农业机械学报2024，Vol.55Issue(4)：124-135,12.DOI:10.6041/j.issn.1000-1298.2024.04.012
丘陵果园自然环境下柑橘采摘机器人设计与试验
Design and Experiment of Citrus Picking Robot in Hilly Orchard Natural Environment
摘要
Abstract
In the future development of orchard industry,intelligent orchard is an important development trend.In order to realize the intelligent orchard,intelligent fruit picking is one of the key bottlenecks.In order to achieve the goal of intelligent fruit picking,a citrus picking robot system suitable for hilly dwarf cultivation of fruit trees was built.Aiming at the uneven ground between ridges in hilly orchards and the terrain inclination angle of 0°～20°,an adaptive leveling platform was designed to keep the base level of the manipulator.The visual system used the depth camera to obtain the point cloud image to establish the three-dimensional model of the fruit tree,and realize the acquisition of the position information of the fruit to be picked.In order to avoid damage to the fruit during the picking process,an integrated end-effector for shearing and clamping was designed,which protected the fruit from damage while picking the fruit by shearing and clamping.The main interference factors in the orchard in the natural environment were light and wind.The light and wind were graded,and 10 foot control experiments were set up.The results showed that under low light or normal light conditions,the average fruit positioning accuracy was 82.5％,the end-effector clamping success rate was 87.5％,and the average fruit picking time was 12.3 s/piece.The average fruit positioning accuracy under high light conditions was 72％,the success rate of end-effector clamping was 80％,and the average time of fruit picking was 12.5 s/piece.The research result can provide a reference for the study of fruit picking in hilly terrain.关键词
柑橘/采摘机器人/三维点云模型/自适应平台/末端执行器Key words
citrus/picking robot/3D point cloud model/adaptive platform/end-effector分类
农业科技引用本文复制引用
鲍秀兰,马志涛,马萧杰,黎亦书,任梦涛,李善军..丘陵果园自然环境下柑橘采摘机器人设计与试验[J].农业机械学报,2024,55(4):124-135,12.基金项目
湖北省农机装备补短板核心技术应用攻关项目(HBSNYT202219)和国家重点研发计划项目(2020YFD1000101) （HBSNYT202219）
