农业工程2026，Vol.16Issue(7)：34-40,7.DOI:10.19998/j.cnki.2095-1795.202605005
基于双通道感知与卡尔曼平滑的覆膜田垄导航检测
Navigation line detection in plastic-covered planting ridges based on dual-channel perception and kalman smoothing
摘要
Abstract
To address instability in navigation path recognition in potato plastic-covered planting environments,caused by strong plastic mulch film reflection,complex variations in natural illumination,and vibrations from machinery operations,a navigation line detection method has been proposed that integrated depth information with color image features.This method combined with Kalman filtering to achieve temporal smoothing of path parameters.This method first established a dual-channel(depth-color)parallel recognition frame-work.Depth image was restored by filling gaps using linear interpolation,and depth information was transformed into height distribu-tion features.Geometric centers of ridges were then extracted using a row-wise regional adaptive threshold segmentation method.Color channel,an adaptive brightness normalization and color feature enhancement algorithm was developed to address complex field illumina-tion conditions,including strong sunlight,backlighting,and cloudy conditions.This algorithm performed feature suppression,en-hancement,and fusion within HSI color space to accurately obtain plastic mulch texture center.Subsequently,an initial navigation line was obtained based on a decision-level fusion strategy,and a Kalman filtering was introduced to predict and correct navigation line para-meters across consecutive frames,thereby reducing path angle fluctuations caused by machine vibration and image noise.Field experi-ments have shown that under cloudy,sunny front-light,and sunny backlight conditions,recognition success rates of depth image meth-od were 100%,95.5%,and 98.5%,respectively,while those of color image method were 99.5%,93.5%,and 96.0%,respectively.After dual-channel fusion,navigation line recognition success rate remained stable at over 97%under all working conditions.Kalman filtering reduced standard deviation of navigation angle deviation by 57.1%and the maximum angular jump by 74.1%.Overall method achieved navigation path angle deviation of less than 1°,with a single-frame processing time of less than 0.30 s,thereby meeting re-quirements for navigation accuracy,operational stability,and real-time performance of potato automatic seedling-releasing machine.An effective approach for visual navigation of agricultural equipment was provided for plastic-covered planting scenarios.关键词
马铃薯/视觉导航系统/图像处理/卡尔曼滤波/光照自适应增强/导航线提取/覆膜种植Key words
potatoes/visual navigation system/image processing/Kalman filtering/adaptive illumination enhancement/navigation line extraction/plastic-covered planting分类
农业科技引用本文复制引用
庞树杰,马壮红,马梦良,蒋厚康,刘继展,陈雨,张硕,张军昌..基于双通道感知与卡尔曼平滑的覆膜田垄导航检测[J].农业工程,2026,16(7):34-40,7.基金项目
榆林市科技计划项目(2024-GY-231) （2024-GY-231）
