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
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
批准号:
20J14910
负责人:
NGUYEN VANPHO
金额:
$1.09万
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
项目状态:
已结题
起止时间:
2020-04-24 至 2022-03-31
中文摘要
通过一个理论模型,通过机械手操作食物的应用验证了微图案垫(m-pad)在增加抓取软易碎性物体时的湿附着力方面的作用。我们建立了一个理论模型来估计两个柔软的手指在正常指尖垫(n-pad)和m-pad两种情况下操作柔软潮湿物体所涉及的减少挤压力和增加湿附着力。对象处于两种环境中:空气和液体;而垫子是干的。通过垫片对物体进行接近、附着和脱离三个步骤的抓取。m-pad有14400个方形单元,尺寸为85×85μm,由深度为44μm的通道分隔。通过对抓握魔芋、豆腐、果冻、咖啡果冻、鹌鹑蛋的实际应用验证了抓握力的正确性。估算和实验结果表明,与n-pad相比,m-pad对被抓物体的挤压力和变形的减量更大。在m-pad的不同形态下,进一步研究了该模型的湿粘附能力。在这个场景中,我们将图案通道的宽度分为7.5 μm(类型1)、15 μm(类型2)和22.5μm(类型3)三个级别,然后应用于抓取食物物体。m-pad中w的变化会影响机器人手指的抓取能力。因此,我们可以根据不同条件下抓取的对象来优化w。
英文摘要
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.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
“Interdisciplinary Collaborative Case-studies” and “Futuristic Demo Presentations” in IEEE ICRA2020 Workshop “Beyond Soft Robotics”
IEEE ICRA2020 研讨会“Beyond Soft Robotics”中的“跨学科协作案例研究”和“未来派演示演示”
DOI:
--
发表时间:
2020
期刊:
影响因子:
--
作者:
[]
通讯作者:
Toward An Ontology Model Supporting Vision-Based Tactile Internet Interoperability
建立支持基于视觉的触觉互联网互操作性的本体模型
DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
[Pho Van Nguyen, Van Cu Pham, Yasuo Tan, Van Anh Ho]
通讯作者:
Van Anh Ho
DOI:
10.1109/lra.2021.3067277
发表时间:
2021-07-01
期刊:
IEEE ROBOTICS AND AUTOMATION LETTERS
影响因子:
5.2
作者:
[Nguyen, Van Pho, Ho, Van Anh]
通讯作者:
Ho, Van Anh