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Strawberry Plant Alive Status Detection and Relative Pixel Based Plant Localization

Xiangling Kong, Yunjun Xu

发表年份
2020
引用次数
2

摘要

Abstract Autonomous 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.

关键词

RangingPixelComputer scienceGlobal Positioning SystemComputer visionArtificial intelligenceKalman filterKinematicsReal Time KinematicLidar

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