An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution
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 machi...
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doaj-35e2f04426844eeba97eadd3c3914bf12021-09-14T23:01:20ZengIEEEIEEE Access2169-35362021-01-01912458312459910.1109/ACCESS.2021.31109379530529An Extension of BIM Using AI: A Multi Working-Machines Pathfinding SolutionYusheng Xiang0https://orcid.org/0000-0002-4306-961XKailun Liu1Tianqing Su2Jun Li3Shirui Ouyang4Samuel S. Mao5Marcus Geimer6Elephant Tech LLC, Shenzhen, ChinaInstitute of Mobile Machines, Karlsruhe Institute of Technology, Karlsruhe, GermanyElephant Tech LLC, Shenzhen, ChinaElephant Tech LLC, Shenzhen, ChinaInstitute of Mobile Machines, Karlsruhe Institute of Technology, Karlsruhe, GermanyElephant Tech LLC, Shenzhen, ChinaInstitute of Mobile Machines, Karlsruhe Institute of Technology, Karlsruhe, GermanyMulti 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. Our algorithm’s most extensive feature is that it can quickly replan the path to overcome the emergency on a construction site.https://ieeexplore.ieee.org/document/9530529/Smart working sitemulti agents pathfindingconflict based searchingbuilding information modelconstruction site productivityHuoshenshan hospital project |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yusheng Xiang Kailun Liu Tianqing Su Jun Li Shirui Ouyang Samuel S. Mao Marcus Geimer |
spellingShingle |
Yusheng Xiang Kailun Liu Tianqing Su Jun Li Shirui Ouyang Samuel S. Mao Marcus Geimer An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution IEEE Access Smart working site multi agents pathfinding conflict based searching building information model construction site productivity Huoshenshan hospital project |
author_facet |
Yusheng Xiang Kailun Liu Tianqing Su Jun Li Shirui Ouyang Samuel S. Mao Marcus Geimer |
author_sort |
Yusheng Xiang |
title |
An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution |
title_short |
An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution |
title_full |
An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution |
title_fullStr |
An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution |
title_full_unstemmed |
An Extension of BIM Using AI: A Multi Working-Machines Pathfinding Solution |
title_sort |
extension of bim using ai: a multi working-machines pathfinding solution |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
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. Our algorithm’s most extensive feature is that it can quickly replan the path to overcome the emergency on a construction site. |
topic |
Smart working site multi agents pathfinding conflict based searching building information model construction site productivity Huoshenshan hospital project |
url |
https://ieeexplore.ieee.org/document/9530529/ |
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