Yan

Papers

Total Citations

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About

Yan’s research focuses on mobile robotics, particularly in path planning and self-localization for autonomous navigation. Their major contributions include developing an improved genetic algorithm for dynamic path planning, which enhances robot adaptability in complex environments by optimizing routes in real time. This work, published in 2010, has garnered 28 citations, reflecting its relevance to robotic navigation challenges. Yan also advanced vision-based self-localization using a Maximum A Posteriori (MAP) approach, integrating odometry and monocular camera data through nonlinear models and unscented transforms to handle sensor imprecision. This system, detailed in a 2008 paper with 5 citations, enables robust pose estimation in 3D environments with landmarks, emphasizing probabilistic geometry and statistical data association. Additionally, Yan explored hybrid methods combining improved artificial potential fields with optimization algorithms for path planning, contributing to safer and more efficient robot movement. Their work is notable for systematically addressing real-world uncertainties, such as sensor noise and motion dynamics, through rigorous experimental validation. Yan’s research offers practical insights for students and engineers working on autonomous systems, balancing theoretical rigor with application-driven solutions.