Erlan Wang

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About

Erlan Wang is a robotics researcher whose work focuses on the dynamic modeling, control, and visual localization of autonomous systems. His most significant contribution lies in the static balancing of robotic bicycles, where he developed a method to maintain balance at zero velocity. By deriving a novel linearized dynamic equation from a nonlinear bicycle model near large steer angles, Wang enabled the application of Linear Quadratic Regulator (LQR) control to achieve stable equilibrium. This work, published in 2018 and garnering 14 citations, represents a notable advancement in two-wheeled robotics, addressing a fundamental challenge in low-speed maneuverability. Additionally, Wang has explored indoor robot positioning, proposing a visual system that leverages floor features captured by a fisheye camera and processed with Canny edge detection. While this work has received 2 citations, it demonstrates his versatility in tackling practical localization problems. Wang’s research bridges theoretical control design with real-world robotic applications, offering valuable insights for students and researchers interested in nonlinear dynamics, balance control, and vision-based navigation.