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An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution

Xiang, Y. 1; Liu, K. 1; Su, T.; Li, J.; Ouyang, S. 1; Mao, S. S.; Geimer, M. 1
1 Fakultät für Maschinenbau – Institut für Fahrzeugtechnik und Mobile Arbeitsmaschinen (IFFMA), Karlsruher Institut für Technologie (KIT)

Abstract:

Multi working-machines pathfinding solution enables more mobile machines simultaneously to work inside of a working site so that the productivity can be expected to increase evolutionary. To date, the potential cooperation conflicts among construction machinery limit the amount of construction machinery investment in a concrete working site. To solve the cooperation problem, civil engineers optimize the working site from a logistic perspective while computer scientists improve pathfinding algorithms’ performance on the given benchmark maps. In the practical implementation of a construction site, it is sensible to solve the problem with a hybrid solution; therefore, in our study, we proposed an algorithm based on a cutting-edge multi-pathfinding algorithm to enable the massive number of machines cooperation and offer the advice to modify the unreasonable part of the working site in the meantime. Using the logistic information from BIM, such as unloading and loading point, we added a pathfinding solution for multi machines to improve the whole construction fleet’s productivity. In the previous study, the experiments were limited to no more than ten participants, and the computational time to gather the solution was not given; thus, we publish our pseudo-code, our tested map, and benchmark our results. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000137762
Veröffentlicht am 23.09.2021
Originalveröffentlichung
DOI: 10.1109/ACCESS.2021.3110937
Scopus
Zitationen: 5
Web of Science
Zitationen: 2
Dimensions
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 2169-3536
KITopen-ID: 1000137762
Erschienen in IEEE Access
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Band 9
Nachgewiesen in Dimensions
Scopus
Web of Science
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