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A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Standard

A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization. / Schiller, Lars; Seibel, Arthur; Schlattmann, Josef.
in: IEEE Robotics and Automation Letters, Jahrgang 5, Nr. 2, 8957491, 01.04.2020, S. 1199-1206.

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet

Harvard

Schiller, L, Seibel, A & Schlattmann, J 2020, 'A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization', IEEE Robotics and Automation Letters, Jg. 5, Nr. 2, 8957491, S. 1199-1206. https://doi.org/10.1109/LRA.2020.2966396

APA

Schiller, L., Seibel, A., & Schlattmann, J. (2020). A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization. IEEE Robotics and Automation Letters, 5(2), 1199-1206. Artikel 8957491. https://doi.org/10.1109/LRA.2020.2966396

Vancouver

Schiller L, Seibel A, Schlattmann J. A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization. IEEE Robotics and Automation Letters. 2020 Apr 1;5(2):1199-1206. 8957491. doi: 10.1109/LRA.2020.2966396

Bibtex

@article{5e55a7b49be948b9965c1ef42986e056,
title = "A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization",
abstract = "This letter extends the piecewise constant curvature modeling approach by energy minimization techniques in order to simulate contact with the environment. The new method enables a fast and sufficiently good estimation of the forward kinematics for soft structures whose behavior is mainly determined by boundary conditions. This enables to predict the configuration of such structures for a given reference input, which is demonstrated on a gecko-inspired soft robot. The newly gained simulation capability is then used to find new patterns for straight as well as curved trotting gait. The existing gait pattern for straight gait could be improved by a factor of 1.4, and a new gait pattern for the rotation on the spot could be discovered.",
keywords = "and learning for soft robots, control, Modeling, motion control, soft robot applications, Engineering",
author = "Lars Schiller and Arthur Seibel and Josef Schlattmann",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.",
year = "2020",
month = apr,
day = "1",
doi = "10.1109/LRA.2020.2966396",
language = "English",
volume = "5",
pages = "1199--1206",
journal = "IEEE Robotics and Automation Letters",
issn = "2377-3766",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "2",

}

RIS

TY - JOUR

T1 - A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization

AU - Schiller, Lars

AU - Seibel, Arthur

AU - Schlattmann, Josef

N1 - Publisher Copyright: © 2016 IEEE.

PY - 2020/4/1

Y1 - 2020/4/1

N2 - This letter extends the piecewise constant curvature modeling approach by energy minimization techniques in order to simulate contact with the environment. The new method enables a fast and sufficiently good estimation of the forward kinematics for soft structures whose behavior is mainly determined by boundary conditions. This enables to predict the configuration of such structures for a given reference input, which is demonstrated on a gecko-inspired soft robot. The newly gained simulation capability is then used to find new patterns for straight as well as curved trotting gait. The existing gait pattern for straight gait could be improved by a factor of 1.4, and a new gait pattern for the rotation on the spot could be discovered.

AB - This letter extends the piecewise constant curvature modeling approach by energy minimization techniques in order to simulate contact with the environment. The new method enables a fast and sufficiently good estimation of the forward kinematics for soft structures whose behavior is mainly determined by boundary conditions. This enables to predict the configuration of such structures for a given reference input, which is demonstrated on a gecko-inspired soft robot. The newly gained simulation capability is then used to find new patterns for straight as well as curved trotting gait. The existing gait pattern for straight gait could be improved by a factor of 1.4, and a new gait pattern for the rotation on the spot could be discovered.

KW - and learning for soft robots

KW - control

KW - Modeling

KW - motion control

KW - soft robot applications

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85079282409&partnerID=8YFLogxK

U2 - 10.1109/LRA.2020.2966396

DO - 10.1109/LRA.2020.2966396

M3 - Journal articles

AN - SCOPUS:85079282409

VL - 5

SP - 1199

EP - 1206

JO - IEEE Robotics and Automation Letters

JF - IEEE Robotics and Automation Letters

SN - 2377-3766

IS - 2

M1 - 8957491

ER -

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DOI

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