Qinyan Huang
Papers
1
Total Citations
2
H-Index
1
About
Qinyan Huang is a researcher advancing the field of intelligent perception and robotics, with a primary focus on RFID-based localization and automation systems. Their most notable contribution is the development of a novel tag position perception method for RFID robots, detailed in their 2023 paper "An Indoor Tags Position Perception Method Based on GWO–MLP Algorithm for RFID Robot." This work addresses critical challenges in real-time spatial positioning of RFID tags for applications such as unmanned warehouse package retrieval and library book management. By integrating a Grey Wolf Optimizer with a Multilayer Perceptron neural network, Huang's method significantly improves the accuracy of predicting tag distributions based on signal strength (RSS) data during robotic inventory. Although early in their career, with 2 citations to date, this research demonstrates strong potential for impact in logistics automation and smart environments. Huang's work bridges machine learning and robotic perception, offering practical solutions for efficient, real-time inventory tracking. Their innovative approach positions them as an emerging contributor to intelligent systems and indoor localization technologies.
Research Focus
Key Achievements
Top Papers
- 1