Papers
1
Total Citations
2
H-Index
1
About
Qing Huang is a researcher specializing in the intersection of robotics, machine learning, and intelligent systems, with a particular focus on autonomous cleaning technologies. Their most notable contribution is the development of a novel evaluation method for cleaning robot performance, detailed in their 2022 paper "Research of Evaluation Method of Cleaning Performance for Cleaning Robots Based on Machine Learning." In this work, Huang pioneered the use of machine learning to analyze and extract key impact factors—such as stain area, color intensity, and moisture level—to create a stain recognition model. Achieving a precision rate of 95.7% and a recall rate of 85.9%, this model represents a significant advancement in quantifying and optimizing cleaning efficiency. While early in its citation impact, this research lays critical groundwork for smarter, data-driven home and industrial automation. Huang’s work bridges practical engineering challenges with cutting-edge AI, offering a systematic framework that could shape future standards in robotic cleaning performance assessment.
Research Focus
Key Achievements
Top Papers
- 1