Xiai Chen

About

Xiai Chen is a robotics researcher specializing in the calibration, performance testing, and intelligent control of industrial and mobile robotic systems. Her major contributions lie in advancing the accuracy and reliability of six-degree-of-freedom (6-DOF) serial industrial robots through innovative calibration methodologies. Notably, her work on sequential calibration of transmission ratios using laser trackers (8 citations) addresses the challenge of isolating parameter errors in kinematic models, while her sensitivity analysis of ISO 9283 performance tests (8 citations) provides critical insights into how error sources affect robot end positioning and orientation. Chen has also made notable contributions to autonomous mobile robotics, designing an Ackerman mobile robot system integrated with ROS and LiDAR (6 citations), and developing a monocular vision manipulator positioning system using neural networks (3 citations). Her research on intelligent disinfection robots (2 citations) demonstrates practical applications of ROS-based control and mapping algorithms. With a growing citation record and a focus on bridging theoretical calibration techniques with real-world robotic systems, Chen’s work is highly relevant for researchers and engineers working to improve industrial robot precision and autonomous navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   Sensitivity Analysis of Performance Tests for Six-Degree-of-Freedom Serial Industrial Robots

   8 citations · 2024
2. 2
   Sequential calibration of transmission ratios for joints of 6-DOF serial industrial robots based on laser tracker

   8 citations · 2023
3. 3
   Design of Ackerman Mobile Robot System Based on ROS and Lidar

   6 citations · 2021
4. 4
   Design of target positioning system for monocular vision manipulator based on neural network

   3 citations · 2021
5. 5
   Discussion on a Method of Designing Intelligent Disinfection Robot

   2 citations · 2022

Key Collaborators

Contact & Links