摘要
托盘拾取是自动化仓储的重要环节之一,为提高叉车的托盘拾取能力,提出一种基于2-D激光雷达的托盘探测算法,实现托盘位置和姿态的识别。建立了托盘探测模型,确立了算法有效探测范围与激光点数量(分布于托盘支架正面)、托盘支架宽度和激光雷达分辨率的函数关系;通过改进的增量式直线提取算法,获取托盘姿态;根据托盘姿态,建立动态模板,以滑动窗口模式进行匹配,获取托盘位置。结果表明,有效探测范围,随激光点数量减小扩大,随托盘宽度增加而扩大,随分辨率增加而扩大;当激光扫描仪分辨率为0.33°,托盘支架宽度为90 mm时,实际探测范围符合托盘探测模型计算,x轴方向定位误差为±60 mm,y轴方向定位误差为±59 mm,托盘角度探测误差为±6°。本算法实现托盘位姿可靠识别,明确探测范围,为提高智能仓储装备拾取作业能力提供理论基础。
Pallet picking is one of the important links of automated warehousing. An algorithm was proposed for estimating the localization and angle of pallet with lake information,based on 2-D Lidar. It aims at improving the recognition pallet ability of forklift and the flexibility in automated warehousing. A detection model was built to define the geometry relationship between detection region the number of lidar point（ detecting the pallet foot）,the width of pallet foot and the resolution of Lidar. The algorithm extracted the lines as candidate pallet foot with the improved incremental algorithm and calculate the angle of pallet. Then the dynamic template was created and matched with sliding window,to calculated the position of the pallet. The result shows that the detect region was expend with smaller the threshold number of laser,longer the width of pallet foot and higher resolution of Lidar; the detect region met the result calculated based on the pallet detect model; error on x axis and y axis were ± 60 mm mm and ± 59 mm respectively; pallet angle error was. With the flexible pallet detecting algorithm,the requirement of localization of warehouse equipment and human was reduced and effect would be enhanced.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2017年第10期2469-2476,共8页
Chinese Journal of Scientific Instrument
基金
国家科技支撑计划课题(2015BAD18B0303)
现代农业产业技术体系建设专项资金(CARS-33-13)项目资助
