Xiaoting Guo

Sinomach (China), Shenyang Conservatory of Music

Papers

Total Citations

H-Index

About

Xiaoting Guo is a leading researcher in pipeline inspection robotics, specializing in the design, dynamic simulation, and experimental validation of advanced in-pipe detection systems. Her work focuses on solving critical challenges in the maintenance of oil and gas infrastructure, particularly through the development of self-propelled crawlers and high-definition magnetic flux leakage (MFL) detection robots. Guo’s most cited paper, “Dynamic Simulation Analysis and Experiment of Large-caliber Self-propelled Pipeline Crawler Based on ADAMS” (2021, 9 citations), provides a rigorous framework for analyzing the complex force states and torque outputs of driving wheels during horizontal, climbing, and turning maneuvers—a key advancement for reliable autonomous navigation. She further contributed the “Design and Validation of Three-Axis High Definition Magnetic Flux Leakage Detection Robot for Oil/Gas Pipelines” (2020, 3 citations), which integrates multi-axis MFL sensors for precise defect identification. Though her citation counts are modest, Guo’s work is foundational for engineers seeking to improve pipeline safety and reduce manual inspection risks. Her research bridges theoretical simulation with practical experimentation, offering actionable insights for next-generation robotic inspection systems.