Papers
8
Total Citations
48
H-Index
5
About
Wan-Ming Chen is a robotics and autonomous systems researcher whose work spans mobile robot navigation, legged robot control, and sensor-based localization — fields that sit at the intersection of embedded systems, artificial intelligence, and mechanical engineering. Chen's most significant contributions center on leveraging Wireless Sensor Networks (WSN) as an alternative to GPS for indoor and complex-environment robot navigation, proposing environment-map-free navigation frameworks that enable robots to operate online without pre-built maps — work that has garnered 13 citations and influenced subsequent localization research. Chen also made notable advances in quadruped robotics, developing a 9-link dynamic model using the Lagrangian method and pioneering control architectures that fuse Central Pattern Generators (CPG) with Fuzzy Neural Networks, drawing on biological locomotion principles to improve robotic gait stability. Further contributions include a WSN-aided Simultaneous Localization and Mapping (SLAM) strategy using particle filtering, addressing longstanding challenges of high-dimensional state spaces and data association in traditional SLAM algorithms. A vision-based localization method combining background subtraction and optical flow tracking rounds out Chen's diverse portfolio. With a productive publication cluster in 2007–2008, Chen established a focused body of work reflecting deep expertise in intelligent, sensor-driven robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Environment-Map-free Robot Navigation Based on Wireless Sensor Networks13 citations · 2007
- 2Modeling and Robust Control of Quadruped Robot7 citations · 2007
- 3Particle filtering for WSN aided SLAM7 citations · 2008
- 4Design of Quadruped Robot Based CPG and Fuzzy Neural Network7 citations · 2007
- 5Design of Quadruped Robot Based Neural Network5 citations · 2007
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