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

dc.creatorFue, K. G.
dc.creatorGeorgia, Tifton
dc.creatorPorter, W. M.
dc.creatorBarnes, E. M.
dc.creatorRains, G. C.
dc.date2022-06-14T14:21:28Z
dc.date2022-06-14T14:21:28Z
dc.date2019
dc.date.accessioned2022-10-25T08:50:37Z
dc.date.available2022-10-25T08:50:37Z
dc.descriptionConference Paper
dc.descriptionPrecision 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.
dc.formatapplication/pdf
dc.identifierhttps://www.suaire.sua.ac.tz/handle/123456789/4266
dc.identifier.urihttp://hdl.handle.net/123456789/90424
dc.languageen
dc.publisher2019 ASABE Annual International Meeting,  Boston, Massachusetts
dc.subjectGPS system
dc.subjectRTK-GPS
dc.subjectPrecision farming
dc.subjectrobotic cotton harvesting
dc.titleVisual row detection using pixel-based algorithm and stereo camera for cotton-picking robot
dc.typeConferencce Proceedings

Files