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About

Yucan Huang is a robotics researcher whose work focuses on advancing the autonomy and reliability of indoor inspection mobile robots. His key research areas include optimal trajectory planning, visual simultaneous localization and mapping (SLAM), and robust trajectory tracking control. Huang’s major contributions center on developing integrated solutions that overcome the limitations of traditional two-stage planning approaches. His most cited work, "Optimal Trajectory Planning for Wheeled Robots (OTPWR)" (2024, 4 citations), introduces a globally and dynamically optimal method that unifies global and local planning to produce continuous, efficient trajectories. In "W-VSLAM" (2024, 3 citations), he addresses critical challenges in visual-inertial estimation for mapping, tackling issues like redundant pose degrees of freedom and accelerometer drift. His paper on "Active Disturbance Rejection Trajectory Tracking Control" (2024, 2 citations) further enhances robot precision by applying Linear Active Disturbance Rejection Control to minimize angle and distance deviations during tracking. Together, these works demonstrate Huang’s commitment to creating seamless, high-performance robotic systems for real-world inspection tasks, marking him as an emerging innovator in mobile robotics.