Physical edge detection in clothing items for robotic manipulation
Physical edge detection in clothing items for robotic manipulation
复制标题
用于机器人操作的服装中的物理边缘检测
DOI：
10.1109/icar.2017.8023660
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Antonio Gabas and Yasuyo Kita
中科院分区：
文献类型：
--
作者：
Yasuyo Kita;Yousuke Goi and Yoshihiro Kawai;Antonio Gabas and Yasuyo Kita
物体的物理边缘包含有价值的信息，可以识别其形状并对其进行操作。在自动处理服装物品的情况下，物理边缘为确定其类型和形状以及为许多操作任务找到良好的抓取点提供了重要线索。在本文中，我们提出了一种从服装的三维观察中提取服装物理边缘的方法。首先计算深度边缘作为候选像素，然后使用深度卷积神经网络对边缘进行像素分类。用不同大小、不同柔软度的毛巾进行实验，结果表明该方法具有较好的鲁棒性。为了证明这种检测到的物理边缘信息的有效性，我们还进行了用双臂机器人打开毛巾的实验。
The physical edges of an object contain valuable information to recognize its shape and also to manipulate it. In the case of handling clothing items automatically, the physical edges give important clues to determine its type and shape as well as to find good grasping points for many manipulation tasks. In this paper, we propose a method to extract the garment's physical edges from the three-dimensional observation of the garment. First, we calculate depth edges as candidate pixels, and then use a Deep Convolutional Neural Network for pixel-wise classification of the edges. Experimental results obtained by using various towels of different sizes and softness show the robustness of this method. To demonstrate the usefulness of this detected physical edge information, we also conducted experiments of opening towels with a dual-arm robot.