Design and Optimization of the Bionic Flexible Gripper Based on Magnetically Sensitive Rubber

Flexible grippers based on magnetically sensitive rubber have garnered significant research attention due to their high gripping adaptability and ease of control. However, current research designs often separate the excitation device from the flexible finger, which can lead to potential interference or damage to other electronic components in the working environment and an inability to simultaneously ensure safety and gripping performance. In this paper, we propose an integrated magnetically controlled bionic flexible gripper that combines the excitation device and the flexible finger. We derive a formula for calculating the magnetic field generated by the excitation device, model and simulate the device, and find that the optimal magnetic field effect is achieved when the core-to-coil size ratio is 1:5. Additionally, we fabricated flexible fingers with different NdFeB volume ratios and experimentally determined that a volume ratio of 20% yields relatively better bending performance. The integrated magnetically controlled bionic flexible gripper described in this paper can adaptively grasp items such as rubber, column foam, and electrical tape, achieving maximum grasping energy efficiency of 0.524 g per millitesla (g/mT). These results highlight its potential advantages in applications such as robotic end-effectors and industrial automatic sorting.

Authors

Institutions

Publication Details

Journal
Actuators
Published
2025-03-05
DOI
https://doi.org/10.3390/act14030124
Citations
3
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
2.02

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Optimization of the Bionic Flexible Gripper Based on Magnetically Sensitive Rubber

Mengjie Shou, Xiaoxu Bian, Pingan Yang, Rui Li et al.
3 citations
Actuators
Soft Robotics and Applications
2.02
article

Design and Optimization of the Bionic Flexible Gripper Based on Magnetically Sensitive Rubber

Mengjie Shou, Xiaoxu Bian, Pingan Yang, Rui Li, Yu Ding
article en
3 citations

Abstract

Flexible grippers based on magnetically sensitive rubber have garnered significant research attention due to their high gripping adaptability and ease of control. However, current research designs often separate the excitation device from the flexible finger, which can lead to potential interference or damage to other electronic components in the working environment and an inability to simultaneously ensure safety and gripping performance. In this paper, we propose an integrated magnetically controlled bionic flexible gripper that combines the excitation device and the flexible finger. We derive a formula for calculating the magnetic field generated by the excitation device, model and simulate the device, and find that the optimal magnetic field effect is achieved when the core-to-coil size ratio is 1:5. Additionally, we fabricated flexible fingers with different NdFeB volume ratios and experimentally determined that a volume ratio of 20% yields relatively better bending performance. The integrated magnetically controlled bionic flexible gripper described in this paper can adaptively grasp items such as rubber, column foam, and electrical tape, achieving maximum grasping energy efficiency of 0.524 g per millitesla (g/mT). These results highlight its potential advantages in applications such as robotic end-effectors and industrial automatic sorting.

ActuatorsVol. 14(3)
Chongqing University of Posts and Telecommunications (CN)
Natural Science Foundation of Chongqing
Openalex Percentile: Top 15%
Soft Robotics and Applications
2.02
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.