Evidence map›Paper›PMID 39409448›Full record

ArticleSensors (Basel, Switzerland)2024

Design and Experimental Test of Rope-Driven Force Sensing Flexible Gripper.

Zuhao Zhu, Yufei Liu, Jinyong Ju, En Lu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zuhao ZhuSchool of Artificial Intelligence, Anhui Polytechnic University, Wuhu 241000, China.ORCID 0009-0006-2511-8103
Yufei LiuSchool of Artificial Intelligence, Anhui Polytechnic University, Wuhu 241000, China.ORCID 0000-0002-3584-9931
Jinyong JuSchool of Artificial Intelligence, Anhui Polytechnic University, Wuhu 241000, China.ORCID 0000-0003-2713-7173
En LuSchool of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.ORCID 0000-0002-7194-6894

Funding

National Key Research and Development Program of China No.2022YFD00150402National Natural Science Foundation of China No.51805001University Natural Science Research Project of Anhui Province No.2023AH030018University Natural Science Research Project of Anhui Province No.2023AH050931
6 · The paper itself

Abstract

Robotic grasping is a common operation scenario in industry and agriculture, in which the force sensing function is a significant factor to achieve reliable grasping. Existing force sensing methods of flexible grippers require intelligent materials or force sensors embedded in the flexible gripper, which causes such problems of higher manufacturing requirements and contact surface properties changing. In this paper, a novel rope-driven force sensing flexible gripper is designed based on the fin-shaped gripper structure, which can realize the grasping sensing functions of contact nodes and contact forces without the need for force sensors. Firstly, the rope-driven force sensing flexible gripper is designed, including the driving unit, the transmission part, the gripper unit, and the force sensing unit. The force sensing unit and the gripper unit are connected by rope, and the prototype of the rope-driven force sensing flexible gripper is completed. Secondly, a force sensing algorithm and control system based on finite element method and grasping geometric relationship are designed to realize the rope-driven force sensing flexible gripper grasping control and sensor data acquisition and processing. Finally, the experimental system of the rope-driven force sensing flexible gripper is built, and the grasping experimental tests of objects with different diameters and different contact nodes are carried out to verify the force sensing function of the rope-driven force sensing flexible gripper. The force sensing flexible gripper designed in this paper can provide a new idea for the design and force sensing method of intelligent robotic grasping system in robotic teaching, scientific research, and industrial applications.

Indexed as

control systemexperimental testflexible gripperforce sensingrobotic grasping systemrope-driven

Identifiers

PMID39409448
PMCPMC11479328

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.