Sensor Fusion of Light Detection and Ranging and iBeacon to Enhance Accuracy of Autonomous Mobile Robot in Hard Disk Drive Clean Room Production Line

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dc.contributor.authorYanyong, Sarucha
dc.contributor.authorParichatprecha, Rattapoohm
dc.contributor.authorChaisiri, Punyavee
dc.contributor.authorKaitwanidvilai, Somyot
dc.contributor.authorKonghuayrob, Poom
dc.date.accessioned2026-08-06T10:40:11Z
dc.date.available2026-08-06T10:40:11Z
dc.date.issued2023-01-01
dc.description.abstractIn this paper, the adaptive Monte Carlo localization (AMCL) error in terms of similar data detected by light detection and ranging (LiDAR) in different locations is investigated. This localization causes a robot to move to the incorrect location temporarily. We propose the fusion of landmark-based localization using an iBeacon device combined with the AMCL algorithm. This technique can solve the probabilistic localization problem of the conventional techniques applied in mobile robots by fusing the timed elastic band (TEB) and scan-matching algorithms, which reduces the error from 7 cm to less than 3 cm. The proposed technique is implemented on a clean-room-type mobile robot with 100 kg payload certificated by the SOP39 standard.
dc.identifier.citationSensors and Materials, 35(4), 1473-1486, 2023
dc.identifier.doi10.18494/SAM4158
dc.identifier.issn09144935
dc.identifier.other2-s2.0-85158819980
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/14069
dc.sourceSensors and Materials
dc.subjectiBeacon
dc.subjectmobile robot
dc.subjectrobot operating system
dc.subjectscan matching
dc.subjecttimed elastic band local planner
dc.titleSensor Fusion of Light Detection and Ranging and iBeacon to Enhance Accuracy of Autonomous Mobile Robot in Hard Disk Drive Clean Room Production Line
dc.typeArticle

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