Hongming Wang

Chinese Academy of Sciences, Shandong Institute of Automation

Papers

Total Citations

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About

Hongming Wang is a robotics researcher whose work focuses on autonomous navigation, sensor fusion, and environmental perception for mobile robots. His key contributions lie in developing intelligent systems that enable robots to understand and operate in complex, dynamic environments using sonar and multi-sensor data. Wang’s research addresses fundamental challenges in robotic mapping and control, including feature extraction, scene analysis, and adaptive tracking. His most cited work, "Sonar Feature Map Building for a Mobile Robot" (2007, 5 citations), introduces a novel approach combining data-level and feature-level fusion for constructing robust environmental maps. Another notable contribution, "Mapping Dynamic Environment Using Gaussian Mixture Model" (2007, 2 citations), pioneers the use of probabilistic models to distinguish static and moving objects—a critical capability for real-world deployment. Wang also advanced adaptive control theory with his work on neural network tracking for manipulators (2008, 3 citations). While his citation counts reflect a focused, early-career impact, his methodological innovations in sonar-based scene analysis and dynamic mapping have laid groundwork for subsequent research in autonomous robotics. Wang’s integration of kernel PCA for environmental classification further demonstrates his commitment to computationally efficient, perception-driven robotic systems.