Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 7176-7182 |
| Seitenumfang | 7 |
| ISBN (elektronisch) | 978-1-7281-4004-9 |
| ISBN (Print) | 978-1-7281-4005-6 |
| Publikationsstatus | Veröffentlicht - Nov. 2019 |
| Veranstaltung | 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China Dauer: 3 Nov. 2019 → 8 Nov. 2019 |
Publikationsreihe
| Name | IEEE International Conference on Intelligent Robots and Systems |
|---|---|
| ISSN (Print) | 2153-0858 |
| ISSN (elektronisch) | 2153-0866 |
Abstract
Soft material robotic systems provide increased adaptability and flexibility compared to conventional rigid metal robots. The soft systems benefit from their inherent compliance, which enables them to be used in applications that require safe interaction between humans and robots or manipulation in cluttered environment. Despite advancements in recent years research on soft material robots still needs to make progress in terms of modeling for model based control or path planning. The high nonlinearity of soft material robots makes efficient and accurate modeling difficult. In this work we introduce a kinematic modeling approach based on cubic hermite splines. The method is applied to a soft pneumatic actuator and evaluated against the widely used constant curvature approach. The hermite spline offers the possibility of accurate shape reconstruction from simulated or measured deformation data. Both the shape of a robot's segment and its orientation can be approximated this way. In this paper a machine learning approach is used to train the kinematic relation between actuating pressure and configuration parameters.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Software
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Informatik (insg.)
- Angewandte Informatik
Zitieren
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- Apa
- Vancouver
- BibTex
- RIS
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Institute of Electrical and Electronics Engineers Inc., 2019. S. 7176-7182 8967776 (IEEE International Conference on Intelligent Robots and Systems).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Kinematic Modeling of a Soft Pneumatic Actuator Using Cubic Hermite Splines
AU - Wiese, Mats
AU - Rustmann, Kenneth
AU - Raatz, Annika
PY - 2019/11
Y1 - 2019/11
N2 - Soft material robotic systems provide increased adaptability and flexibility compared to conventional rigid metal robots. The soft systems benefit from their inherent compliance, which enables them to be used in applications that require safe interaction between humans and robots or manipulation in cluttered environment. Despite advancements in recent years research on soft material robots still needs to make progress in terms of modeling for model based control or path planning. The high nonlinearity of soft material robots makes efficient and accurate modeling difficult. In this work we introduce a kinematic modeling approach based on cubic hermite splines. The method is applied to a soft pneumatic actuator and evaluated against the widely used constant curvature approach. The hermite spline offers the possibility of accurate shape reconstruction from simulated or measured deformation data. Both the shape of a robot's segment and its orientation can be approximated this way. In this paper a machine learning approach is used to train the kinematic relation between actuating pressure and configuration parameters.
AB - Soft material robotic systems provide increased adaptability and flexibility compared to conventional rigid metal robots. The soft systems benefit from their inherent compliance, which enables them to be used in applications that require safe interaction between humans and robots or manipulation in cluttered environment. Despite advancements in recent years research on soft material robots still needs to make progress in terms of modeling for model based control or path planning. The high nonlinearity of soft material robots makes efficient and accurate modeling difficult. In this work we introduce a kinematic modeling approach based on cubic hermite splines. The method is applied to a soft pneumatic actuator and evaluated against the widely used constant curvature approach. The hermite spline offers the possibility of accurate shape reconstruction from simulated or measured deformation data. Both the shape of a robot's segment and its orientation can be approximated this way. In this paper a machine learning approach is used to train the kinematic relation between actuating pressure and configuration parameters.
UR - http://www.scopus.com/inward/record.url?scp=85081166805&partnerID=8YFLogxK
U2 - 10.1109/IROS40897.2019.8967776
DO - 10.1109/IROS40897.2019.8967776
M3 - Conference contribution
AN - SCOPUS:85081166805
SN - 978-1-7281-4005-6
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 7176
EP - 7182
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Y2 - 3 November 2019 through 8 November 2019
ER -