Time-bounded large-scale mission planning under uncertainty for UV disinfection

The COVID-19 pandemic has motivated research on mobile robot-based disinfection methods to help contain the spread of the virus, including ultraviolet (UV) germicidal inactivation. Recent approaches have focused on formulating autonomous disinfection as a coverage problem. However, the focus so far...

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Main Authors: Brudermüller, L, Bhattacharyya, R, Lacerda, B, Hawes, N
Format: Conference item
Language:English
Published: ICAPS 2022
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author Brudermüller, L
Bhattacharyya, R
Lacerda, B
Hawes, N
author_facet Brudermüller, L
Bhattacharyya, R
Lacerda, B
Hawes, N
author_sort Brudermüller, L
collection OXFORD
description The COVID-19 pandemic has motivated research on mobile robot-based disinfection methods to help contain the spread of the virus, including ultraviolet (UV) germicidal inactivation. Recent approaches have focused on formulating autonomous disinfection as a coverage problem. However, the focus so far has been on maximising coverage, rather than scaling solutions to large-scale environments or making solutions robust to environmental uncertainty. Since the intensity of UV light is strongly coupled with the distance to the target surface, localisation errors should be included in the decision making process to synthesise meaningful irradiation durations. Therefore, in this paper we solve a linked path and dosage planning problem, explicitly considering localisation uncertainty in the model. Our model is formulated as a Markov decision process (MDP) which maps localisation uncertainty to dose delivery distributions given radiation and localisation models. We solve this (MDP) over a finite horizon using prioritised value iteration to maximise dose delivery within specified time bounds. Simulation experiments performed on real-world data show successful disinfection, outperforming a rule-based baseline.
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spelling oxford-uuid:e431c98b-c83d-43c1-88f4-f4d5b9156fd82022-11-10T11:21:51ZTime-bounded large-scale mission planning under uncertainty for UV disinfectionConference itemhttp://purl.org/coar/resource_type/c_5794uuid:e431c98b-c83d-43c1-88f4-f4d5b9156fd8EnglishSymplectic ElementsICAPS2022Brudermüller, LBhattacharyya, RLacerda, BHawes, NThe COVID-19 pandemic has motivated research on mobile robot-based disinfection methods to help contain the spread of the virus, including ultraviolet (UV) germicidal inactivation. Recent approaches have focused on formulating autonomous disinfection as a coverage problem. However, the focus so far has been on maximising coverage, rather than scaling solutions to large-scale environments or making solutions robust to environmental uncertainty. Since the intensity of UV light is strongly coupled with the distance to the target surface, localisation errors should be included in the decision making process to synthesise meaningful irradiation durations. Therefore, in this paper we solve a linked path and dosage planning problem, explicitly considering localisation uncertainty in the model. Our model is formulated as a Markov decision process (MDP) which maps localisation uncertainty to dose delivery distributions given radiation and localisation models. We solve this (MDP) over a finite horizon using prioritised value iteration to maximise dose delivery within specified time bounds. Simulation experiments performed on real-world data show successful disinfection, outperforming a rule-based baseline.
spellingShingle Brudermüller, L
Bhattacharyya, R
Lacerda, B
Hawes, N
Time-bounded large-scale mission planning under uncertainty for UV disinfection
title Time-bounded large-scale mission planning under uncertainty for UV disinfection
title_full Time-bounded large-scale mission planning under uncertainty for UV disinfection
title_fullStr Time-bounded large-scale mission planning under uncertainty for UV disinfection
title_full_unstemmed Time-bounded large-scale mission planning under uncertainty for UV disinfection
title_short Time-bounded large-scale mission planning under uncertainty for UV disinfection
title_sort time bounded large scale mission planning under uncertainty for uv disinfection
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