当前位置: X-MOL 学术Philosophies › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Two Experimental Devices for Record and Playback of Tactile Data
Philosophies ( IF 0.6 ) Pub Date : 2021-06-30 , DOI: 10.3390/philosophies6030054
Masahiro Ohka , Hiraku Komura , Keisuke Watanabe , Ryota Nomura

A tactile record and playback system will progress tactileology—a new cross-disciplinary field related to tactile sensations—as it will enhance its use in the instruction, archiving, and analysis of human manipulation. In this paper, we describe two key devices for achieving tactileology: a tactile sensor capturing human tactile sense (fingernail color sensor) and a robotic tactile sensor, both of which can detect not only normal force but also tangential force. This is beneficial because people manipulate objects and tools in various ways, such as grasping, picking, and rubbing. The fingernail color sensor registers the three-dimensional (3D) force applied to a fingertip by detecting the fingernail color change caused by blood distribution under the fingernail, which can be observed with green illumination and a miniature camera. Since detecting this color change is more complicated than using a robotic sensor, the relationships between the image and 3D force are learned using a convolutional neural network (CNN). In the robotic sensor, the 3D force applied to a robotic finger transforms into a bright area using an illuminated acrylic core, a rubber robotic finger skin, and a miniature camera. We measure normal force and tangential force by the brightness and movement of the bright area, respectively. Using a force gauge or an electronic scale for measurement, we perform a series of evaluation experiments. The experimental results show that the precision of both the fingernail color sensor and the robotic tactile sensor are sufficient for our system.

中文翻译:

两种触觉数据记录和回放实验装置

触觉记录和回放系统会进步tactileology——与触觉相关的一个新的跨学科领域——因为它将加强其在人类操作的指导、存档和分析中的使用。在本文中,我们描述了实现触觉学的两个关键设备:捕捉人类触觉的触觉传感器(指甲颜色传感器)和机器人触觉传感器,它们不仅可以检测法向力,还可以检测切向力。这是有益的,因为人们以各种方式操纵物体和工具,例如抓握、拾取和摩擦。指甲颜色传感器通过检测指甲下血液分布引起的指甲颜色变化来记录施加到指尖的三维 (3D) 力,这可以通过绿色照明和微型相机进行观察。由于检测这种颜色变化比使用机器人传感器更复杂,因此使用卷积神经网络 (CNN) 学习图像和 3D 力之间的关系。在机器人传感器中,施加在机器人手指上的 3D 力使用发光的亚克力芯、橡胶机器人手指皮肤和微型相机转变为明亮区域。我们分别通过明亮区域的亮度和运动来测量法向力和切向力。使用测力计或电子秤进行测量,我们进行了一系列评估实验。实验结果表明,指甲颜色传感器和机器人触觉传感器的精度对于我们的系统来说是足够的。在机器人传感器中,施加在机器人手指上的 3D 力使用发光的亚克力芯、橡胶机器人手指皮肤和微型相机转变为明亮区域。我们分别通过明亮区域的亮度和运动来测量法向力和切向力。使用测力计或电子秤进行测量,我们进行了一系列评估实验。实验结果表明,指甲颜色传感器和机器人触觉传感器的精度对于我们的系统来说是足够的。在机器人传感器中,施加在机器人手指上的 3D 力使用发光的亚克力芯、橡胶机器人手指皮肤和微型相机转变为明亮区域。我们分别通过明亮区域的亮度和运动来测量法向力和切向力。使用测力计或电子秤进行测量,我们进行了一系列评估实验。实验结果表明,指甲颜色传感器和机器人触觉传感器的精度对于我们的系统来说是足够的。使用测力计或电子秤进行测量,我们进行了一系列评估实验。实验结果表明,指甲颜色传感器和机器人触觉传感器的精度对于我们的系统来说是足够的。使用测力计或电子秤进行测量,我们进行了一系列评估实验。实验结果表明,指甲颜色传感器和机器人触觉传感器的精度对于我们的系统来说是足够的。
更新日期:2021-06-30
down
wechat
bug