Visual row detection using pixel-based algorithm and stereo camera for cotton-picking robot

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dc.contributor.authorFue, K. G.
dc.contributor.authorGeorgia, Tifton
dc.contributor.authorPorter, W. M.
dc.contributor.authorBarnes, E. M.
dc.contributor.authorRains, G. C.
dc.date.accessioned2022-06-14T14:21:28Z
dc.date.available2022-06-14T14:21:28Z
dc.date.issued2019
dc.descriptionConference Paperen_US
dc.description.abstractPrecision farming still depends heavily on RTK-GPS to navigate the rows of crops. However, GPS cannot be the only method to navigate the farm for robots to work as a “swarm” on the same farm; they also require visual systems to navigate and avoid collisions. Also, plant growth and canopy changes are not accommodated. Hence, the visual system remains a complementary method to add to the efficiency of the GPS system. In this study, optical detection of cotton rows is investigated and demonstrated. A stereo camera is used to detect the row depth, and then, a pixel- based algorithm is used to calculate and determine the upper and lower part of the canopy of the cotton rows by assuming the normal distribution of the high and low pixels. The left and right row are detected by using perspective transform and pixel-based sliding window algorithms. Then, the system determines the Bayesian score of the detection and calculates the center of the rows for smooth navigation of the cotton-picking robot. The 92.3% accuracy and F1 score of 0.951 are sufficient to deploy the algorithm for robotic operations. The deployment and testing of the robot navigation will be done in 2019.en_US
dc.identifier.urihttps://www.suaire.sua.ac.tz/handle/123456789/4266
dc.language.isoenen_US
dc.publisher2019 ASABE Annual International Meeting,  Boston, Massachusettsen_US
dc.subjectGPS systemen_US
dc.subjectRTK-GPSen_US
dc.subjectPrecision farmingen_US
dc.subjectrobotic cotton harvestingen_US
dc.titleVisual row detection using pixel-based algorithm and stereo camera for cotton-picking roboten_US
dc.typeConferencce Proceedingsen_US

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