Ultraviolet type-C irradiation (UV-C) is an effective no-contact disinfection procedure for surfaces and environments to reduce the spread of severe acute respiratory syndrome coron- avirus 2 (SARS-CoV-2), the virus that causes COVID-19. This work evaluates the effect of the adoption of mobile robots for UV-C irradiation, compared to conventional disinfection methods based on static UV-C lamps. On-field evaluation was conducted to measure the energy dose delivered by a robot-based moving source of UV-C radiation at different locations in an indoor environment. The effectively released radiation dose was experimentally measured using distributed UV-C-sensitive detectors, considering all of the environmental factors involved. Moreover, this article proposes a novel trajectory planner consisting of a genetic algorithm (GA) that explores the possible trajectories and disinfection outcomes of a robot moving in a tunable artificial potential field (APF) and is capable of maximizing the delivered UV dose based on ambient geometry. The experimental results show that, compared to a conventional trajectory, an optimized one has better performance in terms of both the coverage of the radiated energy in the environment and the time required to complete the disinfection task.

UV-C Mobile Robots with Optimized Path Planning

tiseni, luca;chiaradia, domenico;gabardi, massimiliano;solazzi, massimiliano;leonardis, daniele;frisoli, antonio
2021

Abstract

Ultraviolet type-C irradiation (UV-C) is an effective no-contact disinfection procedure for surfaces and environments to reduce the spread of severe acute respiratory syndrome coron- avirus 2 (SARS-CoV-2), the virus that causes COVID-19. This work evaluates the effect of the adoption of mobile robots for UV-C irradiation, compared to conventional disinfection methods based on static UV-C lamps. On-field evaluation was conducted to measure the energy dose delivered by a robot-based moving source of UV-C radiation at different locations in an indoor environment. The effectively released radiation dose was experimentally measured using distributed UV-C-sensitive detectors, considering all of the environmental factors involved. Moreover, this article proposes a novel trajectory planner consisting of a genetic algorithm (GA) that explores the possible trajectories and disinfection outcomes of a robot moving in a tunable artificial potential field (APF) and is capable of maximizing the delivered UV dose based on ambient geometry. The experimental results show that, compared to a conventional trajectory, an optimized one has better performance in terms of both the coverage of the radiated energy in the environment and the time required to complete the disinfection task.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11382/536097
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