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10.3389/frobt.2021.624333 http://scihub22266oqcxt.onion/10.3389/frobt.2021.624333 33791341!8006599!33791341     free     free     free       Front+Robot+AI 2021 ; 8 (?): 624333 Nephropedia Template TP {{tp|p=33791341|t=2021. Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment |pdf=|usr=}}{{33791341}} gab.com Text Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment JO: Front Robot AI http://www.kidney.de/pget.php?&tw=1&pmid=33791341 #FOAvip The effective disinfection of hospitals is paramount in lowering the COVID-19 transmission risk to both patients and medical personnel. Autonomous mobile robots can perform the surface disinfection task in a timely and cost-effective manner, while preventing the direct contact of disinfecting agents with humans. This paper proposes an end-to-end coverage path planning technique that generates a continuous and uninterrupted collision-free path for a mobile robot to cover an area of interest. The aim of this work is to decrease the disinfection task completion time and cost by finding an optimal coverage path using a new graph-based representation of the environment. The results are compared with other existing state-of-the-art coverage path planning approaches. It is shown that the proposed approach generates a path with shorter total travelled distance (fewer number of overlaps) and smaller number of turns. Twit Text FOAVip Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment ????Front Robot AI http://www.kidney.de/pget.php?&tw=1&pmid=33791341 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33791341 #FOAvip English Wikipedia <ref>{{Cite pmid|33791341}}</ref> Efficient Coverage Path Planning for Mobile Disinfecting Robots Using Graph-Based Representation of Environment #MMPMID33791341 Nasirian B; Mehrandezh M; Janabi-Sharifi F Front Robot AI 2021[]; 8 (?): 624333 PMID33791341show ga The effective disinfection of hospitals is paramount in lowering the COVID-19 transmission risk to both patients and medical personnel. Autonomous mobile robots can perform the surface disinfection task in a timely and cost-effective manner, while preventing the direct contact of disinfecting agents with humans. This paper proposes an end-to-end coverage path planning technique that generates a continuous and uninterrupted collision-free path for a mobile robot to cover an area of interest. The aim of this work is to decrease the disinfection task completion time and cost by finding an optimal coverage path using a new graph-based representation of the environment. The results are compared with other existing state-of-the-art coverage path planning approaches. It is shown that the proposed approach generates a path with shorter total travelled distance (fewer number of overlaps) and smaller number of turns. ?Efficient Coverage Path Planning for Mobile Disinfecting Robots Using (epmc).pdf DeepDyve Pubget Overpricing