Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/32551
Title: A Model-Based Sensor Fusion Approach for Force and Shape Estimation in Soft Robotics
Authors: Navarro, Stefan Escaida
NAGELS, Steven 
Alagi, Hosam
Faller, Lisa-Marie
Goury, Olivier
Morales-Bieze, Thor
Zangl, Hubert
Hein, Bjoern
RAMAKERS, Raf 
DEFERME, Wim 
Zheng, Gang
Duriez, Christian
Issue Date: 2020
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Source: IEEE ROBOTICS AND AUTOMATION LETTERS, 5 (4) , p. 5621 -5628
Abstract: In this letter, we address the challenge of sensor fusion in Soft Robotics for estimating forces and deformations. In the context of intrinsic sensing, we propose the use of soft capacitive sensing to find a contact's location, and the use of pneumatic sensing to estimate the force intensity and the deformation. Using a FEM-based numerical approach, we integrate both sensing streams and model two Soft Robotics devices we have conceived. These devices are a Soft Pad and a Soft Finger. We show in an evaluation that external forces on the Soft Pad can be estimated and that the shape of the Soft Finger can be reconstructed.
Notes: Navarro, SE (corresponding author), Inria Lille Nord Europe, DEFROST, F-59650 Villeneuve Dascq, France.; Navarro, SE (corresponding author), CRIStAL Ctr Rech Informat Signal & Automat Lille, F-59650 Villeneuve Dascq, France.
stefan.escaida-navarro@inria.fr; steven.nagels@uhasselt.be;
hosam.alagi@kit.edu; l.faller@fh-kaernten.at; olivier.goury@inria.fr;
thorbieze@gmail.com; hubert.zangl@tugraz.at; hein@ira.uka.de;
raf.ramakers@uhasselt.be; wim.deferme@uhasselt.be; gang.zheng@inria.fr;
christian.duriez@inria.fr
Other: Navarro, SE (corresponding author), Inria Lille Nord Europe, DEFROST, F-59650 Villeneuve Dascq, France, CRIStAL Ctr Rech Informat Signal & Automat Lille, F-59650 Villeneuve Dascq, France. stefan.escaida-navarro@inria.fr; steven.nagels@uhasselt.be; hosam.alagi@kit.edu; l.faller@fh-kaernten.at; olivier.goury@inria.fr; thorbieze@gmail.com; hubert.zangl@tugraz.at; hein@ira.uka.de; raf.ramakers@uhasselt.be; wim.deferme@uhasselt.be; gang.zheng@inria.fr; christian.duriez@inria.fr
Keywords: Modeling;control;and learning for soft robots;soft sensors and actuators;soft robot materials and design;force and tactile sensing
Document URI: http://hdl.handle.net/1942/32551
ISSN: 2377-3766
e-ISSN: 2377-3766
DOI: 10.1109/LRA.2020.3008120
ISI #: WOS:000552945200005
Rights: © Copyright 2020 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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