Vol.130, No.3, 2022, pp.1853-1882, doi:10.32604/cmes.2022.018004
OPEN ACCESS
ARTICLE
Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene
  • Zhen Xu1, Shuai Guo1,2,*, Tao Song1, Yuwen Li1, Lingdong Zeng1
1 Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, China
2 National Demonstration Center for Experimental Engineering Training Education, Shanghai University, Shanghai, 200444, China
* Corresponding Author: Shuai Guo. Email:
(This article belongs to this Special Issue: Modeling and Analysis of Autonomous Intelligence)
Received 22 June 2021; Accepted 28 September 2021; Issue published 30 December 2021
Abstract
The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability. Localization of mobile robot is increasingly important for the printing of buildings in the construction scene. Although many available studies on the localization have been conducted, only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes. To realize the accurate localization of mobile robot in designated stations, we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map. Then, the performances of localization for mobile robot based on the original and optimized map are compared and evaluated. Finally, experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21% compared to that of the original map.
Keywords
Large-scale construction; artificial landmark map; localization; mobile robot; non-linear optimization
Cite This Article
Xu, Z., Guo, S., Song, T., Li, Y., Zeng, L. (2022). Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene. CMES-Computer Modeling in Engineering & Sciences, 130(3), 1853–1882.
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