Aitken, J. orcid.org/0000-0003-4204-4020, Veres, S., Shaukat, A. et al. (7 more authors) (2018) Autonomous nuclear waste management. IEEE Intelligent Systems, 33 (6). pp. 47-55. ISSN 1541-1672
Abstract
Redundant and non-operational buildings at nuclear sites are decommissioned over a period of time. The process involves demolition of physical infrastructure resulting in large quantities of residual waste material. The resulting waste materials are packed into import containers to be delivered for post-processing, containing either sealed canisters or assortments of miscellaneous objects. At present post-processing does not happen within the United Kingdom. Sellafield Ltd. and National Nuclear Laboratory are developing a process for future operation so that upon an initial inspection, imported waste materials undergo two stages of post-processing before being packed into export containers, namely sort and segregate or sort and disrupt. The post-processing facility will remotely treat and export a wide range of wastes before downstream encapsulation. Certain wastes require additional treatment, such as disruption, before export to ensure suitability for long-term disposal. This article focuses on the design, development, and demonstration of a reconfigurable rational agent-based robotic system that aims to highly automate these processes removing the need for close human supervision. The proposed system is being demonstrated through a downsized, lab-based setup incorporating a small-scale robotic arm, a time-of-flight camera, and high-level rational agent-based decision making and control framework.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | computing methodologies; artificial intelligence; robotics; commercial robots and applications; affective computing; affective computing applications; social agents/robotics; vision; affective issues in enhancing machine/robotic intelligence; function in robotic systems; function in intelligent systems |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/J011843/1 NATIONAL NUCLEAR LABORATORY UNSPECIFIED |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Dec 2017 16:26 |
Last Modified: | 15 Mar 2024 17:00 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/MIS.2018.111144814 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:124729 |