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dc.contributor.authorKong, Xiangling
dc.contributor.authorXu, Yunjun
dc.date.accessioned2022-02-04T14:51:18Z
dc.date.available2022-02-04T14:51:18Z
dc.date.copyright2020/02/14/
dc.date.issued2020
dc.identifier.issn0022-0434
dc.identifier.otherds_142_05_054501.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4274524
dc.description.abstractAutonomous plant alive status monitoring and corresponding localization of individual plant are two important tasks in precision agriculture. In this study, two new methods that are crucial to such robotic operations are proposed. First, a low cost and light scene invariant approach is proposed to differentiate green and yellow leaves using distinct color-ratio index ranges. Second, based on the relative pixel information of neighboring plants, an extended Kalman filter is used to determine plant positions. Such a differential style localization method is shown to be capable of achieving a similar centimeter level accuracy as light detection and ranging (LIDAR) or real-time kinematic-global positioning system (RTK-GPS) based approaches, but with a much lower upfront and maintenance cost. These two new methods are successfully validated in a nearby commercial field.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleStrawberry Plant Alive Status Detection and Relative Pixel Based Plant Localization
dc.typeJournal Paper
dc.journal.volume142
dc.journal.issue5
dc.journal.titleJournal of Dynamic Systems, Measurement, and Control
dc.identifier.doi10.1115/1.4046102
dc.page54501
dc.treeJournal of Dynamic Systems, Measurement, and Control:;2020:;volume( 142 ):;issue: 005
dc.contenttypeFulltext


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