基于改进遗传算法与机器视觉的工业机器人猪腹剖切轨迹规划
发布时间：2018-11-11 11:43
【摘要】：以猪肉生产线为研究背景,对猪腹剖切工位的自动化改造进行了研究.自动化剖切系统的组成包括6自由度工业机器人、定制工具、PC、摄像机以及悬挂支架等.通过对工业机器人工具坐标系、用户坐标系以及摄像机的标定,建立起"手-目标-眼"之间的空间位姿关系.特征识别算法可以将猪腹轮廓曲线从图像中提取出来并用五次样条曲线对其进行拟合.结合猪腹膜腔生物特征和改进的遗传算法(GA)对样条曲线进行分段轨迹规划.最终将轨迹规划结果按照空间位姿关系转换到笛卡儿空间进行编程.实验目的是利用所推荐的方法高效地将猪腹剖开且不损坏脏腹膜,便于酮体与内脏的后续处理.实验结果表明,工业机器人猪腹剖切方法在切割质量与效率上超越了手工切割,可以满足猪肉生产线要求.
[Abstract]:Based on the research background of pork production line, the automatic transformation of porcine abdominal cutting position was studied. The automatic cutting system consists of 6 DOF industrial robot, custom tool, PC, camera and suspension support. By calibrating the tool coordinate system, the user coordinate system and the camera of the industrial robot, the spatial position and pose relationship between the hand, the target and the eye is established. The feature recognition algorithm can extract the porcine abdominal contour curve from the image and fit it with the quintic spline curve. Combined with pig peritoneal cavity biometrics and improved genetic algorithm (GA), the spline curve was segmented trajectory planning. Finally, the trajectory planning results are converted to Cartesian space according to the spatial position and pose relationship. The aim of the experiment is to dissect the pig abdomen efficiently without damaging the viscera, and to facilitate the subsequent treatment of ketone body and viscera. The experimental results show that the cutting quality and efficiency of the industrial robot pig belly cutting method is higher than that of manual cutting method, which can meet the requirements of pork production line.
【作者单位】： 大连理工大学机械工程学院;
【基金】：辽宁省科技创新重大专项(2015106011)
【分类号】：TP18;TP242.2;TP391.41
[Abstract]:Based on the research background of pork production line, the automatic transformation of porcine abdominal cutting position was studied. The automatic cutting system consists of 6 DOF industrial robot, custom tool, PC, camera and suspension support. By calibrating the tool coordinate system, the user coordinate system and the camera of the industrial robot, the spatial position and pose relationship between the hand, the target and the eye is established. The feature recognition algorithm can extract the porcine abdominal contour curve from the image and fit it with the quintic spline curve. Combined with pig peritoneal cavity biometrics and improved genetic algorithm (GA), the spline curve was segmented trajectory planning. Finally, the trajectory planning results are converted to Cartesian space according to the spatial position and pose relationship. The aim of the experiment is to dissect the pig abdomen efficiently without damaging the viscera, and to facilitate the subsequent treatment of ketone body and viscera. The experimental results show that the cutting quality and efficiency of the industrial robot pig belly cutting method is higher than that of manual cutting method, which can meet the requirements of pork production line.
【作者单位】： 大连理工大学机械工程学院;
【基金】：辽宁省科技创新重大专项(2015106011)
【分类号】：TP18;TP242.2;TP391.41
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