Verifying and assessing a performance of an automatic vacuum robot under different room conditions
Issued Date
2022-01-01
Resource Type
eISSN
23987340
Scopus ID
2-s2.0-85127822117
Journal Title
EPiC Series in Computing
Volume
82
Start Page
11
End Page
20
Rights Holder(s)
SCOPUS
Bibliographic Citation
EPiC Series in Computing Vol.82 (2022) , 11-20
Suggested Citation
Pinyo T.P. Verifying and assessing a performance of an automatic vacuum robot under different room conditions. EPiC Series in Computing Vol.82 (2022) , 11-20. 20. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/87512
Title
Verifying and assessing a performance of an automatic vacuum robot under different room conditions
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
Artificial intelligence has become the mainstream technology. Automatic vacuum cleaners or robot vacuums change the field of vacuum cleaners with an involvement of an automation, which is a technology that makes people’s daily life easier and more economical. Robot vacuums were invented by the Massachusetts Institute of Technology in 1990. Today, robot vacuums are successful and have many users all around the world. More than 2.5 million families live in 60 countries use them. However, a question that is still being asked about robot vacuum is the efficiency of room coverage and the ability to remember the redundant areas that have already been cleaned. The answers to these questions are unclear, as manufacturers do not reveal the algorithms that are learned by robots, or sometimes they just partially did, due to business reasons. This study was proposed in response to the above questions by using our mobile application for tracking and recording actual geolocations of the robot walking across various points of the room by extracting the real geolocation data from satellites consisting of a latitude and a longitude under multiple different room conditions. Once the robot has cleaned throughout the room, the application reported all areas that the robot has cleaned for analysis purpose. We presented the actual route map, the coverage area map, and the duplicate area map of the robot that potentially led the further understanding of robot vacuum’s effectiveness.