A Nonlinear Finite Element Analysis of a Tapered Soft Actuator for Improved Bending Performance in Soft Robotics

Clicks: 2
ID: 313211
2023
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #681 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Compared to hard robots, soft robots, often referred to as nature-inspired robots, offer a safer approach to interact with delicate goods like agricultural and food products. This study sug- gests a novel soft actuator design that takes inspiration from a soft pneumatic actuator with a rec- tangular shape including a row of channels. The actuator is tapered to optimise its bending angle and decrease energy losses caused by its form. Due to their nonlinearities varying geometries, soft actuators are challenging to model, and the Finite Element Method should be used to deal with these problems. This research paper proposes a finite element analysis–based deformation model. In or- der to forecast the impact of boundary conditions and support the behaviour of large deformable materials utilised in soft robotic gripper applications. This paper presents a finite element analysis- based deformation model to predict the effect of boundary conditions and supports the behavior of large deformable materials used in soft robotic gripper applications. Future research in this field can be developed on the findings of this area.
Reference Key
imported_1777059810_69ebc7e28aeec Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sheeraz Ahmed
Journal Journal of Computing & Biomedical Informatics
Year 2023
DOI
DOI not found
URL
https://jcbi.org/index.php/Main/article/view/174
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.