Yulan Hu

Papers

Total Citations

H-Index

About

Yulan Hu is a researcher in robotics and computational intelligence, with a primary focus on path planning and optimization algorithms. Her most cited work, "Robot Path Planning Method Based on Improved Genetic Algorithm" (2013), introduces a novel approach that integrates artificial potential fields into the initialization of genetic algorithm populations. By adjusting value weights within the fitness function, Hu’s method enhances both the controllability of path length and the smoothness of robot trajectories—key factors for efficient and safe autonomous navigation. This contribution addresses a longstanding challenge in mobile robotics: balancing computational efficiency with path quality. Although her citation count is modest, with the paper accumulating 6 citations, the work demonstrates a practical synthesis of evolutionary computation and robotic control. Hu’s research is particularly valuable for students and engineers seeking to understand how hybrid algorithms can improve real-world robot performance. Her approach offers a clear, implementable framework for those exploring adaptive path planning in dynamic environments, marking her as a thoughtful contributor to the intersection of artificial intelligence and robotics.