X
Xiao Yuan
Researcher at University of Southern California
Publications - 15
Citations - 676
Xiao Yuan is an academic researcher from University of Southern California. The author has contributed to research in topics: Sulfur concrete & Rotor (electric). The author has an hindex of 7, co-authored 15 publications receiving 405 citations. Previous affiliations of Xiao Yuan include Tsinghua University.
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Journal ArticleDOI
Cementitious materials for construction-scale 3D printing: Laboratory testing of fresh printing mixture
TL;DR: In this paper, a framework for performance-based laboratory testing of cementitious mixtures for construction-scale 3D printing is developed, where workability of a fresh "printing mixture" is studied in terms of print quality, shape stability, and printability window.
Journal ArticleDOI
Computer vision for real-time extrusion quality monitoring and control in robotic construction
TL;DR: The high precision and responsiveness of the developed system demonstrates the great potential for computer vision as a real-time quality monitoring and control tool for robotic construction.
Journal ArticleDOI
Construction by Contour Crafting using sulfur concrete with planetary applications
TL;DR: In this article, the authors report on the experiments with the Contour Crafting Automated Construction process using sulfur concrete as the choice of construction material and compare the results of simulation with the results obtained from experiments performed at centimeter and meter scales.
Proceedings ArticleDOI
Advances in Contour Crafting Technology for Extraterrestrial Settlement Infrastructure Buildup
TL;DR: In this paper, a synergetic simulation plan is proposed for utilizing these maturing systems coupled with a unique, patented robotic fabrication technology called Contour Crafting, tailored for swift and reliable lunar infrastructure development.
Journal ArticleDOI
Automated inspection in robotic additive manufacturing using deep learning for layer deformation detection
TL;DR: An automated layer defect detection system for construction 3D printing which is able to detect deformations in the printed concrete layers extracted from the images using the CNN model is proposed.