Lessons learned: symbiotic autonomous robot ecosystem for nuclear environments

Mitchell, D. et al. (2023) Lessons learned: symbiotic autonomous robot ecosystem for nuclear environments. IET Cyber-Systems and Robotics, 5(4), e12103. (doi: 10.1049/csy2.12103)

Abstract

Nuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Clean Out (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding during nuclear decommissioning phases. The UK Nuclear Decommissioning Authority supports the view that human-in-the-loop (HITL) robotic deployments are a solution to improve procedures and reduce risks within radiation characterisation of nuclear sites. The authors present a novel implementation of a Cyber-Physical System (CPS) deployed in an analogue nuclear environment, comprised of a multi-robot (MR) team coordinated by a HITL operator through a digital twin interface. The development of the CPS created efficient partnerships across systems including robots, digital systems and human. This was presented as a multi-staged mission within an inspection scenario for the heterogeneous Symbiotic Multi-Robot Fleet (SMuRF). Symbiotic interactions were achieved across the SMuRF where robots utilised automated collaborative governance to work together, where a single robot would face challenges in full characterisation of radiation. Key contributions include the demonstration of symbiotic autonomy and query-based learning of an autonomous mission supporting scalable autonomy and autonomy as a service. The coordination of the CPS was a success and displayed further challenges and improvements related to future MR fleets.

• Item Type: Articles
• Additional Information: We would also like to thank the following funders who enabled this work to take place. EPSRC Grants EP/P01366X/1(RNE), EP/W001128/1 (RAIN+), EPSRC Impact Acceleration Account Secondment Scheme, “Heterogeneous multi‐agent robotic inspection missions” which was jointly funded by Sellafield Ltd., The University of Manchester and EPSRC, Chinese Scholarship Council‐University of Manchester joint programme, EPSRC Grant EP/V026941/1 (ALACANDRA) and SBRI—Digital Technologies for Robotic Nuclear Decommissioning: Teleoperation with digital twins— C/2064382.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhao, Dr Guodong and Kizilkaya, Mr Burak and Popoola, Dr Olaoluwa and Harper, Mr Samuel and Mitchell, Mr Daniel and Wang, Mr Jingyan and XU, Xiangmin and Blanche, Dr Jamie and Meng, Zhen and Shawky, Mr Mahmoud and Qi, Mr Liyuan and Ahmad, Dr Wasim and Flynn, Professor David and Zahid, Mr Abdul Ghani
• Authors: Mitchell, D., Emor Baniqued, P. D., Zahid, A., West, A., Nouri Rahmat Abadi, B., Lennox, B., Liu, B., Kizilkaya, B., Flynn, D., Francis, D. J., Pulgarin, E. J. L., Zhao, G., Kivrak, H., Blanche, J. R. D., David, J., Wang, J., Bolarinwa, J., Yao, K., Groves, K., Qi, L., Shawky, M. A., Giuliani, M., Sandison, M., Popoola, O., Marjanovic, O., Bremner, P., Harper, S. T., Nandakumar, S., Watson, S., Agrawal, S., Lim, T., Johnson, T., Ahmad, W., XU, X., Meng, Z., and Jiang, Z.
• College/School: College of Science and Engineering; 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: IET Cyber-Systems and Robotics
• Publisher: Wiley
• ISSN: 2631-6315
• ISSN (Online): 2631-6315
• Published Online: 26 December 2023
• Copyright Holders: Copyright © 2023 The Author(s)
• First Published: First published in IET Cyber-Systems and Robotics 5(4):e12103
• Publisher Policy: Reproduced under a Creative Commons license