (ORCA) Hub under EPSRC Project EP/R026173/1, EPSRC Holistic Operation and Maintenance for Energy (HOME) from Offshore Wind Farms; and in part by MicroSense Technologies Ltd. (MTL) in the provision of their patented microwave FMCW sensing technology (PCT/GB2017/053275) and decommissioned wind turbine blade section.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Blanche, Dr Jamie and Harper, Mr Samuel and Mitchell, Mr Daniel and Flynn, Professor David
• Authors: Mitchell, D., Blanche, J., Zaki, O., Roe, J., Kong, L., Harper, S., Robu, V., Lim, T., and Flynn, D.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity; College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Access
• Publisher: IEEE
• ISSN: 2169-3536
• ISSN (Online): 2169-3536
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in IEEE Access 9:141421-141452
• Publisher Policy: Reproduced under a Creative Commons licence