Curvature Sensing and Control of Soft Continuum Robots Using e-Textile Sensors

Soft continuum robots, with their flexible and deformable structures, excel in tasks requiring delicate manipulation and navigation through complex environments. Accurate shape sensing is vital to enhance their performance, safety, and adaptability. Unlike rigid sensors, soft sensors conform to the robot’s flexible surfaces, ensuring consistent measurement of shape and motion. This paper introduces a new approach using soft e-textile resistive sensors, which integrate seamlessly with the robot’s structure. These sensors adjust their resistance in response to movements, capturing multidimensional force data. A deep Convolutional Neural Network (CNN) decodes the sensor signals, enabling precise shape estimation and control. Our findings indicate that soft e-textile sensors may surpass traditional rigid sensors in shape sensing and control, significantly improving the functionality of soft continuum robots in challenging applications.

Authors

Institutions

Publication Details

Journal
Applied System Innovation
Published
2024-09-13
DOI
https://doi.org/10.3390/asi7050084
Citations
4
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Curvature Sensing and Control of Soft Continuum Robots Using e-Textile Sensors

Haitham El-Hussieny, Ayman A. Nada, Ibrahim A. Hameed, Eric Vincent Galeta
4 citations
Applied System Innovation
Soft Robotics and Applications
0.74
article

Curvature Sensing and Control of Soft Continuum Robots Using e-Textile Sensors

Haitham El-Hussieny, Ayman A. Nada, Ibrahim A. Hameed, Eric Vincent Galeta
article en
4 citations

Abstract

Soft continuum robots, with their flexible and deformable structures, excel in tasks requiring delicate manipulation and navigation through complex environments. Accurate shape sensing is vital to enhance their performance, safety, and adaptability. Unlike rigid sensors, soft sensors conform to the robot’s flexible surfaces, ensuring consistent measurement of shape and motion. This paper introduces a new approach using soft e-textile resistive sensors, which integrate seamlessly with the robot’s structure. These sensors adjust their resistance in response to movements, capturing multidimensional force data. A deep Convolutional Neural Network (CNN) decodes the sensor signals, enabling precise shape estimation and control. Our findings indicate that soft e-textile sensors may surpass traditional rigid sensors in shape sensing and control, significantly improving the functionality of soft continuum robots in challenging applications.

Applied System InnovationVol. 7(5)
Norwegian University of Science and Technology (NO), Egypt-Japan University of Science and Technology (EG)
Openalex Percentile: Top 32%
Soft Robotics and Applications
0.74
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.

Curvature Sensing and Control of Soft Continuum Robots Using e-Textile Sensors — Haitham El-Hussieny, Ayman A. Nada, et al. · Applied System Innovation (2024) | TGRS Research Map | TGRS