Xiuqing Yang

About

Dr. Xiuqing Yang is a leading researcher in the field of robotic mobile fulfillment systems (RMFS) and intelligent warehouse automation. Her work focuses on optimizing the efficiency of "parts-to-picker" storage systems, where robots transport pods to stationary workstations. Dr. Yang’s major contributions include pioneering studies on order and rack sequencing for systems with multiple picking stations, as well as innovative non-traditional layout designs that significantly improve throughput in high-density storage warehouses. Her research on mobile robot path planning has also been highly influential, particularly her development of an adaptive ant colony optimization algorithm and a time taboo ant colony optimization method, which solve critical challenges like slow convergence and navigation in dynamic environments. Additionally, she has advanced indoor robot localization and mapping using LIDAR and an improved RBPF-SLAM algorithm. With her most-cited papers accumulating over 120 citations, Dr. Yang’s work is essential reading for engineers and researchers seeking to enhance the speed, accuracy, and autonomy of modern logistics and robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Order and rack sequencing in a robotic mobile fulfillment system with multiple picking stations

   35 citations · 2022
2. 2
   A simulation study on the robotic mobile fulfillment system in high-density storage warehouses

   32 citations · 2021
3. 3
   Mobile Robot Path Planning Based on Time Taboo Ant Colony Optimization in Dynamic Environment

   28 citations · 2021
4. 4
   Non-Traditional Layout Design for Robotic Mobile Fulfillment System with Multiple Workstations

   9 citations · 2021
5. 5
   Localization and Mapping Algorithm for the Indoor Mobile Robot Based on LIDAR

   9 citations · 2020
6. 6
   Path Planning of Mobile Robot Based on Adaptive Ant Colony Optimization

   7 citations · 2021

Key Collaborators

Contact & Links