Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 189-197 |
| Seitenumfang | 9 |
| Fachzeitschrift | At-Automatisierungstechnik |
| Jahrgang | 65 |
| Ausgabenummer | 3 |
| Publikationsstatus | Veröffentlicht - 11 März 2017 |
| Extern publiziert | Ja |
Abstract
This paper proposes a method for the automated generation of roadmaps for AGVs. So far the roadmaps are mostly generated manually, which leads to long and laborious planning phases. The presented method incorporates both mathematical roadmap algorithms as well as human knowledge in the form of a fuzzy inference system. The results of the expert system are evaluated in comparisons to the A∗ algorithm and to manually generated roadmaps on a real production layout. In both cases the expert system performs better.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Informatik (insg.)
- Angewandte Informatik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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in: At-Automatisierungstechnik, Jahrgang 65, Nr. 3, 11.03.2017, S. 189-197.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Combining a fuzzy inference system with an A∗ algorithm for the automated generation of roadmaps for Automated Guided Vehicles
AU - Uttendorf, Sarah
AU - Eilert, Björn
AU - Overmeyer, Ludger
PY - 2017/3/11
Y1 - 2017/3/11
N2 - This paper proposes a method for the automated generation of roadmaps for AGVs. So far the roadmaps are mostly generated manually, which leads to long and laborious planning phases. The presented method incorporates both mathematical roadmap algorithms as well as human knowledge in the form of a fuzzy inference system. The results of the expert system are evaluated in comparisons to the A∗ algorithm and to manually generated roadmaps on a real production layout. In both cases the expert system performs better.
AB - This paper proposes a method for the automated generation of roadmaps for AGVs. So far the roadmaps are mostly generated manually, which leads to long and laborious planning phases. The presented method incorporates both mathematical roadmap algorithms as well as human knowledge in the form of a fuzzy inference system. The results of the expert system are evaluated in comparisons to the A∗ algorithm and to manually generated roadmaps on a real production layout. In both cases the expert system performs better.
KW - Expertensystem
KW - FTF
KW - Fuzzy Logik
KW - Wegenetz
UR - http://www.scopus.com/inward/record.url?scp=85016047552&partnerID=8YFLogxK
U2 - 10.1515/auto-2016-0081
DO - 10.1515/auto-2016-0081
M3 - Article
AN - SCOPUS:85016047552
VL - 65
SP - 189
EP - 197
JO - At-Automatisierungstechnik
JF - At-Automatisierungstechnik
SN - 0178-2312
IS - 3
ER -