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Main Authors: Kanno, Ryo, Nguyen, Pham H., Pinskier, Joshua, Howard, David, Song, Sukho, Kovac, Mirko
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.06327
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author Kanno, Ryo
Nguyen, Pham H.
Pinskier, Joshua
Howard, David
Song, Sukho
Kovac, Mirko
author_facet Kanno, Ryo
Nguyen, Pham H.
Pinskier, Joshua
Howard, David
Song, Sukho
Kovac, Mirko
contents One of the trendsetting themes in soft robotics has been the goal of developing the ultimate universal soft robotic gripper. One that is capable of manipulating items of various shapes, sizes, thicknesses, textures, and weights. All the while still being lightweight and scalable in order to adapt to use cases. In this work, we report a soft gripper that enables delicate and precise grasps of fragile, deformable, and flexible objects but also excels in lifting heavy objects of up to 1617x its own body weight. The principle behind the soft gripper is based on extending the capabilities of electroadhesion soft grippers through the enhancement principles found in metamaterial adhesion cut and patterning. This design amplifies the adhesion and grasping payload in one direction while reducing the adhesion capabilities in the other direction. This counteracts the residual forces during peeling (a common problem with electroadhesive grippers), thus increasing its speed of release. In essence, we are able to tune the maximum strength and peeling speed, beyond the capabilities of previous electroadhesive grippers. We study the capabilities of the system through a wide range of experiments with single and multiple-fingered peel tests. We also demonstrate its modular and adaptive capabilities in the real-world with a two-finger gripper, by performing grasping tests of up to $5$ different multi-surfaced objects.
format Preprint
id arxiv_https___arxiv_org_abs_2403_06327
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Hybrid Soft Electrostatic Metamaterial Gripper for Multi-surface, Multi-object Adaptation
Kanno, Ryo
Nguyen, Pham H.
Pinskier, Joshua
Howard, David
Song, Sukho
Kovac, Mirko
Robotics
One of the trendsetting themes in soft robotics has been the goal of developing the ultimate universal soft robotic gripper. One that is capable of manipulating items of various shapes, sizes, thicknesses, textures, and weights. All the while still being lightweight and scalable in order to adapt to use cases. In this work, we report a soft gripper that enables delicate and precise grasps of fragile, deformable, and flexible objects but also excels in lifting heavy objects of up to 1617x its own body weight. The principle behind the soft gripper is based on extending the capabilities of electroadhesion soft grippers through the enhancement principles found in metamaterial adhesion cut and patterning. This design amplifies the adhesion and grasping payload in one direction while reducing the adhesion capabilities in the other direction. This counteracts the residual forces during peeling (a common problem with electroadhesive grippers), thus increasing its speed of release. In essence, we are able to tune the maximum strength and peeling speed, beyond the capabilities of previous electroadhesive grippers. We study the capabilities of the system through a wide range of experiments with single and multiple-fingered peel tests. We also demonstrate its modular and adaptive capabilities in the real-world with a two-finger gripper, by performing grasping tests of up to $5$ different multi-surfaced objects.
title Hybrid Soft Electrostatic Metamaterial Gripper for Multi-surface, Multi-object Adaptation
topic Robotics
url https://arxiv.org/abs/2403.06327