Map construction for construction robot based on integrated improved algorithm

XUE Hui; ZHANG Zhenshan; ZHANG Yanwei; ZHU Zina; CUI Guohua; LU Shengyao

doi:10.12299/jsues.24-0169

Volume 39 Issue 4

Dec. 2025

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Article Navigation > Journal of Shanghai University of Engineering Science > 2025 > 39(4): 451-457

XUE Hui, ZHANG Zhenshan, ZHANG Yanwei, ZHU Zina, CUI Guohua, LU Shengyao. Map construction for construction robot based on integrated improved algorithm[J]. Journal of Shanghai University of Engineering Science, 2025, 39(4): 451-457. doi: 10.12299/jsues.24-0169

Citation:

XUE Hui, ZHANG Zhenshan, ZHANG Yanwei, ZHU Zina, CUI Guohua, LU Shengyao. Map construction for construction robot based on integrated improved algorithm[J]. Journal of Shanghai University of Engineering Science, 2025, 39(4): 451-457. doi: 10.12299/jsues.24-0169

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Map construction for construction robot based on integrated improved algorithm

doi: 10.12299/jsues.24-0169

School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

Received Date: 2024-06-12
Available Online: 2026-02-02
Publish Date: 2025-12-01

Abstract

Abstract

The construction environment is characterized by unstructured, large workspace, and construction processes that are significantly influenced by on-site conditions. To address problems such as inaccurate pose estimation, incomplete map display, and more residual shadows in highly dynamic scenes during construction robot localization and mapping, multiple sensors including dual LiDAR, inertial measurement unit (IMU), and wheeled odometry were fused. Based on the Cartographer algorithm framework, an extended Kalman filter was employed to optimize the multi-sensor for more accurate pose estimation. Furthermore, dynamic obstacle point clouds were filtered and removed from the raw laser scan data to enhance mapping quality. Experimental results show that the proposed improved data fusion Cartographer algorithm can improve map quality and positioning accuracy, meeting the requirements for map construction in construction environment.
- construction environment,
- multi-sensor,
- extended Kalman filter,
- dynamic barriers,
- map construction

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References(19)

References

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