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Review of Robot Localization and Navigation Research Based on BIM
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Xiao-hui WANG, Si-tong CHEN*
Science Technology and Engineering | 2025, 25(21) : 8761 - 8772
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Science Technology and Engineering | 2025, 25(21): 8761-8772
Surveies·Automation and Computational Technology
Review of Robot Localization and Navigation Research Based on BIM
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Xiao-hui WANG, Si-tong CHEN*
Affiliations
  • School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Published: 2025-07-28 doi: 10.12404/j.issn.1671-1815.2407283
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Traditional robot localization and navigation methods in complex building environments are characterized by low accuracy, heavy reliance on sensors, and an inability to effectively address dynamic obstacles, making it challenging to achieve satisfactory results in practical applications. To address these issues, building information modeling (BIM) technology was introduced. BIM, with its geometric and semantic information, was utilized to assist robot localization and navigation in complex environments. More accurate environmental perception and optimal path planning were provided to robots, reducing the risk of collisions with environmental components and improving the accuracy and efficiency of task execution. The current status of BIM technology in robot localization, mapping, and path planning was compared, the advantages and challenges of its application in architectural environments were analyzed, and future prospects for its application in intelligent buildings and robotic intelligence were explored.

robot  /  autonomous localization and navigation  /  building information modeling (BIM)  /  mapping  /  path planning
Xiao-hui WANG, Si-tong CHEN. Review of Robot Localization and Navigation Research Based on BIM[J]. Science Technology and Engineering, 2025 , 25 (21) : 8761 -8772 . DOI: 10.12404/j.issn.1671-1815.2407283
Year 2025 volume 25 Issue 21
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doi: 10.12404/j.issn.1671-1815.2407283
  • Receive Date:2024-09-29
  • Online Date:2026-01-13
  • Published:2025-07-28
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  • Received:2024-09-29
  • Revised:2025-04-15
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    School of Intelligence Science and Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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