Fin-A-Rays: Expanding Soft Gripper Compliance via Discrete Arrays of Flexible Structures

夹持器 模块化设计 方向(向量空间) 切片 对象(语法) 集合(抽象数据类型) 计算机科学 软机器人 巴(单位) 人工智能 工程类 机器人 机械工程 模拟 物理 数学 操作系统 气象学 程序设计语言 几何学
作者
Loong Yi Lee,Silvia Terrile,Saekwang Nam,Tingting Liang,Nathan F. Lepora,Jonathan Rossiter
出处
期刊:Soft robotics [Mary Ann Liebert, Inc.]
标识
DOI:10.1177/21695172251379600
摘要

Typical soft robot grippers use a small number of "fingers," often inspired by human hands, limiting adaptability to objects. One way to increase the number of digits in the end effector is through arrays of independent flexible structures, quantizing the gripper and increasing compliance. This work investigates what happens when we "slice" a Fin Ray soft gripper into an array of discrete fingers, called Fin-A-Rays. Fin-A-Rays are modular gripper systems that can be readily integrated into an off-the-shelf two-fingered parallel gripper. Here, between one and 24 Fin Ray fingers of width 2.5 mm to 60 mm are arranged side-by-side as a gripper. An analysis of the effects of finger width on gripper stiffness and object contact is presented via finite element analysis. The design space of Fin-A-Rays was studied via experiments and simulation, and a set of performance metrics for Fin-A-Rays was defined to understand the effects of "slicing" on grasping a set of objects. A design algorithm is also introduced to prearrange a Fin-A-Ray configuration based on an image of the object. The discretized compliance across an array of fingers in a Fin-A-Ray enables several novel behaviors during grasping, including finger splay and twisting. Results show that a balance between finger widths is required when slicing Fin-A-Rays, where algorithmically designed Fin-A-Rays showed higher average performance metrics than uniform configurations. Fin-A-Rays showed new capabilities, including multiobject grasping and in-hand manipulation. The passive morphological adaptability of Fin-A-Rays simplifies grasp planning, enabling delicate grasps for picking and packing complex shapes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
刚刚
phentjn发布了新的文献求助10
1秒前
xiaokezhang完成签到,获得积分20
1秒前
2秒前
2秒前
3秒前
3秒前
蛋子s发布了新的文献求助10
3秒前
4秒前
科研通AI6应助zhang采纳,获得30
4秒前
we发布了新的文献求助10
4秒前
4秒前
小志呀发布了新的文献求助10
4秒前
LeslieWK完成签到,获得积分10
5秒前
念念发布了新的文献求助10
5秒前
6秒前
6秒前
6秒前
johnson7777发布了新的文献求助10
6秒前
7秒前
leaolf应助zwy109采纳,获得10
7秒前
盛盛完成签到,获得积分20
7秒前
Hello应助科研通管家采纳,获得10
7秒前
顾矜应助科研通管家采纳,获得20
7秒前
隐形曼青应助科研通管家采纳,获得30
7秒前
Xinxxx应助科研通管家采纳,获得10
7秒前
CR7应助科研通管家采纳,获得20
7秒前
FashionBoy应助科研通管家采纳,获得10
7秒前
思源应助科研通管家采纳,获得10
8秒前
Xinxxx应助科研通管家采纳,获得10
8秒前
8秒前
Ustinian应助科研通管家采纳,获得10
8秒前
搜集达人应助科研通管家采纳,获得10
8秒前
ShenghuiH完成签到,获得积分10
8秒前
Dyson Hou应助科研通管家采纳,获得20
8秒前
酷波er应助科研通管家采纳,获得10
8秒前
Lucas应助科研通管家采纳,获得10
8秒前
今后应助科研通管家采纳,获得10
8秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Solid-Liquid Interfaces 600
Aircraft Engine Design, Third Edition 500
Neonatal and Pediatric ECMO Simulation Scenarios 500
苏州地下水中新污染物及其转化产物的非靶向筛查 500
Rapid Review of Electrodiagnostic and Neuromuscular Medicine: A Must-Have Reference for Neurologists and Physiatrists 500
Vertebrate Palaeontology, 5th Edition 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4747924
求助须知:如何正确求助?哪些是违规求助? 4094810
关于积分的说明 12669441
捐赠科研通 3807040
什么是DOI,文献DOI怎么找? 2101645
邀请新用户注册赠送积分活动 1126981
关于科研通互助平台的介绍 1003580