Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS |
| Seiten | 444-449 |
| Seitenumfang | 6 |
| Publikationsstatus | Veröffentlicht - 2005 |
| Veranstaltung | IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005 - Edmonton, AB, Kanada Dauer: 2 Aug. 2005 → 6 Aug. 2005 |
Abstract
This paper presents a complete approach for parametrization of model- and knowledge-based controller for parallel robots. By combining and merging methodologies from mechanics, system theory, information processing and intelligent control, an accurate and compact method resulted and is substantiated with experimental results achieved on an innovative hexapod PaLiDA. An appropriate form of excitation trajectories helps to overcome classical identification problems, like disturbances in the acceleration signals. The Gauss-Markov estimator is applied for solving the over determined linear equation system. A novel method is presented that uses statistical and uncertainty attributes of the estimate for choosing an optimal structure and parameter number of the dynamics model.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Artificial intelligence
- Informatik (insg.)
- Maschinelles Sehen und Mustererkennung
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
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- BibTex
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2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS. 2005. S. 444-449 1545021.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Identification and appropriate parametrization of parallel robot dynamic models by using estimation statistical properties
AU - Abdellatif, H.
AU - Heimann, Bodo
AU - Hornung, Oliver
AU - Grotjahn, Martin
PY - 2005
Y1 - 2005
N2 - This paper presents a complete approach for parametrization of model- and knowledge-based controller for parallel robots. By combining and merging methodologies from mechanics, system theory, information processing and intelligent control, an accurate and compact method resulted and is substantiated with experimental results achieved on an innovative hexapod PaLiDA. An appropriate form of excitation trajectories helps to overcome classical identification problems, like disturbances in the acceleration signals. The Gauss-Markov estimator is applied for solving the over determined linear equation system. A novel method is presented that uses statistical and uncertainty attributes of the estimate for choosing an optimal structure and parameter number of the dynamics model.
AB - This paper presents a complete approach for parametrization of model- and knowledge-based controller for parallel robots. By combining and merging methodologies from mechanics, system theory, information processing and intelligent control, an accurate and compact method resulted and is substantiated with experimental results achieved on an innovative hexapod PaLiDA. An appropriate form of excitation trajectories helps to overcome classical identification problems, like disturbances in the acceleration signals. The Gauss-Markov estimator is applied for solving the over determined linear equation system. A novel method is presented that uses statistical and uncertainty attributes of the estimate for choosing an optimal structure and parameter number of the dynamics model.
KW - Dynamics
KW - Identification
KW - Intelligent control
KW - Parallel manipulators
UR - http://www.scopus.com/inward/record.url?scp=43049182592&partnerID=8YFLogxK
U2 - 10.1109/IROS.2005.1545021
DO - 10.1109/IROS.2005.1545021
M3 - Conference contribution
AN - SCOPUS:43049182592
SN - 0780389123
SN - 9780780389120
SP - 444
EP - 449
BT - 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
T2 - IEEE IRS/RSJ International Conference on Intelligent Robots and Systems, IROS 2005
Y2 - 2 August 2005 through 6 August 2005
ER -