Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Mitchell, Daniel; Emor Baniqued, Paul Dominick; Zahid, Abdul; West, Andrew; Nouri Rahmat Abadi, Bahman; Lennox, Barry; Liu, Bin; Kizilkaya, Burak; Flynn, David; Francis, David John; Pulgarin, Erwin Jose Lopez; Zhao, Guodong; Kivrak, Hasan; Blanche, Jamie Rowland Douglas; David, Jennifer; Wang, Jingyan; Bolarinwa, Joseph; Yao, Kanzhong; Groves, Keir; Qi, Liyuan; Shawky, Mahmoud A.; Giuliani, Manuel; Sandison, Melissa; Popoola, Olaoluwa; Marjanovic, Ognjen; Bremner, Paul; Harper, Samuel Thomas; Nandakumar, Shivoh; Watson, Simon; Agrawal, Subham; Lim, Theodore; Johnson, Thomas; Ahmad, Wasim; Xu, Xiangmin; Meng, Zhen; Jiang, Zhengyi

Abstract

AbstractNuclear 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.

Citation

Mitchell, D., Emor Baniqued, P. D., Zahid, A., West, A., Nouri Rahmat Abadi, B., Lennox, B., …Jiang, Z. (2023). Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments. IET Cyber-Systems and Robotics, 5(4), Article e12103. https://doi.org/10.1049/csy2.12103

• Journal Article Type: Article
• Acceptance Date: Oct 30, 2023
• Online Publication Date: Dec 26, 2023
• Publication Date: Dec 31, 2023
• Deposit Date: Jan 2, 2024
• Publicly Available Date: Jan 2, 2024
• Journal: IET Cyber-Systems and Robotics
• Electronic ISSN: 2631-6315
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Issue: 4
• Article Number: e12103
• DOI: https://doi.org/10.1049/csy2.12103
• Keywords: Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Hardware and Architecture, Human-Computer Interaction, Information Systems
• Public URL: https://uwe-repository.worktribe.com/output/11533303