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.
Highlights
Faced with the large-scale construction for complex structures, the localization of mobile robot plays a key role in the quality of buildings
The localization performances for mobile 3D printing construction robot that based on the original and optimized artificial landmark map were analyzed in detail
5.2 Localization Results of Mobile Robot in 15 Stations For achieving the printing of large-scale buildings, the buildings are classified to 15 parts, and each part was printed in the designated station
Summary
Faced with the large-scale construction for complex structures, the localization of mobile robot plays a key role in the quality of buildings. The large-scale 3D printing process for buildings was investigated [4], and the corresponding robotic system are developed, including mainly the cable-driven parallel robot [5–8], vehicle-mounted robot [9] and mobile. The mobile robotics that integrated the manipulator and mobile platform is gradually developed to complete the large-scale printing instead of the formers. It can print structures with any shapes and sizes, and effectively avoids the trouble of installation. Ignoring the error of the manipulator, the printing quality and efficiency of buildings are indirectly determined by the localization accuracy of the mobile robot. Due to the architectural scene is unstructured and featureless, which poses a huge challenge to an accurate localization of mobile robot
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