施药机器人对行施药系统的设计与试验
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江苏省农业科技自主创新资金项目(CX(15)1033)


Design and experiment of row-following pesticide spraying system by robot
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    【目的】设计一种能在作物行间自主导航的施药机器人,实现移动机器人在温室中自动行走并均匀施药。【方法】针对导航路径识别受光线变化影响较大的问题,在Kinect摄像机获取的彩色图像中选取了HIS空间,并对K-means算法的聚类中心和聚类数目的选取进行了优化,随后采用改进的K-means算法对与光照信息无关的HS分量联合分割,获得完整道路信息,并采用Candy算子检测边缘及改进的Hough变化方法拟合导航路径。采用模糊控制方法通过实时调整转角和转向,对车体行走偏移进行矫正。同时,为满足不同农作物的施药需求,在喷药系统上选用了自整定模糊PID控制算法。【结果】该系统可有效适应不同光照条件,提取作物行中心线平均耗时12.36 ms,导航偏差不超过5 cm,植株叶片正面的上、中、下层覆盖率分别为63.26%、50.89%和75.82%,单位面积(1 cm2)雾滴数平均为55、42和78个。【结论】本系统可以满足温室移动机器人自主施药防治病虫害的需求。

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    【Objective】 To realize the automatic walk and uniform application of mobile robot in the greenhouse, a kind of spraying robot capable of navigating autonomously between crop lines was designed.【Method】 Aiming at the problem that the recognition of navigation path was greatly affected by light changes, HIS space was selected from the color images acquired by Kinect camera. The clustering center and number were optimized for K-means algorithm. Using the improved K-means algorithm,the components of H and S were segmented and the complete road information was obtained. The method of Candy operator was used to detect the edge,and the method of improved Hough change was used to fit the navigation path. The method of fuzzy control was used to correct robot walking offset by adjusting the rotating angle and turn in real time. A self-tuning fuzzy PID control algorithm was selected for this spraying system to meet application requirements of different crops.【Result】 The system could effectively adapt to different light conditions. On average, it took 12.36 ms to extract the center line of crop. The navigation deviation does not exceed 5 cm. The coverage rate of plant leaves on upper, middle and lower layers was 63.26%, 50.89% and 75.82% respectively, and the droplet number per square centimeter was 55, 42 and 78 respectively.【Conclusion】 This system can meet the need of pesticide application of mobile robot to prevent pests and diseases in greenhouse.

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白如月,汪小旵,鲁伟,李成光,Morice O. ODHIAMBO.施药机器人对行施药系统的设计与试验[J].华南农业大学学报,2018,39(5):101-109

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  • 收稿日期:2018-03-10
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  • 在线发布日期: 2018-07-18