摘要
针对农业移动机器人视觉导航路径提取受光照影响大,实时性差的问题,提出了一种利用农作物行特征辅助进行的视觉导航方案,实现机器人的田间自主导航。选用单目相机获取农田的环境信息,首先针对农田光照不均的情况提出了YCr Cb亮度均衡法,然后针对实时性差的问题提出了OTSU(大津法)融合遗传退火算法的图像二值分割算法,并利用Hough直线变换检测,实现农田导航路径的快速提取。视觉导航实验结果表明,所提出的光照平衡算法较直方图均衡法实时性提升25.7%,优化后的OTSU法二值化速度提升了26.5%,在双边缺植情况下,导航线平均偏移量为2.3°,符合农田导航的实用性和实时性要求。
In order to solve the problem that the extraction of visual navigation path of agricultural mobile robot is greatly affected by light and has poor real-time performance, a visual navigation scheme assisted by crop row features is proposed to realize the robot’s autonomous navigation in the field. A monocular camera is selected to obtain the environmental information of farmland. First, YCrCb brightness equalization method is proposed for uneven illumination of farmland. Then, aiming at the problem of poor real-time performance,an image binary segmentation algorithm based on OTSU(Otsu method) and genetic annealing algorithm is proposed, and Hough line transformation detection is used to achieve rapid extraction of farmland navigation path. The visual navigation experiment results show that the real-time performance of the proposed light balance algorithm is improved by 25.7% compared with the histogram balancing method, the binarization speed of the optimized OTSU method is improved by 26.5%, In the case of bilateral lack of planting, the average deviation of the navigation line is 2.3 °, which conforms to the practicality and real-time of farmland navigation.
作者
刘义亭
吴清政
陆宇豪
李佩娟
LIU Yiting;WU Qingzheng;LU Yuhao;LI Peijuan(School of Automation,Nanjing Institute of Engineering,Nanjing 2111671,China;School of Information Science and Engineering,Southeast University,Nanjing 210096,China;Graduate School of Nanjing Institute of Engineering,Nanjing 211167,China)
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2022年第6期777-782,790,共7页
Journal of Chinese Inertial Technology
基金
国家自然科学基金青年基金(61903184)
江苏省自然科学基金青年基金(BK20181017,BK2019K186)
南京工程学院引进人才科研启动基金(YKJ201822)
中国博士后科学基金第67批面上项目(2020M671292)
江苏省博士后科研资助计划(B类)(2019K186)
2021年度省重点研发计划(产业前瞻与共性关键技术)(BE2021016-5)。
关键词
机器视觉
农业机器人
图像分割
遗传退火算法
Hough直线变换
machine vision
agricultural robot
image segmentation
genetic annealing algorithm
hough line transformation