Gan Chen

Papers

Total Citations

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About

Gan Chen is a robotics researcher whose work bridges the gap between theoretical control systems and practical, low-cost hardware. His primary research areas include mobile robot trajectory tracking, robust control of inverted pendulums, and the application of neural networks to systems with limited sensing. Chen’s most notable contribution is an online neural network trajectory tracking controller for tracked mobile robots, which overcomes the extreme challenge of using only three binary sensors—devices that return only 0 or 1. This work, cited 18 times, demonstrates how intelligent algorithms can compensate for poor-quality hardware, making advanced robotics more accessible. In another highly cited paper (14 citations), Chen tackled the classic two-wheeled inverted pendulum problem using LEGO Mindstorms, synthesizing a robust H₂ control system that accounts for real-world modeling uncertainties. This achievement is particularly impressive for its use of an affordable, educational platform to explore complex control theory. Chen’s research is distinguished by its focus on implementing sophisticated control strategies on simple, low-fidelity hardware, offering practical solutions for students and researchers working with limited resources. His work continues to inspire cost-effective approaches to autonomous systems and mobile robotics.