Xiaoqi Cheng

Papers

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About

Xiaoqi Cheng is a researcher specializing in sensor fusion, robotic perception, and precision metrology, with a focus on visual-inertial navigation systems (VINS) and structured-light 3D measurement. Their work addresses critical challenges in autonomous inspection and calibration. Cheng’s most cited paper, “Camera-IMU extrinsic calibration method based on intermittent sampling and RANSAC optimization” (2024, 3 citations), introduces a robust approach to calibrating extrinsic parameters between cameras and IMUs—a fundamental step for reliable sensor data fusion in navigation. By leveraging intermittent sampling and RANSAC optimization, this method mitigates timing delays from triggering and transmission, enhancing accuracy in real-world systems. Another notable contribution, “Pipeline inner surface 3D vision measuring system based on robot equipped with multi-directional structured-light sensor” (2025, 2 citations), develops a robotic system for automated pipeline inspection. This work integrates multi-directional structured-light sensors to achieve high-stability, interference-resistant 3D surface measurements, advancing detection capabilities for infrastructure maintenance. Though early in their career, Cheng’s research demonstrates practical impact in robotics and metrology, laying groundwork for more reliable autonomous systems in challenging environments like pipelines.