首页> 外文会议>AOMATT 2010;International symposium on advanced optical manufacturing and testing technologies >3-D Location of Tomato Based on Binocular Stereo Vision for Tomato Harvesting Robot
【24h】

3-D Location of Tomato Based on Binocular Stereo Vision for Tomato Harvesting Robot

机译:基于双目立体视觉的番茄收获机器人3-D定位

获取原文
获取外文期刊封面目录资料

摘要

Accurate harvesting depends on the order of the accuracy of 3-D location for harvesting robot. The precision of location is lower when the distance between fruit and camera is larger than 0.8 m for the method based on binocular stereo vision. This is a big problem. In order to improve the precision of depth measurement for ripe tomato, two stereo matching methods were analyzed comparatively which were centroid-based matching and area-based matching. Their performances in depth measurement were also compared. Experiments showed that the relationship between distance and measurement was linear. Then, models of unitary linear regression (ULR) were used to improve the results of depth measurement. After correction by these models, the depth errors were in a range of -28 mm to 25 mm for centroid-based matching method and -8 mm to 15 mm for area-based matching method at a distance of 0.6 m to 1.15 m. It can be concluded that costs of computation can be decreased with the promise of good precision when the parallax of centroid which is acquired through centroid-based matching method is used to set the range of parallax for area-based matching method.
机译:准确的收获取决于收获机器人的3D定位精度的顺序。对于基于双目立体视觉的方法,当水果与相机之间的距离大于0.8 m时,定位精度会降低。这是个大问题。为了提高成熟番茄深度测量的精度,比较分析了两种立体匹配方法,分别是基于质心的匹配和基于面积的匹配。还比较了他们在深度测量中的性能。实验表明,距离与测量之间的关系是线性的。然后,使用of线性回归(ULR)模型来改善深度测量的结果。通过这些模型进行校正后,基于质心的匹配方法的深度误差在-28 mm至25 mm的范围内,而基于面积的匹配方法的深度误差在0.6 m至1.15 m的范围内在-8 mm至15 mm的范围内。可以得出结论,将基于质心的匹配方法获取的质心视差用于基于面积的匹配方法设置视差范围时,可以降低计算成本,并具有较高的精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号