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Performance analysis of autonomous UV disinfecting robot (UV bot) using Taguchi method.
Gowri, Vigneswari; Sethuramalingam, Prabhu; Uma, M.
  • Gowri V; Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai 603203, India.
  • Sethuramalingam P; Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai 603203, India.
  • Uma M; Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai 603203, India.
Mater Today Proc ; 68: 1980-1987, 2022.
Article in English | MEDLINE | ID: covidwho-2116870
ABSTRACT
As a result of the COVID-19 epidemic, there is a growing demand for robots to perform various operations which include service bots, cleaning, and disinfection bots. Viral contamination has been one of the major causes of human fatality which has abruptly increased in this situation. Availability of existing technologies is always surpassed by an effective one so as is the UV-Bot developed in this project. This bot aims for a highly accurate percentage of up to 96.8% of germ clearance at pre-defined conditions which are user-friendly. Also, the robot is designed in a compact size and effective shape to achieve maximum efficiency. The robot is deployed in hospital pathway and rooms for disinfection whereas human detection and obstacle avoidance has been included with a custom-developed algorithm that supports autonomous navigation and corner tracking facility. The robot also supports live streaming of the disinfecting site with an emergency alarm and stop in human detection. This type of robot is highly capable of destroying viral infections at a particular point which is validated using Taguchi analysis and also the robot is 3D modelled and tested using static and dynamic obstacles. Thus UV-Bot is manually controllable or autonomous which uses the A* algorithm to store or retrieve the disinfecting site map which is recorded if used frequently.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Mater Today Proc Year: 2022 Document Type: Article Affiliation country: J.matpr.2022.08.227

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Mater Today Proc Year: 2022 Document Type: Article Affiliation country: J.matpr.2022.08.227