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アマガエルの濡れた付着メカニズムの解明と、そのソフトロボットハンド開発への応用

树蛙湿粘附机制的阐明及其在软体机器人手开发中的应用

基本信息

批准号：
20J14910
负责人：
NGUYEN VANPHO
金额：
$ 1.09万
依托单位：
Japan Advanced Institute of Science and Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for JSPS Fellows
财政年份：
2020
资助国家：
日本
起止时间：
2020-04-24 至 2022-03-31
项目状态：
已结题

项目摘要

Role of the micropatterned pad (m-pad) on increasing the wet adhesion in grasping soft-fragile objects was continuously exploited through a theoretical model validated by applications of manipulating food by a robotic hand.We built a theoretical model to estimate decreasing squeeze force and increasing wet adhesion force concerned for manipulating a soft, wet object by two soft fingers in two cases: normal fingertip pad (n-pad) and the m-pad. Object was in two cases of environment: in-air and in-liquid; whereas the pad was dry. Grasping the object was conducted three steps by the pad: approach, attach to the object and detach from the object. The m-pad has 14400 square cells is with the size of 85×85μm, separated by the channels with 44μm in depth. Our estimation of the grasped force for the pads were conducted, then verified by actual application in griping konjac, tofu, jelly, coffee jelly and quail egg. Both estimated and experimental results reveal that the m-pad can achieve a higher decrement of the squeeze force and deformation on the grasped objects than that of the n-pad. The ability of the wet adhesion in such model was further investigated for different morphologies of the m-pad. In this scenario, we varied the width of the pattern channel in three levels: 7.5 (type-1), 15 (type-2) and 22.5μm (type-3), and then applied to grasping the food objects. Varying w in the m-pad affects grasping ability of robotic fingers. Thus, we can optimize w according to grasped object in different conditions.

通过机器人手操作食物的应用验证的理论模型，不断探索微图案垫（m-pad）在抓取软易碎物体时增加湿粘附力的作用。我们建立了一个理论模型，以估计两个柔软手指在两种情况下操作软湿物体时所涉及的减少挤压力和增加湿粘附力：普通指尖焊盘（n焊盘）和m焊盘。对象是在两种情况下的环境：在空气中和在液体中，而垫是干燥的。通过垫进行三个步骤抓持物体：接近、附接到物体和从物体分离。m-pad具有14400个正方形单元，尺寸为85×85μm，由深度为44μm的通道分隔。对吸盘的抓持力进行了估算，并通过实际应用对豆腐、豆腐、果冻、咖啡果冻和鹌鹑蛋的抓持进行了验证。实验结果表明，与n型垫相比，m型垫能更好地减小被抓取物体的挤压力和变形。在这种模型中的湿粘附的能力，进一步研究了不同形态的m-pad。在这种情况下，我们改变了三个级别的模式通道的宽度：7.5（类型-1），15（类型-2）和22.5μm（类型-3），然后应用于抓取食物对象。改变m垫中的w影响机器人手指的抓取能力。因此，我们可以在不同的条件下，根据抓取对象优化w。