Implementing autonomy in nuclear robotics; an experience-informed review of applying SACE

Phillip Mulvana; Lacey-Jo Marsland; Tom Boden; Guy Burroughes; Richard David Hawkins; Matthew Osborne

Implementing autonomy in nuclear robotics; an experience-informed review of applying SACE

Phillip Mulvana, Lacey-Jo Marsland, Tom Boden, Guy Burroughes, Richard David Hawkins, Matthew Osborne

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Nuclear decommissioning is a complex, hazardous, and time-consuming process that requires highly skilled and trained operators. To address the workforce bottleneck and the growing inventory of nuclear materials, a Robotic Glovebox with AI capability that can assist in the preparation and processing of nuclear material is being developed. This innovative solution can enable safer, more efficient, and continuous decommissioning operations. To support the adoption of this new technology it is necessary to develop a safety case for the system. In this paper we describe how we have used an autonomous system safety case process (the SACE approach) to generate confidence in our initial AI glovebox design. This safety case example is being provided as input it into the Office for Nuclear Regulation (ONR) regulatory innovation sandbox and should help to establish a new paradigm in safety cases for autonomous systems in nuclear environments.

Original language	English
Title of host publication	Safety-Critical Systems Symposium (SSS’24)
Publication status	Accepted/In press - 30 Nov 2024
Event	Safety Critical Systems Symposium - Bristol, United Kingdom Duration: 13 Feb 2024 → 15 Feb 2024

Conference

Conference	Safety Critical Systems Symposium
Abbreviated title	SSS'24
Country/Territory	United Kingdom
City	Bristol
Period	13/02/24 → 15/02/24

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

Access to Document

Mulvana et al - SSS 2024 FINAL
This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.
Accepted author manuscript, 574 KBLicence: CC BY

Cite this

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title = "Implementing autonomy in nuclear robotics; an experience-informed review of applying SACE",

abstract = "Nuclear decommissioning is a complex, hazardous, and time-consuming process that requires highly skilled and trained operators. To address the workforce bottleneck and the growing inventory of nuclear materials, a Robotic Glovebox with AI capability that can assist in the preparation and processing of nuclear material is being developed. This innovative solution can enable safer, more efficient, and continuous decommissioning operations. To support the adoption of this new technology it is necessary to develop a safety case for the system. In this paper we describe how we have used an autonomous system safety case process (the SACE approach) to generate confidence in our initial AI glovebox design. This safety case example is being provided as input it into the Office for Nuclear Regulation (ONR) regulatory innovation sandbox and should help to establish a new paradigm in safety cases for autonomous systems in nuclear environments.",

author = "Phillip Mulvana and Lacey-Jo Marsland and Tom Boden and Guy Burroughes and Hawkins, {Richard David} and Matthew Osborne",

note = "This is an author-produced version of the published paper. Uploaded in accordance with the University{\textquoteright}s Research Publications and Open Access policy. ; Safety Critical Systems Symposium, SSS'24 ; Conference date: 13-02-2024 Through 15-02-2024",

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AU - Mulvana, Phillip

AU - Marsland, Lacey-Jo

AU - Boden, Tom

AU - Burroughes, Guy

AU - Hawkins, Richard David

AU - Osborne, Matthew

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.

PY - 2024/11/30

Y1 - 2024/11/30

N2 - Nuclear decommissioning is a complex, hazardous, and time-consuming process that requires highly skilled and trained operators. To address the workforce bottleneck and the growing inventory of nuclear materials, a Robotic Glovebox with AI capability that can assist in the preparation and processing of nuclear material is being developed. This innovative solution can enable safer, more efficient, and continuous decommissioning operations. To support the adoption of this new technology it is necessary to develop a safety case for the system. In this paper we describe how we have used an autonomous system safety case process (the SACE approach) to generate confidence in our initial AI glovebox design. This safety case example is being provided as input it into the Office for Nuclear Regulation (ONR) regulatory innovation sandbox and should help to establish a new paradigm in safety cases for autonomous systems in nuclear environments.

AB - Nuclear decommissioning is a complex, hazardous, and time-consuming process that requires highly skilled and trained operators. To address the workforce bottleneck and the growing inventory of nuclear materials, a Robotic Glovebox with AI capability that can assist in the preparation and processing of nuclear material is being developed. This innovative solution can enable safer, more efficient, and continuous decommissioning operations. To support the adoption of this new technology it is necessary to develop a safety case for the system. In this paper we describe how we have used an autonomous system safety case process (the SACE approach) to generate confidence in our initial AI glovebox design. This safety case example is being provided as input it into the Office for Nuclear Regulation (ONR) regulatory innovation sandbox and should help to establish a new paradigm in safety cases for autonomous systems in nuclear environments.

M3 - Conference contribution

BT - Safety-Critical Systems Symposium (SSS’24)

T2 - Safety Critical Systems Symposium

Y2 - 13 February 2024 through 15 February 2024

ER -