Strain-based Modeling of Rod-driven Soft Continuum Robots with Co-located Embedded Sensors

Rod-driven soft robots (RDSR) with a well-balanced performance in terms of perception, precision, and intelligence have a great potential for application. Mathematical description and predicted sensing of deformable soft bodies are crucial to achieve controllable and intelligent behaviors of these robots. In this work, we propose a kinetostatic model for RDSR embedded with co-located sensors based on the Geometric Variable Strain (GVS) approach where local deformations, actuation lengths and external interactions are included. This approach allows us to estimate the shape of RDSR and predict the strain variation of soft bodies under internal and external interactions. Simulations and experimental results show that tip position errors are not greater than 1.8% with respect to the whole body length under different loads (0, 100, 200, 300 gf). The maximum error of predicted sensor length change is up to 2 mm and its percentage relative to the actual length does not exceed 4%. The results demonstrate the accuracy and effectiveness of the proposed model.

Authors

Institutions

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801729
Citations
2
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.37

Funders

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

Strain-based Modeling of Rod-driven Soft Continuum Robots with Co-located Embedded Sensors

Daniel Feliu-Talegón, Federico Renda, Cecilia Laschi, Peiyi Wang et al.
2 citations
Soft Robotics and Applications
0.37
article

Strain-based Modeling of Rod-driven Soft Continuum Robots with Co-located Embedded Sensors

Daniel Feliu-Talegón, Federico Renda, Cecilia Laschi, Peiyi Wang, Sheng Guo
article en
2 citations

Abstract

Rod-driven soft robots (RDSR) with a well-balanced performance in terms of perception, precision, and intelligence have a great potential for application. Mathematical description and predicted sensing of deformable soft bodies are crucial to achieve controllable and intelligent behaviors of these robots. In this work, we propose a kinetostatic model for RDSR embedded with co-located sensors based on the Geometric Variable Strain (GVS) approach where local deformations, actuation lengths and external interactions are included. This approach allows us to estimate the shape of RDSR and predict the strain variation of soft bodies under internal and external interactions. Simulations and experimental results show that tip position errors are not greater than 1.8% with respect to the whole body length under different loads (0, 100, 200, 300 gf). The maximum error of predicted sensor length change is up to 2 mm and its percentage relative to the actual length does not exceed 4%. The results demonstrate the accuracy and effectiveness of the proposed model.

National University of Singapore (SG), Khalifa University of Science and Technology (AE), Beijing Jiaotong University (CN)
Ministry of Education, National Natural Science Foundation of China, Office of Naval Research
Openalex Percentile: Top 41%
Soft Robotics and Applications
0.37
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.

Strain-based Modeling of Rod-driven Soft Continuum Robots with Co-located Embedded Sensors — Daniel Feliu-Talegón, Federico Renda, et al. · (2024) | TGRS Research Map | TGRS