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PMID: 34703078 Published · ppublish English Journal Article

Occupant-centric robotic air filtration and planning for classrooms for Safer school reopening amid respiratory pandemics.

Robotics and autonomous systems ·Vol. 147 ·2022-01-00 ·页码 103919

Yang H, Balakuntala MV, Quiñones JJ, Kaur U, Moser AE, Doosttalab A, Esquivel-Puentes A, Purwar T, Castillo L, Ma X, Zhang LT, Voyles RM

Abstract

Coexisting with the current COVID-19 pandemic is a global reality that comes with unique challenges impacting daily interactions, business, and facility maintenance. A monumental challenge accompanied is continuous and effective disinfection of shared spaces, such as office/school buildings, elevators, classrooms, and cafeterias. Although ultraviolet light and chemical sprays are routines for indoor disinfection, they irritate humans, hence can only be used when the facility is unoccupied. Stationary air filtration systems, while being irritation-free and commonly available, fail to protect all occupants due to limitations in air circulation and diffusion. Hence, we present a novel collaborative robot (cobot) disinfection system equipped with a Bernoulli Air Filtration Module, with a design that minimizes disturbance to the surrounding airflow and maneuverability among occupants for maximum coverage. The influence of robotic air filtration on dosage at neighbors of a coughing source is analyzed with derivations from a Computational Fluid Dynamics (CFD) simulation. Based on the analysis, the novel occupant-centric online rerouting algorithm decides the path of the robot. The rerouting ensures effective air filtration that minimizes the risk of occupants under their detected layout. The proposed system was tested on a 2 × 3 seating grid (empty seats allowed) in a classroom, and the worst-case dosage for all occupants was chosen as the metric. The system reduced the worst-case dosage among all occupants by 26% and 19% compared to a stationary air filtration system with the same flow rate, and a robotic air filtration system that traverses all the seats but without occupant-centric planning of its path, respectively. Hence, we validated the effectiveness of the proposed robotic air filtration system.

Keywords
Approximation of computational fluid dynamics Robotic air filtration Socially-distanced classrooms Trajectory and speed optimization
作者与单位
共 12 位作者,点击展开单位 / ORCID
Yang Haoguang
Polytechnic Institute, Purdue University, United States of America.
Balakuntala Mythra V
Polytechnic Institute, Purdue University, United States of America.
Quiñones Jhon J
School of Mechanical Engineering, Purdue University, United States of America.
Kaur Upinder
Polytechnic Institute, Purdue University, United States of America.
Moser Abigayle E
School of Mechanical Engineering, Purdue University, United States of America. | Department of Aerospace Engineering, Iowa State University, United States of America.
Doosttalab Ali
School of Mechanical Engineering, Purdue University, United States of America.
Esquivel-Puentes Antonio
School of Mechanical Engineering, Purdue University, United States of America.
Purwar Tanya
School of Mechanical Engineering, Purdue University, United States of America.
Castillo Luciano
School of Mechanical Engineering, Purdue University, United States of America.
Ma Xin
Polytechnic Institute, Purdue University, United States of America.
Zhang Lucy T
Mechanical Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, United States of America.
Voyles Richard M
Polytechnic Institute, Purdue University, United States of America.
Article Info
Journal
Robotics and autonomous systems
Abbr.
Rob Auton Syst
ISSN
0921-8890
Published
2022-01-00
电子出版
2021-00-22
页码
103919
Language
English
Country/Region
Netherlands
NLM ID
100971588
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