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Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments

Daniel Mitchell, Paul Dominick E. Baniqued, Abdul Zahid, Andrew West, Bahman Nouri Rahmat Abadi, Barry Lennox, Bin Liu, Burak Kizilkaya, David Flynn, David John Francis, Erwin Jose López Pulgarín, Guodong Zhao, Hasan Kivrak, Jamie Blanche, Jennifer David, Wang Jing-yan, Joseph Bolarinwa, Kanzhong Yao, Keir Groves, Liyuan Qi

发表年份
2023
引用次数
19
访问权限
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摘要

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.

关键词

Nuclear decommissioningRobotComputer scienceSystems engineeringProcess managementEngineering managementEngineeringArtificial intelligence

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