Details
| Original language | English |
|---|---|
| Title of host publication | 2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 |
| Publisher | IEEE Computer Society |
| Pages | 977-981 |
| Number of pages | 5 |
| ISBN (electronic) | 9781509036653 |
| Publication status | Published - 27 Dec 2016 |
| Externally published | Yes |
| Event | 2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016 - Bali, Indonesia Duration: 4 Dec 2016 → 7 Dec 2016 |
Publication series
| Name | IEEE International Conference on Industrial Engineering and Engineering Management |
|---|---|
| Volume | 2016-December |
| ISSN (Print) | 2157-3611 |
| ISSN (electronic) | 2157-362X |
Abstract
So far the generation of roadmaps for automated guided vehicles (AGVs) is mostly performed manually. Mathematical path finding algorithms often return results that are mathematically optimal but not applicable to a real production layout. This paper proposes an expert system as a solution that combines traditional path finding algorithms (in the form of a modified version of the A∗ and the Bellman-Ford algorithm) with a fuzzy inference system that incorporates the human knowledge of AGV system planners. Results that prove the efficiency of the proposed solution are shown in the end.
Keywords
- automated guided vehicles, fuzzy logic, path planning, roadmaps
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Business, Management and Accounting (miscellaneous)
- Engineering(all)
- Industrial and Manufacturing Engineering
- Engineering(all)
- Safety, Risk, Reliability and Quality
Cite this
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2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016. IEEE Computer Society, 2016. p. 977-981 7798023 (IEEE International Conference on Industrial Engineering and Engineering Management; Vol. 2016-December).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A fuzzy logic expert system for the automated generation of roadmaps for automated guided vehicle systems
AU - Uttendorf, Sarah
AU - Eilert, Björn
AU - Overmeyer, Ludger
PY - 2016/12/27
Y1 - 2016/12/27
N2 - So far the generation of roadmaps for automated guided vehicles (AGVs) is mostly performed manually. Mathematical path finding algorithms often return results that are mathematically optimal but not applicable to a real production layout. This paper proposes an expert system as a solution that combines traditional path finding algorithms (in the form of a modified version of the A∗ and the Bellman-Ford algorithm) with a fuzzy inference system that incorporates the human knowledge of AGV system planners. Results that prove the efficiency of the proposed solution are shown in the end.
AB - So far the generation of roadmaps for automated guided vehicles (AGVs) is mostly performed manually. Mathematical path finding algorithms often return results that are mathematically optimal but not applicable to a real production layout. This paper proposes an expert system as a solution that combines traditional path finding algorithms (in the form of a modified version of the A∗ and the Bellman-Ford algorithm) with a fuzzy inference system that incorporates the human knowledge of AGV system planners. Results that prove the efficiency of the proposed solution are shown in the end.
KW - automated guided vehicles
KW - fuzzy logic
KW - path planning
KW - roadmaps
UR - http://www.scopus.com/inward/record.url?scp=85009841304&partnerID=8YFLogxK
U2 - 10.1109/ieem.2016.7798023
DO - 10.1109/ieem.2016.7798023
M3 - Conference contribution
AN - SCOPUS:85009841304
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 977
EP - 981
BT - 2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
PB - IEEE Computer Society
T2 - 2016 International Conference on Industrial Engineering and Engineering Management, IEEM 2016
Y2 - 4 December 2016 through 7 December 2016
ER -