Yinan Guo

China University of Mining and Technology

Papers

Total Citations

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About

Yinan Guo is a researcher whose work lies at the intersection of robotics and computational intelligence, with a primary focus on developing sophisticated path planning algorithms for autonomous systems. Her major contributions center on solving the NP-complete problem of robot navigation in complex, hybrid-terrain environments—a challenge where traditional methods fall short. Guo pioneered the integration of cultural algorithms and dual evolution strategies, leveraging both common sense and evolution knowledge to create adaptive path planning solutions. Her most cited work, "A fast robot path planning algorithm based on bidirectional associative learning" (2021, 12 citations), represents a significant advancement in the field, introducing a novel approach that dramatically improves computational efficiency. Earlier foundational papers, including "Path planning method for robots in complex ground environment based on cultural algorithm" (2009, 4 citations) and "Knowledge-inducing Global Path Planning for Robots in Environment with Hybrid Terrain" (2010, 2 citations), established her reputation for tackling real-world navigation challenges where road conditions and terrain types vary across regions. Guo’s research has been particularly notable for its practical applicability, addressing the critical gap between theoretical path planning and the messy realities of outdoor robotic navigation. Her work continues to influence the development of more intelligent, terrain-aware autonomous systems.